Bitcoins the hard way: Using the raw Bitcoin protocol

All the recent media attention on Bitcoin inspired me to learn how Bitcoin really works, right down to the bytes flowing through the network. Normal people use software[1] that hides what is really going on, but I wanted to get a hands-on understanding of the Bitcoin protocol. My goal was to use the Bitcoin system directly: create a Bitcoin transaction manually, feed it into the system as hex data, and see how it gets processed. This turned out to be considerably harder than I expected, but I learned a lot in the process and hopefully you will find it interesting.

(Feb 23: I have a new article that covers the technical details of mining. If you like this article, check out my mining article too.)

This blog post starts with a quick overview of Bitcoin and then jumps into the low-level details: creating a Bitcoin address, making a transaction, signing the transaction, feeding the transaction into the peer-to-peer network, and observing the results.

A quick overview of Bitcoin

I'll start with a quick overview of how Bitcoin works[2], before diving into the details. Bitcoin is a relatively new digital currency[3] that can be transmitted across the Internet. You can buy bitcoins[4] with dollars or other traditional money from sites such as Coinbase or MtGox[5], send bitcoins to other people, buy things with them at some places, and exchange bitcoins back into dollars.

To simplify slightly, bitcoins consist of entries in a distributed database that keeps track of the ownership of bitcoins. Unlike a bank, bitcoins are not tied to users or accounts. Instead bitcoins are owned by a Bitcoin address, for example 1KKKK6N21XKo48zWKuQKXdvSsCf95ibHFa.

Bitcoin transactions

A transaction is the mechanism for spending bitcoins. In a transaction, the owner of some bitcoins transfers ownership to a new address.

A key innovation of Bitcoin is how transactions are recorded in the distributed database through mining. Transactions are grouped into blocks and about every 10 minutes a new block of transactions is sent out, becoming part of the transaction log known as the blockchain, which indicates the transaction has been made (more-or-less) official.[6] Bitcoin mining is the process that puts transactions into a block, to make sure everyone has a consistent view of the transaction log. To mine a block, miners must find an extremely rare solution to an (otherwise-pointless) cryptographic problem. Finding this solution generates a mined block, which becomes part of the official block chain.

Mining is also the mechanism for new bitcoins to enter the system. When a block is successfully mined, new bitcoins are generated in the block and paid to the miner. This mining bounty is large - currently 25 bitcoins per block (about $19,000). In addition, the miner gets any fees associated with the transactions in the block. Because of this, mining is very competitive with many people attempting to mine blocks. The difficulty and competitiveness of mining is a key part of Bitcoin security, since it ensures that nobody can flood the system with bad blocks.

The peer-to-peer network

There is no centralized Bitcoin server. Instead, Bitcoin runs on a peer-to-peer network. If you run a Bitcoin client, you become part of that network. The nodes on the network exchange transactions, blocks, and addresses of other peers with each other. When you first connect to the network, your client downloads the blockchain from some random node or nodes. In turn, your client may provide data to other nodes. When you create a Bitcoin transaction, you send it to some peer, who sends it to other peers, and so on, until it reaches the entire network. Miners pick up your transaction, generate a mined block containing your transaction, and send this mined block to peers. Eventually your client will receive the block and your client shows that the transaction was processed.

Cryptography

Bitcoin uses digital signatures to ensure that only the owner of bitcoins can spend them. The owner of a Bitcoin address has the private key associated with the address. To spend bitcoins, they sign the transaction with this private key, which proves they are the owner. (It's somewhat like signing a physical check to make it valid.) A public key is associated with each Bitcoin address, and anyone can use it to verify the digital signature.

Blocks and transactions are identified by a 256-bit cryptographic hash of their contents. This hash value is used in multiple places in the Bitcoin protocol. In addition, finding a special hash is the difficult task in mining a block.

Bitcoin statistic coin ANTANA

Bitcoins do not really look like this. Photo credit: Antana, CC:by-sa

Diving into the raw Bitcoin protocol

The remainder of this article discusses, step by step, how I used the raw Bitcoin protocol. First I generated a Bitcoin address and keys. Next I made a transaction to move a small amount of bitcoins to this address. Signing this transaction took me a lot of time and difficulty. Finally, I fed this transaction into the Bitcoin peer-to-peer network and waited for it to get mined. The remainder of this article describes these steps in detail.

It turns out that actually using the Bitcoin protocol is harder than I expected. As you will see, the protocol is a bit of a jumble: it uses big-endian numbers, little-endian numbers, fixed-length numbers, variable-length numbers, custom encodings, DER encoding, and a variety of cryptographic algorithms, seemingly arbitrarily. As a result, there's a lot of annoying manipulation to get data into the right format.[7]

The second complication with using the protocol directly is that being cryptographic, it is very unforgiving. If you get one byte wrong, the transaction is rejected with no clue as to where the problem is.[8]

The final difficulty I encountered is that the process of signing a transaction is much more difficult than necessary, with a lot of details that need to be correct. In particular, the version of a transaction that gets signed is very different from the version that actually gets used.

Bitcoin addresses and keys

My first step was to create a Bitcoin address. Normally you use Bitcoin client software to create an address and the associated keys. However, I wrote some Python code to create the address, showing exactly what goes on behind the scenes.

Bitcoin uses a variety of keys and addresses, so the following diagram may help explain them. You start by creating a random 256-bit private key. The private key is needed to sign a transaction and thus transfer (spend) bitcoins. Thus, the private key must be kept secret or else your bitcoins can be stolen.

The Elliptic Curve DSA algorithm generates a 512-bit public key from the private key. (Elliptic curve cryptography will be discussed later.) This public key is used to verify the signature on a transaction. Inconveniently, the Bitcoin protocol adds a prefix of 04 to the public key. The public key is not revealed until a transaction is signed, unlike most systems where the public key is made public.

How bitcoin keys and addresses are related

How bitcoin keys and addresses are related

The next step is to generate the Bitcoin address that is shared with others. Since the 512-bit public key is inconveniently large, it is hashed down to 160 bits using the SHA-256 and RIPEMD hash algorithms.[9] The key is then encoded in ASCII using Bitcoin's custom Base58Check encoding.[10] The resulting address, such as 1KKKK6N21XKo48zWKuQKXdvSsCf95ibHFa, is the address people publish in order to receive bitcoins. Note that you cannot determine the public key or the private key from the address. If you lose your private key (for instance by throwing out your hard drive), your bitcoins are lost forever.

Finally, the Wallet Interchange Format key (WIF) is used to add a private key to your client wallet software. This is simply a Base58Check encoding of the private key into ASCII, which is easily reversed to obtain the 256-bit private key. (I was curious if anyone would use the private key above to steal my 80 cents of bitcoins, and sure enough someone did.)

To summarize, there are three types of keys: the private key, the public key, and the hash of the public key, and they are represented externally in ASCII using Base58Check encoding. The private key is the important key, since it is required to access the bitcoins and the other keys can be generated from it. The public key hash is the Bitcoin address you see published.

I used the following code snippet[11] to generate a private key in WIF format and an address. The private key is simply a random 256-bit number. The ECDSA crypto library generates the public key from the private key.[12] The Bitcoin address is generated by SHA-256 hashing, RIPEMD-160 hashing, and then Base58 encoding with checksum. Finally, the private key is encoded in Base58Check to generate the WIF encoding used to enter a private key into Bitcoin client software.[1] Note: this Python random function is not cryptographically strong; use a better function if you're doing this for real.

Inside a transaction

A transaction is the basic operation in the Bitcoin system. You might expect that a transaction simply moves some bitcoins from one address to another address, but it's more complicated than that. A Bitcoin transaction moves bitcoins between one or more inputs and outputs. Each input is a transaction and address supplying bitcoins. Each output is an address receiving bitcoin, along with the amount of bitcoins going to that address.

A sample Bitcoin transaction. Transaction C spends .008 bitcoins from Transactions A and B.

A sample Bitcoin transaction. Transaction C spends .008 bitcoins from Transactions A and B.

The diagram above shows a sample transaction "C". In this transaction, .005 BTC are taken from an address in Transaction A, and .003 BTC are taken from an address in Transaction B. (Note that arrows are references to the previous outputs, so are backwards to the flow of bitcoins.) For the outputs, .003 BTC are directed to the first address and .004 BTC are directed to the second address. The leftover .001 BTC goes to the miner of the block as a fee. Note that the .015 BTC in the other output of Transaction A is not spent in this transaction.

Each input used must be entirely spent in a transaction. If an address received 100 bitcoins in a transaction and you just want to spend 1 bitcoin, the transaction must spend all 100. The solution is to use a second output for change, which returns the 99 leftover bitcoins back to you.

Transactions can also include fees. If there are any bitcoins left over after adding up the inputs and subtracting the outputs, the remainder is a fee paid to the miner. The fee isn't strictly required, but transactions without a fee will be a low priority for miners and may not be processed for days or may be discarded entirely.[13] A typical fee for a transaction is 0.0002 bitcoins (about 20 cents), so fees are low but not trivial.

Manually creating a transaction

For my experiment I used a simple transaction with one input and one output, which is shown below. I started by buying bitcoins from Coinbase and putting 0.00101234 bitcoins into address 1MMMMSUb1piy2ufrSguNUdFmAcvqrQF8M5, which was transaction 81b4c832.... My goal was to create a transaction to transfer these bitcoins to the address I created above, 1KKKK6N21XKo48zWKuQKXdvSsCf95ibHFa, subtracting a fee of 0.0001 bitcoins. Thus, the destination address will receive 0.00091234 bitcoins.

Structure of the example Bitcoin transaction.

Structure of the example Bitcoin transaction.

Following the specification, the unsigned transaction can be assembled fairly easily, as shown below. There is one input, which is using output 0 (the first output) from transaction 81b4c832.... Note that this transaction hash is inconveniently reversed in the transaction. The output amount is 0.00091234 bitcoins (91234 is 0x016462 in hex), which is stored in the value field in little-endian form. The cryptographic parts - scriptSig and scriptPubKey - are more complex and will be discussed later.

version01 00 00 00
input count01
inputprevious output hash
(reversed)
48 4d 40 d4 5b 9e a0 d6 52 fc a8 25 8a b7 ca a4 25 41 eb 52 97 58 57 f9 6f b5 0c d7 32 c8 b4 81
previous output index00 00 00 00
script length
scriptSigscript containing signature
sequenceff ff ff ff
output count01
outputvalue62 64 01 00 00 00 00 00
script length
scriptPubKeyscript containing destination address
block lock time00 00 00 00

Here's the code I used to generate this unsigned transaction. It's just a matter of packing the data into binary. Signing the transaction is the hard part, as you'll see next.

How Bitcoin transactions are signed

The following diagram gives a simplified view of how transactions are signed and linked together.[14] Consider the middle transaction, transferring bitcoins from address B to address C. The contents of the transaction (including the hash of the previous transaction) are hashed and signed with B's private key. In addition, B's public key is included in the transaction.

By performing several steps, anyone can verify that the transaction is authorized by B. First, B's public key must correspond to B's address in the previous transaction, proving the public key is valid. (The address can easily be derived from the public key, as explained earlier.) Next, B's signature of the transaction can be verified using the B's public key in the transaction. These steps ensure that the transaction is valid and authorized by B. One unexpected part of Bitcoin is that B's public key isn't made public until it is used in a transaction.

With this system, bitcoins are passed from address to address through a chain of transactions. Each step in the chain can be verified to ensure that bitcoins are being spent validly. Note that transactions can have multiple inputs and outputs in general, so the chain branches out into a tree.

How Bitcoin transactions are chained together.

How Bitcoin transactions are chained together.[14]

The Bitcoin scripting language

You might expect that a Bitcoin transaction is signed simply by including the signature in the transaction, but the process is much more complicated. In fact, there is a small program inside each transaction that gets executed to decide if a transaction is valid. This program is written in Script, the stack-based Bitcoin scripting language. Complex redemption conditions can be expressed in this language. For instance, an escrow system can require two out of three specific users must sign the transaction to spend it. Or various types of contracts can be set up.[15]

The Script language is surprisingly complex, with about 80 different opcodes. It includes arithmetic, bitwise operations, string operations, conditionals, and stack manipulation. The language also includes the necessary cryptographic operations (SHA-256, RIPEMD, etc.) as primitives. In order to ensure that scripts terminate, the language does not contain any looping operations. (As a consequence, it is not Turing-complete.) In practice, however, only a few types of transactions are supported.[16]

In order for a Bitcoin transaction to be valid, the two parts of the redemption script must run successfully. The script in the old transaction is called scriptPubKey and the script in the new transaction is called scriptSig. To verify a transaction, the scriptSig executed followed by the scriptPubKey. If the script completes successfully, the transaction is valid and the Bitcoin can be spent. Otherwise, the transaction is invalid. The point of this is that the scriptPubKey in the old transaction defines the conditions for spending the bitcoins. The scriptSig in the new transaction must provide the data to satisfy the conditions.

In a standard transaction, the scriptSig pushes the signature (generated from the private key) to the stack, followed by the public key. Next, the scriptPubKey (from the source transaction) is executed to verify the public key and then verify the signature.

As expressed in Script, the scriptSig is:

PUSHDATA
signature data and SIGHASH_ALL
PUSHDATA
public key data
The scriptPubKey is:
OP_DUP
OP_HASH160
PUSHDATA
Bitcoin address (public key hash)
OP_EQUALVERIFY
OP_CHECKSIG

When this code executes, PUSHDATA first pushes the signature to the stack. The next PUSHDATA pushes the public key to the stack. Next, OP_DUP duplicates the public key on the stack. OP_HASH160 computes the 160-bit hash of the public key. PUSHDATA pushes the required Bitcoin address. Then OP_EQUALVERIFY verifies the top two stack values are equal - that the public key hash from the new transaction matches the address in the old address. This proves that the public key is valid. Next, OP_CHECKSIG checks that the signature of the transaction matches the public key and signature on the stack. This proves that the signature is valid.

Signing the transaction

I found signing the transaction to be the hardest part of using Bitcoin manually, with a process that is surprisingly difficult and error-prone. The basic idea is to use the ECDSA elliptic curve algorithm and the private key to generate a digital signature of the transaction, but the details are tricky. The signing process has been described through a 19-step process (more info). Click the thumbnail below for a detailed diagram of the process.

The biggest complication is the signature appears in the middle of the transaction, which raises the question of how to sign the transaction before you have the signature. To avoid this problem, the scriptPubKey script is copied from the source transaction into the spending transaction (i.e. the transaction that is being signed) before computing the signature. Then the signature is turned into code in the Script language, creating the scriptSig script that is embedded in the transaction. It appears that using the previous transaction's scriptPubKey during signing is for historical reasons rather than any logical reason.[17] For transactions with multiple inputs, signing is even more complicated since each input requires a separate signature, but I won't go into the details.

One step that tripped me up is the hash type. Before signing, the transaction has a hash type constant temporarily appended. For a regular transaction, this is SIGHASH_ALL (0x00000001). After signing, this hash type is removed from the end of the transaction and appended to the scriptSig.

Another annoying thing about the Bitcoin protocol is that the signature and public key are both 512-bit elliptic curve values, but they are represented in totally different ways: the signature is encoded with DER encoding but the public key is represented as plain bytes. In addition, both values have an extra byte, but positioned inconsistently: SIGHASH_ALL is put after the signature, and type 04 is put before the public key.

Debugging the signature was made more difficult because the ECDSA algorithm uses a random number.[18] Thus, the signature is different every time you compute it, so it can't be compared with a known-good signature.

Update (Feb 2014): An important side-effect of the signature changing every time is that if you re-sign a transaction, the transaction's hash will change. This is known as Transaction Malleability. There are also ways that third parties can modify transactions in trivial ways that change the hash but not the meaning of the transaction. Although it has been known for years, malleability has recently caused big problems (Feb 2014) with MtGox (press release).

With these complications it took me a long time to get the signature to work. Eventually, though, I got all the bugs out of my signing code and succesfully signed a transaction. Here's the code snippet I used.

The final scriptSig contains the signature along with the public key for the source address (1MMMMSUb1piy2ufrSguNUdFmAcvqrQF8M5). This proves I am allowed to spend these bitcoins, making the transaction valid.

PUSHDATA 4747
signature
(DER)
sequence30
length44
integer02
length20
X2c b2 65 bf 10 70 7b f4 93 46 c3 51 5d d3 d1 6f c4 54 61 8c 58 ec 0a 0f f4 48 a6 76 c5 4f f7 13
integer02
length20
Y 6c 66 24 d7 62 a1 fc ef 46 18 28 4e ad 8f 08 67 8a c0 5b 13 c8 42 35 f1 65 4e 6a d1 68 23 3e 82
SIGHASH_ALL01
PUSHDATA 4141
public key type04
X14 e3 01 b2 32 8f 17 44 2c 0b 83 10 d7 87 bf 3d 8a 40 4c fb d0 70 4f 13 5b 6a d4 b2 d3 ee 75 13
Y 10 f9 81 92 6e 53 a6 e8 c3 9b d7 d3 fe fd 57 6c 54 3c ce 49 3c ba c0 63 88 f2 65 1d 1a ac bf cd

The final scriptPubKey contains the script that must succeed to spend the bitcoins. Note that this script is executed at some arbitrary time in the future when the bitcoins are spent. It contains the destination address (1KKKK6N21XKo48zWKuQKXdvSsCf95ibHFa) expressed in hex, not Base58Check. The effect is that only the owner of the private key for this address can spend the bitcoins, so that address is in effect the owner.

OP_DUP76
OP_HASH160a9
PUSHDATA 1414
public key hashc8 e9 09 96 c7 c6 08 0e e0 62 84 60 0c 68 4e d9 04 d1 4c 5c
OP_EQUALVERIFY88
OP_CHECKSIGac

The final transaction

Once all the necessary methods are in place, the final transaction can be assembled. The final transaction is shown below. This combines the scriptSig and scriptPubKey above with the unsigned transaction described earlier.

version01 00 00 00
input count01
inputprevious output hash
(reversed)
48 4d 40 d4 5b 9e a0 d6 52 fc a8 25 8a b7 ca a4 25 41 eb 52 97 58 57 f9 6f b5 0c d7 32 c8 b4 81
previous output index00 00 00 00
script length8a
scriptSig47 30 44 02 20 2c b2 65 bf 10 70 7b f4 93 46 c3 51 5d d3 d1 6f c4 54 61 8c 58 ec 0a 0f f4 48 a6 76 c5 4f f7 13 02 20 6c 66 24 d7 62 a1 fc ef 46 18 28 4e ad 8f 08 67 8a c0 5b 13 c8 42 35 f1 65 4e 6a d1 68 23 3e 82 01 41 04 14 e3 01 b2 32 8f 17 44 2c 0b 83 10 d7 87 bf 3d 8a 40 4c fb d0 70 4f 13 5b 6a d4 b2 d3 ee 75 13 10 f9 81 92 6e 53 a6 e8 c3 9b d7 d3 fe fd 57 6c 54 3c ce 49 3c ba c0 63 88 f2 65 1d 1a ac bf cd
sequenceff ff ff ff
output count01
outputvalue62 64 01 00 00 00 00 00
script length19
scriptPubKey76 a9 14 c8 e9 09 96 c7 c6 08 0e e0 62 84 60 0c 68 4e d9 04 d1 4c 5c 88 ac
block lock time00 00 00 00

A tangent: understanding elliptic curves

Bitcoin uses elliptic curves as part of the signing algorithm. I had heard about elliptic curves before in the context of solving Fermat's Last Theorem, so I was curious about what they are. The mathematics of elliptic curves is interesting, so I'll take a detour and give a quick overview.

The name elliptic curve is confusing: elliptic curves are not ellipses, do not look anything like ellipses, and they have very little to do with ellipses. An elliptic curve is a curve satisfying the fairly simple equation y^2 = x^3 + ax + b. Bitcoin uses a specific elliptic curve called secp256k1 with the simple equation y^2=x^3+7. [25]

Elliptic curve formula used by Bitcoin.

Elliptic curve formula used by Bitcoin.

An important property of elliptic curves is that you can define addition of points on the curve with a simple rule: if you draw a straight line through the curve and it hits three points A, B, and C, then addition is defined by A+B+C=0. Due to the special nature of elliptic curves, addition defined in this way works "normally" and forms a group. With addition defined, you can define integer multiplication: e.g. 4A = A+A+A+A.

What makes elliptic curves useful cryptographically is that it's fast to do integer multiplication, but division basically requires brute force. For example, you can compute a product such as 12345678*A = Q really quickly (by computing powers of 2), but if you only know A and Q solving n*A = Q is hard. In elliptic curve cryptography, the secret number 12345678 would be the private key and the point Q on the curve would be the public key.

In cryptography, instead of using real-valued points on the curve, the coordinates are integers modulo a prime.[19] One of the surprising properties of elliptic curves is the math works pretty much the same whether you use real numbers or modulo arithmetic. Because of this, Bitcoin's elliptic curve doesn't look like the picture above, but is a random-looking mess of 256-bit points (imagine a big gray square of points).

The Elliptic Curve Digital Signature Algorithm (ECDSA) takes a message hash, and then does some straightforward elliptic curve arithmetic using the message, the private key, and a random number[18] to generate a new point on the curve that gives a signature. Anyone who has the public key, the message, and the signature can do some simple elliptic curve arithmetic to verify that the signature is valid. Thus, only the person with the private key can sign a message, but anyone with the public key can verify the message.

For more on elliptic curves, see the references[20].

Sending my transaction into the peer-to-peer network

Leaving elliptic curves behind, at this point I've created a transaction and signed it. The next step is to send it into the peer-to-peer network, where it will be picked up by miners and incorporated into a block.

How to find peers

The first step in using the peer-to-peer network is finding a peer. The list of peers changes every few seconds, whenever someone runs a client. Once a node is connected to a peer node, they share new peers by exchanging addr messages whenever a new peer is discovered. Thus, new peers rapidly spread through the system.

There's a chicken-and-egg problem, though, of how to find the first peer. Bitcoin clients solve this problem with several methods. Several reliable peers are registered in DNS under the name bitseed.xf2.org. By doing a nslookup, a client gets the IP addresses of these peers, and hopefully one of them will work. If that doesn't work, a seed list of peers is hardcoded into the client. [26]

nslookup can be used to find Bitcoin peers.

nslookup can be used to find Bitcoin peers.

Peers enter and leave the network when ordinary users start and stop Bitcoin clients, so there is a lot of turnover in clients. The clients I use are unlikely to be operational right now, so you'll need to find new peers if you want to do experiments. You may need to try a bunch to find one that works.

Talking to peers

Once I had the address of a working peer, the next step was to send my transaction into the peer-to-peer network.[8] Using the peer-to-peer protocol is pretty straightforward. I opened a TCP connection to an arbitrary peer on port 8333, started sending messages, and received messages in turn. The Bitcoin peer-to-peer protocol is pretty forgiving; peers would keep communicating even if I totally messed up requests.

Important note: as a few people pointed out, if you want to experiment you should use the Bitcoin Testnet, which lets you experiment with "fake" bitcoins, since it's easy to lose your valuable bitcoins if you mess up on the real network. (For example, if you forget the change address in a transaction, excess bitcoins will go to the miners as a fee.) But I figured I would use the real Bitcoin network and risk my $1.00 worth of bitcoins.

The protocol consists of about 24 different message types. Each message is a fairly straightforward binary blob containing an ASCII command name and a binary payload appropriate to the command. The protocol is well-documented on the Bitcoin wiki.

The first step when connecting to a peer is to establish the connection by exchanging version messages. First I send a version message with my protocol version number[21], address, and a few other things. The peer sends its version message back. After this, nodes are supposed to acknowledge the version message with a verack message. (As I mentioned, the protocol is forgiving - everything works fine even if I skip the verack.)

Generating the version message isn't totally trivial since it has a bunch of fields, but it can be created with a few lines of Python. makeMessage below builds an arbitrary peer-to-peer message from the magic number, command name, and payload. getVersionMessage creates the payload for a version message by packing together the various fields.

Sending a transaction: tx

I sent the transaction into the peer-to-peer network with the stripped-down Python script below. The script sends a version message, receives (and ignores) the peer's version and verack messages, and then sends the transaction as a tx message. The hex string is the transaction that I created earlier.

The following screenshot shows how sending my transaction appears in the Wireshark network analysis program[22]. I wrote Python scripts to process Bitcoin network traffic, but to keep things simple I'll just use Wireshark here. The "tx" message type is visible in the ASCII dump, followed on the next line by the start of my transaction (01 00 ...).

A transaction uploaded to Bitcoin, as seen in Wireshark.

A transaction uploaded to Bitcoin, as seen in Wireshark.

To monitor the progress of my transaction, I had a socket opened to another random peer. Five seconds after sending my transaction, the other peer sent me a tx message with the hash of the transaction I just sent. Thus, it took just a few seconds for my transaction to get passed around the peer-to-peer network, or at least part of it.

Victory: my transaction is mined

After sending my transaction into the peer-to-peer network, I needed to wait for it to be mined before I could claim victory. Ten minutes later my script received an inv message with a new block (see Wireshark trace below). Checking this block showed that it contained my transaction, proving my transaction worked. I could also verify the success of this transaction by looking in my Bitcoin wallet and by checking online. Thus, after a lot of effort, I had successfully created a transaction manually and had it accepted by the system. (Needless to say, my first few transaction attempts weren't successful - my faulty transactions vanished into the network, never to be seen again.[8])

A new block in Bitcoin, as seen in Wireshark.

A new block in Bitcoin, as seen in Wireshark.

My transaction was mined by the large GHash.IO mining pool, into block #279068 with hash 0000000000000001a27b1d6eb8c405410398ece796e742da3b3e35363c2219ee. (The hash is reversed in inv message above: ee19...) Note that the hash starts with a large number of zeros - finding such a literally one in a quintillion value is what makes mining so difficult. This particular block contains 462 transactions, of which my transaction is just one.

For mining this block, the miners received the reward of 25 bitcoins, and total fees of 0.104 bitcoins, approximately $19,000 and $80 respectively. I paid a fee of 0.0001 bitcoins, approximately 8 cents or 10% of my transaction. The mining process is very interesting, but I'll leave that for a future article.

Untitled

Bitcoin mining normally uses special-purpose ASIC hardware, designed to compute hashes at high speed. Photo credit: Gastev, CC:by

Conclusion

Using the raw Bitcoin protocol turned out to be harder than I expected, but I learned a lot about bitcoins along the way, and I hope you did too. My code is purely for demonstration - if you actually want to use bitcoins through Python, use a real library[24] rather than my code.

Notes and references

[1] The original Bitcoin client is Bitcoin-qt. In case you're wondering why qt, the client uses the common Qt UI framework. Alternatively you can use wallet software that doesn't participate in the peer-to-peer network, such as Electrum or MultiBit. Or you can use an online wallet such as Blockchain.info.

[2] A couple good articles on Bitcoin are How it works and the very thorough How the Bitcoin protocol actually works.

[3] The original Bitcoin paper is Bitcoin: A Peer-to-Peer Electronic Cash System written by the pseudonymous Satoshi Nakamoto in 2008. The true identity of Satoshi Nakamoto is unknown, although there are many theories.

[4] You may have noticed that sometimes Bitcoin is capitalized and sometimes not. It's not a problem with my shift key - the "official" style is to capitalize Bitcoin when referring to the system, and lower-case bitcoins when referring to the currency units.

[5] In case you're wondering how the popular MtGox Bitcoin exchange got its name, it was originally a trading card exchange called "Magic: The Gathering Online Exchange" and later took the acronym as its name.

[6] For more information on what data is in the blockchain, see the very helpful article Bitcoin, litecoin, dogecoin: How to explore the block chain.

[7] I'm not the only one who finds the Bitcoin transaction format inconvenient. For a rant on how messed up it is, see Criticisms of Bitcoin's raw txn format.

[8] You can also generate transaction and send raw transactions into the Bitcoin network using the bitcoin-qt console. Type sendrawtransaction a1b2c3d4.... This has the advantage of providing information in the debug log if the transaction is rejected. If you just want to experiment with the Bitcoin network, this is much, much easier than my manual approach.

[9] Apparently there's no solid reason to use RIPEMD-160 hashing to create the address and SHA-256 hashing elsewhere, beyond a vague sense that using a different hash algorithm helps security. See discussion. Using one round of SHA-256 is subject to a length extension attack, which explains why double-hashing is used.

[10] The Base58Check algorithm is documented on the Bitcoin wiki. It is similar to base 64 encoding, except it omits the O, 0, I, and l characters to avoid ambiguity in printed text. A 4-byte checksum guards against errors, since using an erroneous bitcoin address will cause the bitcoins to be lost forever.

[11] Some boilerplate has been removed from the code snippets. For the full Python code, see my repository shirriff/bitcoin-code on GitHub. You will also need the ecdsa cryptography library.

[12] You may wonder how I ended up with addresses with nonrandom prefixes such as 1MMMM. The answer is brute force - I ran the address generation script overnight and collected some good addresses. (These addresses made it much easier to recognize my transactions in my testing.) There are scripts and websites that will generate these "vanity" addresses for you.

[13] For a summary of Bitcoin fees, see bitcoinfees.com. This recent Reddit discussion of fees is also interesting.

[14] The original Bitcoin paper has a similar figure showing how transactions are chained together. I find it very confusing though, since it doesn't distinguish between the address and the public key.

[15] For details on the different types of contracts that can be set up with Bitcoin, see Contracts. One interesting type is the 2-of-3 escrow transaction, where two out of three parties must sign the transaction to release the bitcoins. Bitrated is one site that provides these.

[16] Although Bitcoin's Script language is very flexible, the Bitcoin network only permits a few standard transaction types and non-standard transactions are not propagated (details). Some miners will accept non-standard transactions directly, though.

[17] There isn't a security benefit from copying the scriptPubKey into the spending transaction before signing since the hash of the original transaction is included in the spending transaction. For discussion, see Why TxPrev.PkScript is inserted into TxCopy during signature check?

[18] The random number used in the elliptic curve signature algorithm is critical to the security of signing. Sony used a constant instead of a random number in the PlayStation 3, allowing the private key to be determined. In an incident related to Bitcoin, a weakness in the random number generator allowed bitcoins to be stolen from Android clients.

[19] For Bitcoin, the coordinates on the elliptic curve are integers modulo the prime2^256 - 2^32 - 2^9 -2^8 - 2^7 - 2^6 -2^4 -1, which is very nearly 2^256. This is why the keys in Bitcoin are 256-bit keys.

[20] For information on the historical connection between elliptic curves and ellipses (the equation turns up when integrating to compute the arc length of an ellipse) see the interesting article Why Ellipses Are Not Elliptic Curves, Adrian Rice and Ezra Brown, Mathematics Magazine, vol. 85, 2012, pp. 163-176. For more introductory information on elliptic curve cryptography, see ECC tutorial or A (Relatively Easy To Understand) Primer on Elliptic Curve Cryptography. For more on the mathematics of elliptic curves, see An Introduction to the Theory of Elliptic Curves by Joseph H. Silverman. Three Fermat trails to elliptic curves includes a discussion of how Fermat's Last Theorem was solved with elliptic curves.

[21] There doesn't seem to be documentation on the different Bitcoin protocol versions other than the code. I'm using version 60002 somewhat arbitrarily.

[22] The Wireshark network analysis software can dump out most types of Bitcoin packets, but only if you download a recent "beta release - I'm using version 1.11.2.

[24] Several Bitcoin libraries in Python are bitcoin-python, pycoin, and python-bitcoinlib.

[25] The elliptic curve plot was generated from the Sage mathematics package:

var("x y")
implicit_plot(y^2-x^3-7, (x,-10, 10), (y,-10, 10), figsize=3, title="y^2=x^3+7")

[26] The hardcoded peer list in the Bitcoin client is in chainparams.cpp in the array pnseed. For more information on finding Bitcoin peers, see How Bitcoin clients find each other or Satoshi client node discovery.

How Hacker News ranking really works: scoring, controversy, and penalties

The basic formula for Hacker News ranking has been known for years, but questions remained. Does the published code give the real algorithm? Are rankings purely based on votes or do invisible factors come into play? Do stories about the NSA get pushed down in the rankings? Why did that popular story suddenly disappear from the front page after you commented on it?

By carefully analyzing the top 60 HN stories for several days, I can answer those questions and more. The published formula is mostly accurate. There is much more tweaking of rankings than you'd expect, with 20% of front-page stories getting penalized in various ways. Anything with "NSA" in the title is penalized and drops off quickly. A "controversial" story gets severely penalized after hitting 40 comments. This article describes scoring and penalties in detail. [Edit: HN no longer penalizes NSA articles (details).]

How ranking works

Articles are scored based on their upvote score, the time since the article was submitted, and various penalties using the following formula: score=\frac{ \left( votes-1 \right) ^{.8}}{ \left( age _{hours} + 2 \right) ^ {1.8}} * penalties

Because the time has a larger exponent than the votes, an article's score will eventually drop to zero, so nothing stays on the front page too long. This exponent is known as gravity.

You might expect that every time you visit Hacker News, the stories are scored by the above formula and sorted to determine their rankings. But for efficiency, stories are individually reranked only occasionally. When a story is upvoted, it is reranked and moved up or down the list to its appropriate spot, leaving the other stories unchanged. Thus, the amount of reranking is significantly reduced. There is, however, the possibility that a story stops getting votes and ends up stuck in a high position. To avoid this, every 30 seconds one of the top 50 stories is randomly selected and reranked. The consequence is that a story may be "wrongly" ranked for many minutes if it isn't getting votes. In addition, pages can be cached for 90 seconds.

Raw scores and the #1 spot on a typical day

The following image shows the raw scores (excluding penalties) for the top 60 HN articles throughout the day of November 11. Each line corresponds to an article, colored according to its position on the page. The red line shows the top article on HN. Note that because of penalties, the article with the top raw score often isn't the top article.

Hacker News raw article scores throughout a day. Red line indicates the #1 article. Due to penalties, the #1 article does not always have the top score.

This chart shows a few interesting things. The score for an article shoots up rapidly and then slowly drops over many hours. The scoring formula accounts for much of this: an article getting a constant rate of votes will peak quickly and then gradually descend. But the observed peak is even faster - this is because articles tend to get a lot of votes in the first hour or two, and then the voting rate drops off. Combining these two factors yields the steep curves shown.

There are a few articles each day that score much above the rest, along with a lot of articles in the middle. Some articles score very well but are unlucky and get stuck behind a more popular article. Other articles hit #1 briefly, between the fall of one and the climb of another.

Looking at the difference between the article with the top raw score (top of the graph) and the top-ranked article (red line), you can see when penalties have been applied. The article Getting website registration completely wrong hit #1 early in the morning, but was penalized for controversy and rapidly dropped down the page, letting Linux ate my RAM briefly get the #1 spot before Simpsons in CSS overtook it. A bit later, the controversy penalty was applied to Apple Maps shortly after it reached the #1 spot, causing it to lose its #1 spot and rapidly drop down the rankings. The Snapchat article reached the top of HN but was penalized so heavily at 8:22 am that it dropped off the chart entirely. Why you should never use MongoDB was hugely popular and would have spent much of the day in the #1 spot, except it was rapidly penalized and languished around #7. Severing ties with the NSA started off with a NSA penalty but was so hugely popular it still got the #1 spot. However, it was quickly given an even bigger penalty, forcing it down the page. Finally, near the end of the day $4.1m goes missing was penalized. As it turns out, it would have soon lost the #1 spot to FTL even without the penalty.

The green triangles and text show where "controversy" penalties were applied. The blue triangles and text show where articles were penalized into oblivion, dropping off the top 60. Milder penalties are not shown here.

It's clear that the content of the #1 spot on HN isn't "natural", but results from the constant application of penalties to many articles. It's unclear if these penalties result from HN administrators or from flagged articles.

Submissions that get automatically penalized

Some submissions get automatically penalized based on the title, and others get penalized based on the domain. It appears that any article with NSA in the title gets an automatic penalty of .4. I looked for other words causing automatic penalties, such as awesome, bitcoin, and bubble but they do not seem to get penalized. I observed that many websites appear to automatically get a penalty of .25 to .8: arstechnica.com, businessinsider.com, easypost.com, github.com, imgur.com, medium.com, quora.com, qz.com, reddit.com, rt.com, stackexchange.com, theguardian.com, theregister.com, theverge.com, torrentfreak.com, youtube.com. I'm sure the actual list is longer. (This is separate from "banned" sites, which were listed at one point.

One interesting theory by eterm is that news from popular sources gets submitted in parallel by multiple people resulting in more upvotes than the article "merits". Automatically penalizing popular websites would help counteract this effect.

The impact of penalties

Using the scoring formula, the impact of a penalty can be computed. If an article gets a penalty factor of .4, this is equivalent to each vote only counting as .3 votes. Alternatively, the article will drop in ranking 66% faster than normal. A penalty factor of .1 corresponds to each vote counting as .05 votes, or the article dropping at 3.6 times the normal rate. Thus, a penalty factor of .4 has a significant impact, and .1 is very severe.

Controversy In order to prevent flamewars on Hacker News, articles with "too many" comments will get heavily penalized as "controversial". In the published code, the contro-factor function kicks in for any post with more than 20 comments and more comments than upvotes. Such an article is scaled by (votes/comments)^2. However, the actual formula is different - it is active for any post with more comments than upvotes and at least 40 comments. Based on empirical data, I suspect the exponent is 3, rather than 2 but haven't proven this. The controversy penalty can have a sudden and catastrophic effect on an article's ranking, causing an article to be ranked highly one minute and vanish when it hits 40 comments. If you've wondered why a popular article suddenly vanishes from the front page, controversy is a likely cause. For example, Why the Chromebook pundits are out of touch with reality dropped from #5 to #22 the moment it hit 40 comments, and Show HN: Get your health records from any doctor' was at #17 but vanished from the top 60 entirely on hitting 40 comments.

My methodology

I crawled the /news and /news2 pages every minute (staying under the 2 pages per minute guideline). I parsed the (somewhat ugly) HTML with Beautiful Soup, processed the results with a big pile of Python scripts, and graphed results with the incomprehensible but powerful matplotlib. The basic idea behind the analysis is to generate raw scores using the formula and then look for anomalies. At a point in time (e.g. 11/09 8:46), we can compute the raw scores on the top 10 stories:

2.802 Pyret: A new programming language from the creators of Racket
1.407 The Big Data Brain Drain: Why Science is in Trouble
1.649 The NY Times endorsed a secretive trade agreement that the public can't read
0.785 S.F. programmers build alternative to HealthCare.gov (warning: autoplay video)
0.844 Marelle: logic programming for devops
0.738 Sprite Lamp
0.714 Why Teenagers Are Fleeing Facebook
0.659 NodeKnockout is in Full Tilt. Checkout some demos
0.805 ISO 1
0.483 Shopify accepts Bitcoin.
0.452 Show HN: Understand closures
Note that three of the top 10 articles are ranked lower than expected from their score: The NY Times, Marelle and ISO 1. Since The NY Times is ranked between articles with 1.407 and 0.785, its penalty factor can be computed as between .47 and .85. Likewise, the other penalties must be .87 to .93, and .60 to .82. I observed that most stories are ranked according to their score, and the exceptions are consistently ranked much lower, indicating a penalty. This indicates that the scoring formula in use matches the published code. If the formula were different, for instance the gravity exponent were larger, I'd expect to see stories drift out of their "expected" ranking as their votes or age increased, but I never saw this.

This technique shows the existence of a penalty and gives a range for the penalty, but determining the exact penalty is difficult. You can look at the range over time and hope that it converges to a single value. However, several sources of error mess this up. First, the neighboring articles may also have penalties applied, or be scored differently (e.g. job postings). Second, because articles are not constantly reranked, an article may be out of place temporarily. Third, the penalty on an article may change over time. Fourth, the reported vote count may differ from the actual vote count because "bad" votes get suppressed. The result is that I've been able to determine approximate penalties, but there is a fair bit of numerical instability.

Penalties over a day

The following graph shows the calculated penalties over the course of a day. Each line shows a particular article. It should start off at 1 (no penalty), and then drop to a penalty level when a penalty is applied. The line ends when the article drops off the top 60, which can be fairly soon after the penalty is applied. There seem to be penalties of 0.2 and 0.4, as well as a lot in the 0.8-0.9 range. It looks like a lot of penalties are applied at 9am (when moderators arrive?), with more throughout the day. I'm experimenting with different algorithms to improve the graph since it is pretty noisy.
On average, about 20% of the articles on the front page have been penalized, while 38% of the articles on the second page have been penalized. (The front page rate is lower since penalized articles are less likely to be on the front page, kind of by definition.) There is a lot more penalization going on than you might expect.

Here's a list of the articles on the front page on 11/11 that were penalized. (This excludes articles that would have been there if they weren't penalized.) This list is much longer than I expected; scroll for the full list.

Why the Climate Corporation Sold Itself to Monsanto, Facebook Publications, Bill Gates: What I Learned in the Fight Against Polio, McCain says NSA chief Keith Alexander 'should resign or be fired', You are not a software engineer, What is a y-combinator?, Typhoon Haiyan kills 10,000 in Philippines, To Persuade People, Tell Them a Story, Tetris and The Power Of CSS, Microsoft Research Publications, Moscow subway sells free tickets for 30 sit-ups, The secret world of cargo ships, These weeks in Rust, Empty-Stomach Intelligence, Getting website registration completely wrong, The Six Most Common Species Of Code, Amazon to Begin Sunday Deliveries, With Post Office's Help, Linux ate my RAM, Simpsons in CSS, Apple maps: how Google lost when everyone thought it had won, Docker and Go: why did we decide to write Docker in Go?, Amazon Code Ninjas, Last Doolittle Raiders make final toast, Linux Voice - A new Linux magazine that gives back, Want to download anime? Just made a program for that, Commit 15 minutes to explain to a stranger why you love your job., Why You Should Never Use MongoDB, Show HN: SketchDeck - build slides faster, Zero to Peanut Butter Docker Time in 78 Seconds, NSA's Surveillance Powers Extend Far Beyond Counterterrorism, How Sentry's Open Source Service Was Born, Real World OCaml, Show HN: Get your health records from any doctor, Why the Chromebook pundits are out of touch with reality, Towards a More Modular Future for JavaScript Libraries, Why is virt-builder written in OCaml?, IOS: End of an Era, The craziest things you can plug into your iPhone's audio jack, RFC: Replace Java with Go in default languages, Show HN: Find your health plan on Health Sherpa, Web Latency Benchmark: A new kind of browser benchmark, Why are Amazon, Facebook and Yahoo copying Microsoft's stack ranking system?, Severing Ties with the NSA, Doctor performs surgery using Google Glass, Duplicity + S3: Easy, cheap, encrypted, automated full-disk backups, Bitcoin's UK future looks bleak, Amazon Redshift's New Features, You're only getting the nice feedback, Software is Easy, Hardware is of Medium Difficulty, Facebook Warns Users After Adobe Breach, International Space Station Infected With USB Stick Malware, Tidbit: Client-Side Bitcoin Mining, Go: "I have already used the name for *MY* programming language", Multi-Modal Drone: Fly, Swim & Drive, The Daily Go Programming Newspaper, "We have no food, we need water and other things to survive.", Introducing the Humble Store, The Six Most Common Species Of Code, $4.1m goes missing as Chinese bitcoin trading platform GBL vanishes, Could Bitcoin Be More Disruptive than the Internet?, Apple Store is updating.

The code for the scoring formula

The Arc source code for a version of the HN server is available, as well as an updated scoring formula:
  (= gravity* 1.8 timebase* 120 front-threshold* 1
       nourl-factor* .4 lightweight-factor* .17 gag-factor* .1)

    (def frontpage-rank (s (o scorefn realscore) (o gravity gravity*))
      (* (/ (let base (- (scorefn s) 1)
              (if (> base 0) (expt base .8) base))
            (expt (/ (+ (item-age s) timebase*) 60) gravity))
         (if (no (in s!type 'story 'poll))  .8
             (blank s!url)                  nourl-factor*
             (mem 'bury s!keys)             .001
                                            (* (contro-factor s)
                                               (if (mem 'gag s!keys)
                                                    gag-factor*
                                                   (lightweight s)
                                                    lightweight-factor*
                                                   1)))))
In case you don't read Arc code, the above snippet defines several constants: gravity* = 1.8, timebase* = 120 (minutes), etc. It then defines a method frontpage-rank that ranks a story s based on its upvotes (realscore) and age in minutes (item-age). The penalty factor is defined by an if with several cases. If the article is not a 'story' or 'poll', the penalty factor is .8. Otherwise, if the URL field is blank (Ask HN, etc.) the factor is nourl-factor*. If the story has been flagged as 'bury', the scale factor is 0.001 and the article is ranked into oblivion. Finally, the default case combines the controversy factor and the gag/lightweight factor. The controversy factor contro-factor is intended to suppress articles that are leading to flamewars, and is discussed more later.

The next factor hits an article flagged as a gag (joke) with a heavy value of .1, and a "lightweight" article with a factor of .17. The actual penalty system appears to be much more complex than what appears in the published code.

Conclusion

An article's position on the Hacker News home page isn't the meritocracy based on upvotes that you might expect. By carefully examining the articles that appear on the Hacker News page, we can learn a great deal about the scoring formula in use. While upvotes are the obvious factor controlling rankings, there is also a complex "penalty" system causing articles to be ranked lower or disappear entirely. This isn't just preventing spam, but affects many very popular articles. And if an article has more comments than votes, don't add your comment to it or you may kill it off entirely! See discussion on Hacker News.


Update (11/18): article on penalties is penalized

Ironically, this article was penalized on Hacker News. Minutes after reaching the front page, a heavy 0.2 penalty was applied to the article, forcing it off the front page. The black line in the graph below shows the position of this article on Hacker News. You can see the sharp drop when the penalty was applied. The gray line shows where the article would have been ranked without the penalty. Without the penalty, the article would have been in the #5 spot, but with the penalty it never made it back onto the front page (positions 1-30). The lower green line shows the raw score of this article. (11/26: I'm told that the penalty was because the "voting ring detection" triggered erroneously.)
This article was penalized shortly after reaching the front page of Hacker News

The Z-80's 16-bit increment/decrement circuit reverse engineered

The 8-bit Z-80 processor was very popular in the late 1970s and early 1980s, powering many personal computers such as the Osborne 1, TRS-80, and Sinclair ZX Spectrum. It has a 16-bit incrementer/decrementer that efficiently updates the program counter and stack pointer, as well as supporting several 16-bit instructions and memory refresh. By reverse engineering detailed die photographs of the Z-80, we can see exactly how this increment/decrement circuit works and discover the interesting optimizations it uses for efficiency.

The Z-80 microprocessor die, showing the main components of the chip.

The Z-80 microprocessor die, showing the main components of the chip.

The increment/decrement circuit in the lower left corner of the chip photograph above. This circuit takes up a significant amount of space on the chip, illustrating its complexity. It is located close to the register file, allowing it to access the registers directly.

The fundamental use for an incrementer is to step the program counter from instruction to instruction as the program executes. Since this happens at least once for every instruction, a fast incrementer is critical to the performance of the chip. For this reason, the incrementer/decrementer is positioned close to the address pins (along the left and bottom of the photograph above). A second key use is to decrement the stack pointer as data is pushed to the stack, and increment the stack pointer as data is popped from the stack. (This may seem backwards, but the stack grows downwards so it is decremented as data is pushed to the stack.)

The incrementer/decrementer in the Z-80 is also used for a variety of other instructions. For example, the INC and DEC instructions allow 16-bit register pairs to be incremented and decremented. The Z-80 includes powerful block copy and compare instructions (LDIR, LDDR, CPIR, CPDR) that can process up to 64K bytes with a single instruction. These instructions use the 16-bit BC register pair as a loop counter, and the decrementer updates this register pair to count the iterations.

One of the innovative features of the Z-80 is that it includes a DRAM refresh feature. Because Dynamic RAM (DRAM) stores data in capacitors instead of flip flops, the data will drain away if not accessed and refreshed every few milliseconds. Early microcomputer memory boards required special refresh hardware to periodically step through the address space and refresh memory. The incrementer is used to update the address in the refresh register R on each instruction. (Current systems still require memory refresh, but it is handled by the DDR memory modules and memory controller).

Architecture

The architecture diagram below provides a simplified view of how the incrementer/decrementer works with the rest of the Z-80. The incrementer is closely associated with the 16-bit address bus. The data bus, on the other hand, is only 8 bits wide. Many of the registers are 8 bits, but can be paired together as 16-bit registers (BC, DE, HL).

A 16-bit latch feeds into the incrementer. This is needed since if a value were read from the PC, incremented, and written back to the PC at the same time a loop would occur. By latching the value, the read and write are done in separate cycles, avoiding instability. On the chip, the latch is between the incrementer and the register file.

The program counter and refresh register are separated from the rest of the registers and coupled closely to the incrementer. This allows the incrementer to be used in parallel with the rest of the Z-80. In particular, for each instruction fetch, the program counter (PC) is written to the address bus and incremented. Then the refresh address is written to the address bus for the refresh cycle, and the R register is incremented. (Note that the interrupt vector register I is in the same register pair as the R register. This explains why the I value is also written to the address bus during refresh.)

This diagram shows how the incrementer/decrementer is used in the Z-80 microprocessor.

This diagram shows how the incrementer/decrementer is used in the Z-80 microprocessor.

One of the interesting features of the Z-80 is a limited form of pipelining: fetch/execute overlap. Usually, the Z-80 fetches an instruction before the previous instruction has finished executing. The architecture above shows how this is possible. Because the PC and R registers are separated from the other registers, the other registers and ALU can continue to operate during the fetch and refresh steps.

The other registers are not entirely separated from the incrementer/decrementer, though. The stack pointer and other registers can communicate via the bus with the incrementer/decrementer when needed. Pass transistors allow this bus connection to be made as needed.

How a simple incrementer/decrementer works

To understand the circuit, it helps to start with a simple incrementer. If you've studied digital circuits, you've probably seen how two bits can be added with a half-adder, and several half-adders can be chained together to implement a simple multi-bit increment circuit.

The circuit below shows a half-adder, which can increment a single bit. The sum of two bits is computed by XOR, and if both bits are 1, there is a carry.

A simple half-adder that can be used to build an incrementer.

A simple half-adder that can be used to build an incrementer.

Chaining together 16 of these half-adder circuits creates a 16-bit incrementer. Each carry-out is connected to the carry-in of the next bit. A 1 value is fed into the initial carry-in to start the incrementing.

This circuit can be converted to a decrement circuit by renaming the carry signal as a borrow signal. If a bit is 0 and borrow is 1, then there must be a borrow from the next higher bit. (This is similar to grade-school decimal subtraction: 101000 - 1 = 100999 in decimal, since you keep borrowing until you hit a nonzero digit.) When decrementing, a 0 bit potentially causes a borrow, the opposite of incrementing, where a 1 bit potentially causes a carry.

The incrementer and decrementer can be combined into a single circuit by adding one more gate. When computing the carry/borrow for decrementing, each bit is flipped. This is accomplished by using an XOR gate with the decrement condition as an input. If decrement is 1, the input bit is flipped. To increment, the decrement input is set to 0 and the bit passes through the XOR gate unchanged.

A half-adder / subtractor that can be used to build an incrementer/decrementer.

A half-adder / subtractor that can be used to build an incrementer/decrementer.

Repeating the above circuit 16 times creates a 16-bit incrementer/decrementer.

Ripple carry: the problem and solutions

While the circuits above are simple, they have a big problem: they are slow. These circuits use what is called "ripple carry", since the carry value ripples through the circuit bit by bit. The consequence is each bit can't be computed until the carry/borrow is available from the previous bit. This propagation delay limits the clock speed of the system, since the final result isn't available until the carry has made it way through the entire circuit. For a 16-bit counter, this delay is significant.

Carry skip

The Z-80 uses two techniques to avoid ripple carry and speed up the incrementer. First, it uses a technique called carry-skip to compute the result and carry for two bits at a time, reducing the propagation delay.

The circuit diagram below shows how two bits at a time can be computed. Both carry values are computed in parallel, rather than the second carry depending on the first. If both input bits are 1 and there is a carry in, then there is a carry from the left bit. By computing this directly, the propagation delay is reduced.

A circuit to increment or decrement two bits at once.

A circuit to increment or decrement two bits at once.

Due to the MOS gates used in the Z-80, NOR and XNOR gates are more practical than AND and XOR gates, so instead of the carry skip circuit above, the similar circuit below is used in the Z-80. The output bits are inverted, but this is not a problem because many of the Z-80's internal buses are inverted. (The Z-80 uses an interesting pass-transistor XNOR gate, described here. The circuit below performs increment/decrement on two bits, and is repeated six times in the Z-80. To simplify the final schematic, the circuit in the dotted box will simply be shown as a box labeled "2-bit inc/dec".

The circuit used in the Z-80 to increment or decrement two bits.

The circuit used in the Z-80 to increment or decrement two bits.

Carry-lookahead

The second technique used by the Z-80 to avoid the ripple carry delay is carry lookahead, which computes some of the carry values directly from the inputs without waiting on the previous carries. If a sequence of bits is all 1's, there will be a carry from the sequence when it is incremented. Conversely, if there is a 0 anywhere in the sequence, any intermediate carry will be "extinguished". (Similarly, all 0's causes a borrow when decrementing.) By feeding the bits into an AND gate, a sequence of all 1's can be detected, and the carry immediately generated. (The Z-80 uses the inverted bits and a NOR gate, but the idea is the same.)

In the Z-80 three lookahead carries are computed. The carry from the lowest 7 bits is computed directly. If these bits are all 1, and there is a carry-in, then there will be a carry out. The second carry lookahead checks bits 7 through 11 in parallel. The third carry lookahead checks bits 12 through 14 in parallel. Thus, the last bit of the result (bit 15) depends on three carry lookahead steps, rather than 15 ripple steps. This reduces the time for the incrementer to complete.

For more information on carry optimization, see this or this discussion of adders.

The Z-80's increment/decrement circuit

The schematic below shows the actual circuit used in the Z-80 to implement the 16-bit incrementer/decrementer, as determined by reverse engineering the silicon. It uses six of the 2-bit inc/dec blocks described earlier in combination with the three carry-lookahead gates.

In the top half of the schematic, the seven low-order bits are incremented/decremented using the circuit block discussed above. In parallel, the carry/borrow from these bits is computed by the large NOR gate on the left.

Bits 7 through 11 are computed using the carry lookahead value, allowing them to be computed without waiting on the low-order bits. In parallel, the carry/borrow out of these bits is computed by the large NOR gate in the middle, and used to compute bits 12 through 14. The last carry lookahead value is computed at the left and used to compute bit 15. Note that the number of carry blocks decreases as the number of carry lookahead gates increases. For example, output 6 depends on three inc/dec blocks and no carry lookahead gates, while output 14 depends on one inc/dec block and two carry lookahead gates. If the inc/dec blocks and carry lookahead gates require approximately the same time, then the output bits will be ready at approximately the same time.

Schematic of the incrementer/decrementer circuit in the Z-80 microprocessor.

Schematic of the incrementer/decrementer circuit in the Z-80 microprocessor.

The image below shows what the incrementer/decrementer looks like physically, zooming in on the die photograph at the top of the article. The layout on the chip is slightly different from the schematic above. On the chip, the bits are arranged vertically with the low-order bit on top and the high-order bit on the bottom.

The image is a composite: the upper half is from the Z-80 die photograph, while the lower half shows the chip layers as tediously redrawn by the Visual 6502 team for analysis. You can see 8 horizontal "slices" of circuitry from top to bottom, since the bits are processed two at a time. The vertical metal wires are most visible (white in the photograph, blue in the layer drawing). These wires provide power, ground, control signals, and collect the lookahead carry from multiple bits. The polysilicon wires are reddish-orange in the layer diagram, while the diffused silicon is green. Transistors result where the two cross. If you look closely, you can see diagonal orange polysilicon wires about halfway across; these connect the carry-out from one bit to carry-in of the next.

The increment/decrement circuit in the Z-80 microprocessor. Top is the die photograph. Bottom is the layer drawing.

The increment/decrement circuit in the Z-80 microprocessor. Top is the die photograph. Bottom is the layer drawing.

Incrementing the refresh register

The refresh register R and interrupt vector I form a 16-bit pair. The refresh register gets incremented on every memory refresh cycle, but why doesn't the I register get incremented too? This would be a big problem since the value in the I register would get corrupted. The answer is the refresh input into the first carry lookahead gate in the schematic. During a refresh operation, a 1 value is fed into the gate here. This forces the carry to 0, stopping the increment at bit 6, leaving the I register unchanged (along with the top bit of the R register).

You might wonder why only 7 bits of the 8-bit refresh register get incremented. The explanation is that dynamic RAM chips store values in a square matrix. For refresh, only the row address needs to be updated, and all memory values in that row will be refreshed at once. When the Z-80 was introduced, 16K memory chips were popular. Since they held 2^14 bits, they had 7 row address bits and 7 column address bits. Thus, a 7 bit refresh value matched their need. Unfortunately, this rapidly became obsolete with the introduction of 64K memory chips that required 8 refresh bits. [Edit: it's a bit more complicated and depends on the specific chips. See the comments.] Some later chips based on the Z-80, such as the NSC800 had an 8-bit refresh to support these chips.

The non-increment feature

One unexpected feature of the Z-80's incrementer is that it can pass the value through unchanged. If the carry-in to the incrementer/decrementer is set to 0, no action will take place. This seems pointless, but it actually useful since it allows a 16-bit value to be latched and then read back unchanged. In effect, this provides a 16-bit temporary register. The Z-80 uses this action for EX (SP), HL, LD SP, HL, and the associated IX and IY versions. For the LD SP, HL, first HL is loaded into the incrementer latch. Then the unincremented value is stored in the SP register.

The EX (SP), HL is more complex, but uses the latch in a similar way. First the values at (SP+1) and (SP) are read into the WZ temporary register. Next the HL value is written to memory. Finally, WZ is loaded into the incrementer latch and then stored in HL.

You might wonder why values aren't copied between two registers directly. This is due to the structure of the register cells: they do not have separate load and store lines. Instead when a register is connected to the internal register bus, it will be overwritten if another value is on the bus, and otherwise it can be read. Even a simple register-to-register copy such as LD A,B cannot happen directly, but copy the data via the ALU. Since the Z-80's ALU is 4 bits wide, copying a 16-bit value would take at least 4 cycles and be slow. Thus, copying a 16-bit value via the incrementer latch is faster than using the WZ temporary registers.

One timing consequence of using the incrementer latch for 16-bit register-to-register transfers is that it cannot be overlapped with the instruction fetch. Many Z-80 instructions are pipelined and don't finish until several cycles into the next instruction, since register and ALU operations can take place while the Z-80 is fetching the next instruction from memory. However, the PC uses the incrementer during instruction fetch to advance to the next instruction. Thus, any transfer using the incrementer latch must finish before the next instruction starts.

The 0x0001 detector

Another unexpected feature of the incrementer/decrementer is it has a 16-input gate to test if the input is 0x0001 (not shown on the schematic). Why check for 1 and not zero? This circuit is used for the block transfer and search instructions mentioned earlier (LDIR, LDDR, CPIR, CPDR). These operations repeat a transfer or compare multiple times, decrementing the BC register until it reaches zero. But instead of checking for 0 after the decrement, the Z-80 checks if BC register is 1 before the decrement; this works out the same, but gives the Z-80 more time to detect the end of the loop and wrap up instruction execution.

No flags

Unlike the ALU, the incrementer/decrementer doesn't compute parity, negative, carry, or zero values. This is why the 16-bit increment/decrement instructions don't update the status flags.

Comparison with the 6502 and 8085

The 6502 has a 16-bit incrementer, but it is part of the program counter circuit. The 6502 only provides an incrementer, not a decrementer, as the PC doesn't need to be decremented. The other registers are 8 bits, so they don't need a 16-bit incrementer, but use the ALU to be incremented or decremented. (See the 6502 architecture diagram.) The 6502's incrementer uses a couple tricks for efficiency. It uses carry lookahead: the carry from the lowest 8 bits is computed in parallel, as is the carry from the next 4 bits. Alternating bits use a slightly different circuit to avoid inverters in the carry path, slightly reducing the propagation delay.

I've examined the 8085's register file and incrementer in detail. The incrementer/decrementer is implemented by a chain of half-adders with ripple carry. The 8085 has controls to select increment or decrement, similar to the Z-80. The 8085 also includes a feature to increment by two, which speeds up conditional jumps. As in the 6502, an optimization in the 8085 is that alternating bits are implemented with different circuits and the carry out of even bits is inverted. This avoids the inverters that would otherwise be needed to flip the carry back to its regular state. The 8085 uses the carry out from the incrementer to compute the undocumented K flag value.

Conclusion

Looking at the actual circuit for the incrementer/decrementer in the Z-80 shows the performance optimizations in a real chip, compared to a simple incrementer. The 6502 and 8085 also optimize this circuit, but in different ways. In addition, examining the circuitry sheds light on how some operations are implemented in the Z-80, as well as the way memory refresh was handled.

Credits: This couldn't have been done without the Visual 6502 team especially Pavel Zima, Chris Smith, Ed Spittles, Phil Mainwaring, and Julien Oster.

The Z-80 has a 4-bit ALU. Here's how it works.

The 8-bit Z-80 processor is famed for use in many early personal computers such the Osborne 1, TRS-80, and Sinclair ZX Spectrum, and it is still used in embedded systems and TI graphing calculators. I had always assumed that the ALU (arithmetic-logic unit) in the Z-80 was 8 bits wide, like just about every other 8-bit processor. But while reverse-engineering the Z-80, I was shocked to discover the ALU is only 4 bits wide! The founders of Zilog mentioned the 4-bit ALU in a very interesting discussion at the Computer History Museum, so it's not exactly a secret, but it's not well-known either.

I have been reverse-engineering the Z-80 processor using images from the Visual 6502 team. The image below shows the overall structure of the Z-80 chip and the location of the ALU. The remainder of this article dives into the details of the ALU: its architecture, how it works, and exactly how it is implemented.

I've created the following block diagram to give an overview of the structure of the Z-80's ALU. Unlike Z-80 block diagrams published elsewhere, this block diagram is based on the actual silicon. The ALU consists of 4 single-bit units that are stacked to form a 4-bit ALU. At the left of the diagram, the register bus provides the ALU's connection to the register file and the rest of the CPU.

The operation of the ALU starts by loading two 8-bit operands from registers into internal latches. The ALU does a computation on the low 4 bits of the operands and stores the result internally in latches. Next the ALU processes the high 4 bits of the operands. Finally, the ALU writes the 8 bits of result (the 4 low bits from the latch, and the 4 high bits just computed) back to the registers. Thus, by doing two computation cycles, the ALU is able to process a full 8 bits of data. ("Full 8 bits" may not sound like much if you're reading this on a 64-bit processor, but it was plenty at the time.)

As the block diagram shows, the ALU has two internal 4-bit buses connected to the 8-bit register bus: the low bus provides access to bits 0, 1, 2, and 3 of registers, while the high bus provides access to bits 4, 5, 6, and 7. The ALU uses latches to store the operands until it can use them. The op1 latches hold the first operand, and the op2 latches hold the second operand. Each operand has 4 bits of low latch and 4 bits of high latch, to store 8 bits.

Multiplexers select which data is used for the computation. The op1 latches are connected to a multiplexer that selects either the low or high four bits. The op2 latches are connected to a multiplexer that selects either the low or high four bits, as well as selecting either the value or the inverted value. The inverted value is used for subtraction, negation, and comparison.

The two operands go to the "alu core", which performs the desired operation: addition, logical AND, logical OR, or logical XOR. The ALU first performs one computation on the low bits, storing the 4-bit result into the result low latch. The ALU then performs a second computation on the high bits, writing the latched low result and the freshly-computed high bits back to the bus. The carry from the first computation is used in the second computation if needed.

The Z-80 provides extensive bit-addressed operations, allowing a single bit in a byte to be set, reset, or tested. In a bit-addressed operation, bits 5, 4, and 3 of the instruction select which of the 8 bits to use. On the far right of the ALU block diagram is the bit select circuit that support these operations. In this circuit, simple logic gates select one of eight bits based on the instruction. The 8-bit result is written to the ALU bus, where it is used for the bit-addressed operation. Thus, decoding this part of an instruction happens right at the ALU, rather than in the regular instruction decode logic.

The Z-80's shift circuitry is interesting. The 6502 and 8085 have an additional ALU operation for shift right, and perform shift left by adding the number to itself. The Z-80 in comparison performs a shift while loading a value into the ALU. While the Z-80 reads a value from the register bus, the shift circuit selects which lines from the register bus to use. The circuit loads the value unchanged, shifted left one bit, or shifted right one bit. Values shifted in to bit 0 and 7 are handled separately, since they depend on the specific instruction.

The block diagram also shows a path from the low bus to the high op2 latch, and from the high bus to the low op1 latch. These are for the 4-bit BCD shifts RRD and RLD, which rotate a 4-bit digit in the accumulator with two digits in memory.

Not shown in the block diagram are the simple circuits to compute parity, test for zero, and check if a 4-bit value is less than 10. These values are used to set the condition flags.

The silicon that implements the ALU

The image above zooms in on the ALU region of the Z-80 chip. The four horizontal "slices" are visible. The organization of each slice approximately matches the block diagram. The register bus is visible on the left, running vertically with the shifter inputs sticking out from the ALU like "fingers" to obtain the desired bits. The data bus is visible on the right, also running vertically. The horizontal ALU low and ALU high lines are visible at the top and bottom of each slice. The yellow arrows show the locations of some ALU components in one of the slices, but the individual circuits of the ALU are not distinguishable at this scale. In a separate article, I zoom in to some individual gates in the ALU and show how they work: Reverse-engineering the Z-80: the silicon for two interesting gates explained.

The ALU's core computation circuit

The silicon that implements one bit of ALU processing

The heart of each bit of the ALU is a circuit that computes the sum, AND, OR, or XOR for two one-bit operands. Zooming in shows the silicon that implements this circuit; at this scale the transistors and connections that make up the gates are visible. Power, ground, and the control lines are the vertical metal stripes. The shiny horizontal bands are polysilicon "wires" which form the connections in the circuit as well as the transistors. I know this looks like mysterious gray lines, but by examining it methodically, you can figure out the underlying circuit. (For details on how to figure out the logic from this silicon, see my article on the Z-80's gates.) The circuit is shown in the schematic below.

The Z-80 ALU circuit that computes one bit

This circuit takes two operands (op1 and op2), and a carry in. It performs an operation (selected by control lines R, S, and V) and generates an internal carry, a carry-out, and the result.

ALU computation logic in detail

The first step is the "carry computation", which is done by one big multi-level gate. It takes the two operand bits (op1 and op2) and the carry in, and computes the (complemented) internal carry that results from adding op1 plus op2 plus carry-in. There are just two ways this sum can cause a carry: if op1 and op2 are both 1 (bottom AND gate); or if there's a carry-in and at least one of the operands is a 1 (top gates). These two possibilities are combined in the NOR gate to yield the (complemented) internal carry. The internal carry is inverted by the NOR gate at the bottom to yield the carry out, which is the carry in for the next bit. There are a couple control lines that complicate carry generation slightly. If S is 1, the internal carry will be forced to 0. If R is 1, the carry out will be forced to 0 (and thus the carry in for the next bit).

The multi-level result computation gate is interesting as it computes the SUM, XOR, AND or OR. It takes some work to step through the different cases, but if anyone wants the details:

  • SUM: If R is 0, S is 0, and V is 0, then the circuit generates the 1's bit of op1 plus op2 plus carry-in, i.e. op1 xor op2 xor carry-in. To see this, the output is 1 if all three of op1, op2, and carry-in are set, or if at least one is set and there's no internal carry (i.e. exactly one is set).
  • XOR: If R is 1, S is 0, and V is 0, then the circuit generates op1 xor op2 To see this, note that this is like the previous case except carry-in is 0 because of R.
  • AND: If R is 0, S is 1, and V is 0, then the circuit generates op1 and op2. To see this, first note the internal carry is forced to 0, so the lower AND gate can never be active. The carry-in is forced to 1, so the result is generated by the upper AND gate.
  • OR: If R is 1, S is 1, and V is 1, then the circuit generates op1 or op2. The internal carry is forced to 0 by S and the the carry-out (carry-in) is forced to 0 by R. Thus, the top AND gate is disabled, and the 3-input OR gate controls the result.

Believe it or not, this is conceptually a lot simpler than the 8085's ALU, which I described in detail earlier. It's harder to understand, though, then the 6502's ALU, which uses simple gates to compute the AND, OR, SUM, and XOR in parallel, and then selects the desired result with pass transistors.

Conclusion

The Z-80's ALU is significantly different from the 6502 or 8085's ALU. The biggest difference is the 6502 and 8085 use 8-bit ALUs, while the Z-80 uses a 4-bit ALU. The Z-80 supports bit-addressed operations, which the 6502 and 8085 do not. The Z-80's BCD support is more advanced than the 8085's decimal adjust, since the Z-80 handles addition and subtraction, while the 8085 only handles addition. But the 6502 has more advanced BCD support with a decimal mode flag and fast, patented BCD logic.

If you've designed an ALU as part of a college class, it's interesting to compare an "academic" ALU with the highly-optimized ALU used in a real chip. It's interesting to see the short-cuts and tradeoffs that real chips use.

I've created a more detailed schematic of the Z-80 ALU that expands on the block diagram and the core schematic above and shows the gates and transistors that make up the ALU.

I hope this exploration into the Z-80 has convinced you that even with a 4-bit ALU, the Z-80 could still do 8-bit operations. You didn't get ripped off on your old TRS-80.

Credits: This couldn't have been done without the Visual 6502 team especially Chris Smith, Ed Spittles, Pavel Zima, Phil Mainwaring, and Julien Oster.

Intel x86 documentation has more pages than the 6502 has transistors

Microprocessors have become immensely more complex thanks to Moore's Law, but one thing that has been lost is the ability to fully understand them. The 6502 microprocessor was simple enough that its instruction set could almost be memorized. But now processors are so complex that understanding their architecture and instruction set even at a superficial level is a huge task. I've been reverse-engineering parts of the 6502, and with some work you can understand the role of each transistor in the 6502. After studying the x86 instruction set, I started wondering which was bigger: the number of transistors in the 6502 or the number of pages of documentation for the x86.

It turns out that Intel's Intel® 64 and IA-32 Architectures Software Developer Manuals (2011) have 4181 pages in total, while the 6502 has 3510 transistors. There are actually more pages of documentation for the x86 than the number of individual transistors in the 6502.

The above photo shows Intel's IA-32 software developer's manuals from 2004 on top of the 6502 chip's schematic. Since then the manuals have expanded to 7 volumes.

The 6502 has 3510 transistors, or 4528, or 6630, or maybe 9000?

As a slight tangent, it's actually hard to define the transistor count of a chip. The 6502 is usually reported as having 3510 transistors. This comes from the Visual 6502 team, which dissolved a 6502 chip in acid, photographed the die (below), traced every transistor in the image, and built a transistor-level simulator that runs 6502 code (which you really should try). Their number is 3510 transistors.

The 6502 processor chip

One complication is the 6502 is built with NMOS logic which builds gates out of active "enhancement" transistors as well as pull-up "depletion" transistors which basically act as resistors. The count of 3510 is just the enhancement transistors. If you include the 2102 1018 depletion transistors, the total transistor count is 5612 4528.

A second complication is that when manufacturers report the transistor count of chips, they often report "potential" transistors. Chips that include a ROM or PLA will have different numbers of transistors depending on the values stored in the ROM. Since marketing doesn't want to publish different transistor numbers depending on the number of 1 bits and 0 bits programmed into the chip, they often count ROM or PLA sites: places that could have transistors, but might not. By my count, the 6502 decode PLA has 21×131=2751 PLA sites, of which 649 actually have transistors. Adding these 2102 "potential" transistors yields a count of 6630 transistors.

Finally, some sources such as Microsoft Encarta and A History of the Personal Computer state the 6502 contains 9000 transistors, but I don't know how they could have come up with that value.

(The number of pages of Intel documentation is also not constant; the latest 2013 Software Developer Manuals have shrunk to 3251 pages.)

Thus, the x86 has more pages of documentation than the 6502 has transistors, but it depends how you count.

Reverse-engineering the Z-80: the silicon for two interesting gates explained

I've been reverse-engineering the Z-80 processor, using images from the Visual 6502 team. One interesting thing about the Z-80's silicon is it uses complex gates with multiple inputs and multiple levels of logic. It also implements an XOR gate with an unusual pass-transistor circuit. I thought it would be interesting to examine these gates at the silicon level and show how they work.

The image above shows the overall organization of the Z-80 chip. I'm going to zoom way in on the ALU and look at the silicon that implements one of the complex gates there: a 5-input, three-level gate. I'll walk through this gate and show how it works at the silicon level. While the silicon look like a jumble of lines, its operation is actually straightforward if you step through it.

Let's begin with an (oversimplified) description of how the chip is constructed. The chip starts with the silicon wafer. Regions are diffused with an element such as boron, yielding conductive diffusion regions. A layer of polysilicon strips is put on top. Finally, a layer of metal "wires" above the polysilicon provides more connections. For our purposes, diffusion regions, polysilicon, and metal can all be consider conductors.

In the image below, the bright vertical bands are metal wires. The slightly darker horizontal bands are polysilicon; the borders are more visible than the regions themselves. In this part of the Z-80, the polysilicon connections run mostly horizontally, and the metal wires run vertically. The large irregular regions outlined in black are doped silicon diffusion regions. The circles are vias between different layers.

Transistors are formed where a polysilicon line crosses a diffusion region. You might expect transistors to be very visible in the image, but a polysilicon line looks the same whether its a conductor or a transistor. So transistors just appear as long skinny regions in the image. The diagram below shows the physical structure of a transistor: the source and drain are connected if the gate is positive.

Structure of an NMOS transistor

Let's dive in and see how this circuit works. There's a lot going on, but the image below has been colored to make it clearer. Only three of the vertical metal lines are relevant. On the left, the yellow metal line ties together parts of the gate. In the middle is the blue ground line, which is critical to the operation of the gate. At the right, the red positive voltage line is used to pull the output high through a resistor. The large diffusion region has been tinted cyan. This region can be thought of as big conductive areas interrupted by transistors. There are 5 pinkish polysilicon input wires, labeled A, B, C, D, E. When they cross the diffusion region they still act as wires, but also form a transistor below in the diffusion region. For instance, input A is connected to two transistors.

With all the pieces labeled, we can figure out the operation of the circuit. If input A is high, the first transistor will conduct and connect the yellow strip to ground (dotted line 1). Likewise, if input B is high, the second transistor will conduct and ground the yellow strip (dotted line 2). C will ground the yellow strip via 3. So the yellow strip will be grounded for A or B or C. This forms a three-input OR gate.

If input D is high, transistor 4 will connect the yellow strip to the output. Likewise, if input E is high, transistor 5 will connect the yellow strip to the output. Thus, the output will be grounded if (A or B or C) and (D or E).

In the upper right, arrow 6/7/8 will ground the output if A and B and C are high and the three associated transistors (6, 7, 8) conduct. This computes A and B and C.

Putting this all together, the output will be grounded if [(A or B or C) and (D or E)] or [A and B and C]. If the output is not grounded, the resistor (actually a depletion transistor) will pull the output high. Thus, the final output is not [(A or B or C) and (D or E)] or [A and B and C].

The diagram below shows the gate logic implemented by this circuit. This rather complex gate is created from just nine transistors. Note that the final AND and NOR gates are "for free" - they are formed by wiring together previous outputs and don't require additional transistors. Another point of interest is that with NMOS, the output will be high unless something pulls it low, which explains why circuits are based on NAND and NOR gates rather than AND and OR gates.

If you want to see more low-level silicon analysis, see my article on the overflow circuit in the 6502 at the silicon level.

What does this gate do?

This gate is a key part of one bit of the Z-80's ALU. The gate generates the (inverted) sum, AND, OR, or XOR of B and C depending on the inputs. Specifically, B and C are the two operand inputs, and A is the carry in. D is a control input and E is an inverted intermediate carry from B plus C plus carry_in. By controlling D and overriding A and E, the operation is selected.

The Z-80's interesting XOR gate

The Z-80 uses an unusual circuit for its XOR gate. XOR is an inconvenient function to implement since it has a worst-case Karnaugh map, making it expensive to implement from simple gates. Instead, the Z-80 uses a combination of inverters and pass transistors, different from regular NMOS logic.

As before, the diagram below shows the power and ground metal lines, a connecting metal line in yellow, the polysilicon in pink, the polysilicon transistor gates in green, and diffusion in cyan. The two inputs are A and B.

Starting with input A: if it is high, transistor 1 will connect A' to ground. Otherwise the pullup resistor (way on the left), will pull A' high. (Note that A' is the whole diffusion region between transistor 1 and transistor 3 up to the resistor.) Thus transistor 1 forms a simple inverter with inverted output A'. Likewise, transistor 2 inverts input B to give inverted B' (in the whole diffusion region between transistors 2 and 4).

Now comes the tricky part. If A' is high, pass transistor 4 will connect B' to the yellow metal. If B' is high, pass transistor 3 will connect A' to the yellow metal. The third pullup resistor will pull the yellow metal high unless something ties it to ground . Working through the combinations, if A' and B' are both high, both A' and B' are connected to the yellow metal, which gets pulled high. If A' is high and B' is low, B' is connected to the yellow metal, pulling it low. Likewise, if A' is low and B' is high, A' pulls the yellow metal low. Finally if A' and B' are low, nothing gets connected to the yellow metal, so the resistor pulls it high.

To summarize, the yellow metal is pulled high if A' and B' are both high or both low. That is, it is the exclusive-nor of A' and B', which is also the exclusive-or of A and B.

Finally, the xnor value controls transistors 5a and 5b which form an inverter. If xnor is high, transistors 5a and 5b conduct and the xor output is connected to ground, and if xnor is low, the pullup resistors pull the xor output high. One unusual feature here is the parallel transistors 5a and 5b with separate pullup resistors. I haven't seen this in the 8085 or 6502; they use a single larger transistor instead of parallel transistors.

The schematic below summarizes the circuit. In case you're wondering, this XOR gate is used to compute the parity flag. All the bits are XORed together to generate the parity flag.

Comparison to other processors

From what I've seen so far, the Z-80 uses considerably more complex gates than the 8085 and the 6502. The 6502 uses mostly simple NAND/NOR gates and only a few two-level gates, not as complex as on the Z-80. The 8085 uses more complex gates, but still less than the Z-80. I don't know if the difference is due to technical limits on the number of gate levels, or the preferences of the designers.

The XOR circuit in the Z-80 is different from the 8085 and 6502. I'm not sure it saves any transistors, but it is unusual. I've seen other pass-transistor implementations of XOR, but none like the Z-80.

Credits: The Visual 6502 team especially Chris Smith, Ed Spittles, Pavel Zima, Phil Mainwaring, and Julien Oster.

9 Hacker News comments I'm tired of seeing

As a long-time reader of Hacker News, I keep seeing some comments they don't really contribute to the conversation. Since the discussions are one of the most interesting parts of the site I offer my suggestions for improving quality.
  • Correlation is not causation: the few readers who don't know this already won't benefit from mentioning it. If there's some specific reason you think a a study is wrong, describe it.
  • "If you're not paying for it, you're the product" - That was insightful the first time, but doesn't need to be posted about every free website.
  • Explaining a company's actions by "the legal duty to maximize shareholder value" - Since this can be used to explain any action by a company, it explains nothing. Not to mention the validity of the statement is controversial.
  • [citation needed] - This isn't Wikipedia, so skip the passive-aggressive comments. If you think something's wrong, explain why.
  • Premature optimization - labeling every optimization with this vaguely Freudian phrase doesn't make you the next Knuth. Calling every abstraction a leaky abstraction isn't useful either.
  • Dunning-Kruger effect - an overused explanation and criticism.
  • Betteridge's law of headlines - this comment doesn't need to appear every time a title ends in a question mark.
  • A link to a logical fallacy, such as ad hominem or more pretentiously tu quoque - this isn't a debate team and you don't score points for this.
  • "Cue the ...", "FTFY", "This.", "+1", "Sigh", "Meh", and other generic internet comments are just annoying.
My readers had a bunch of good suggestions. Here are a few:
  • The plural of anecdote is not data
  • Cargo cult
  • Comments starting with "No." "Wrong." or "False."
  • Just use bootstrap / heroku / nodejs / Haskell / Arduino.
  • "How [or Why] did this make the front page of HN?" followed by http://ycombinator.com/newsguidelines.html
In general if a comment could fit on a bumper sticker or is simply a link to a Wikipedia page or is almost a Hacker News meme, it's probably not useful.

What comments bother you the most?

Check out the long discussion at Hacker News. Thanks for visiting, HN readers!

Amusing note: when I saw the comments below, I almost started deleting them thinking "These are the stupidest comments I've seen in a long time". Then I realized I'd asked for them :-)

Edit: since this is getting a lot of attention, I'll add my "big theory" of Internet discussions.

There are three basic types of online participants: "watercooler", "scientific conference", and "debate team". In "watercooler", the participants are having an entertaining conversation and sharing anecdotes. In "scientific conference", the participants are trying to increase knowledge and solve problems. In "debate team", the participants are trying to prove their point is right.

HN was originally largely in the "scientific conference" mode, with very smart people discussing areas in which they were experts. Now HN has much more "watercooler" flavor, with smart people chatting about random things they often know little about. And certain subjects (e.g. economics, Apple, sexism, piracy) bring out the "debate team" commenters. Any of the three types can carry on happily by themself. However, much of the problem comes when the types of conversation mix. The "watercooler" conversations will annoy the "scientific conference" readers, since half of what they say is wrong. Conversely, the "scientific conference" commenters come across as pedantic when they interrupt a fun conversation with facts and corrections. A conversation between "debate team" and one of the other groups obviously goes nowhere.