Autolykos Algorithm#

This page provides a brief Overview of the Autolykos algorithm, followed by an in-depth, technical line-by-line breakdown.

Overview#

• Autolykos v1 originally had pool-resistance built-in through the use of non-outsourceable puzzles.
• The Hardening Hard-Fork on block 417,792 marked the launch of Autolykos v2, enabling mining pools. See this paper.
• EIP27: was passed with overwhelming community support, extending emission by 4,566,336 blocks (~17.38 years). This was activated on block 777217

Autolykos V2#

Autolykos V1 was originally pool resistant. However, it became apparent that pool resistance was infeasible due to large players having an advantage with smart contracts. "Bypassing Non-Outsourceable Proof-of-Work Schemes Using Collateralized Smart Contracts" was presented by Alex Chepurnoy at the WTSC workshop associated with Financial Cryptography and Data Security 2020 in Malaysia.

Autolykos V2 has the following modifications

• non-outsourceable puzzles were disabled.
• The algorithm tries to bind an efficient solving procedure with a single table of ~2 GB (initially), which significantly reduces memory optimisation possibilities.
• The table size (memory requirements of a solving algorithm) grows with time.
• The table depends solely on the block height, so there is no penalisation for recalculating block candidates for the same height.

Basic Ideas:

• Like Autolykos-1, based on the k-sum problem, a miner needs to find k (k=32) out of N (2n = 226) elements, and the hash of their sum must be less than the target value (inverse of the difficulty)
• k indexes are pseudorandom values derived from block candidate and nonce
• N elements are derived from block height and constants, unlike Autolykos v.1, so miners can recalculate block candidates quickly now (as only indexes depend on them)
• Indexes calculation also involves the same table
• (which elements are the last 31 bytes of H(i | | h | | M ), where i is in [0, N),
• h is block height,
• M is padding to slow down hash calculation (8kb of constant data).

The algorithm attempts to make mining efficient for ones that store the table, which is 226 * 31 = 2,080,374,784 bytes initially (about 2GB).

The table size (N value) grows with time as follows.

• Until block 614,400, N = 2^{26} = 67,108,864 elements (31 bytes each).
• From this block, and until block 4,198,400, every 51,200 blocks N is increased by 5 percent.
• At block 4,198,400, the value of N is fixed and equals to 2,143,944,600.

Test vectors for N values are provided in the paper.

Line-by-line#

Autolykos is based on the Equihash paper and the birthday problem.

To summarise, the miner is tasked to find k (=32) out of N elements, such that the hash of the sum of the elements is less than the target.

Autolykos Block Mining Pseudocode

Before discussing the block mining procedure, the algorithm first requires

• a very large cyclic group G
• of prime order q
• with fixed generator g
• and identity element e.

This prime group returns integers in Z/qZ during the Blake2b256-based hashing function.

Example cyclic group with generator z, identity element 1, order 6

We will not focus extensively on the cyclic group as it only covers a small segment of the PoW scheme. Now, let’s tackle Autolykos Block mining line by line.

Line 1 – Input h and m#

Input: upcoming block header hash m, block height h

The PoW begins with two inputs:

• the block height h
• the upcoming block header hash m.

The block header hash is a hash of the block header components, (i,e previous block header hash, Merkle root, nonce, etc.)

Line 2 – Calculate list R#

Firstly, it is important to notice the H() notation in line 2. This notation calls the hashing function Algorithm 3. Algorithm 3 is a hash function based on Blake2b256 and is used throughout Autolykos.

Algorithm 3 states that if the Blake hash of the inputs is below

2256 (= 1664 = 0xFFFFFFFFFFFF86633A9E8F1256D61ED5325EBF2A4B4366BA0000000000000000)

then hash.mod(q) is returned.

If not, Algorithm 3 repeats until it reaches a numeric hash within the valid range. For reference, note that q is the prime order of group G, Blake2b256 hash outputs are 256 bits, 64 digits long, and Algorithm 3 will always return a numeric hash in Z/qZ.

Blake2b256 Based Hash function

In line 2, the focus is the creation of list R. List R contains r values which are 31-byte numeric hashes created from integers in [0, N). r values are generated by takeright(31,H(j||h||M)).

The variables are as follows:

• j, integer in [0, N)
• h, block height
• M, 8kb of constant data - padding to slow down the hash calculation

The section takeRight(31,H(…)) means that given H(…), a 32-byte Blake2b256 output, the 31 bytes on the right (i.e. in little-endian (whereas other hash algorithms are bit endian)) are returned.

In other words, the most significant byte, the byte farthest to the left, is dropped. As a result, each r value is the 31 least significant bytes derived from the 32-byte H(j||h||M)) output.

For example, - if j = 1, r1 = takeRight(31,H(1||h||M)). - List R consists of N elements and can be generated for each block by incrementing j by 1 N-1 times.

Since H(…) returns hash.mod(q), we can state that list R consists of r0, 1, 2, 3 … N-1_ and _list R ⊂ Z/qZ.

As stated in the Autolykos v2 whitepaper

N elements are derived from block height and constants, unlike Autolykos v1, so miners can recalculate block candidates easily now (only indexes are depending on them).

In other words,

• j is always in [0,N),
• N is determined by h,
• M is always constant, and h changes every block,
• the only variable a miner needs to compute list R is h. (List R is stored in RAM)

In Autolykos, N = 226 (67,108,864 integers) is used in implementation for every block before 614400. Thus, the memory requirement for blocks before block 614400 is (226 * 31 bytes =) 2.08GB.

N first increased on block 614400. Post block 614400, every 51200 blocks, N increases by 5%. In other words, the memory requirement of an Ergo miner increases by 5% every ~71 days.

The last two values listed in the table should be 2,143,944,600 and not 2,147,387,550. After block 4198400, the storage requirement of list R will be (31 bytes * 2,143,944,600) = 66.46GB.

N elements based on block height

N elements, Ethash vs. Autolykos

Autolykos is like Ethash in the sense that block height determines N elements to be stored in RAM.

• With Autolykos, block height determines N 31-byte numeric hashes to be stored.
• With Ethash, block height determines N 128B DAG pages to be stored.

You might ask yourself if an Ergo block occurs every 2 minutes, how can Ergo miners generate a 2GB+ dataset so quickly? Ethereum miners only regenerate the DAG every 100 hours because it takes so long…

For an Ergo miner, the burden to compute list R is N instances of Algorithm 3; remember, each r value is computed as takeRight(31,H(j||h||M)).

However, a GPU can do this very quickly as GPUs generally have 32-wide or 64-wide multiprocessors (meaning that 32 or 64 Algorithm 3 instances can be done simultaneously).

For example, a 32-wide GPU such as the RTX570 can fill list R in just a few seconds.

Lines 3, 4 – begin while loop and guessing#

Calculate r
while true do


After calculating list R, the miner creates a nonce guess and enters a loop to test if the nonce ultimately creates an output below the given target value.

Lines 5, 6 – seed for generating indexes#

Line 5, i = takeRight(8, H(m||nonce)) mod N, produces an integer in [0,N). Algorithm 3 is utilised but with m and the nonce as inputs. Once the hash H(m||nonce) is returned, the eight least significant bytes are kept and passed through mod N. As a side note, the highest possible integer value with 8 bytes is 264 – 1, and assuming N = 226_, an 8-byte hash mod N will result in the first few digits being zero. The number of zeros in i decreases as N grows.

Line 6 produces e, a seed for index generating. Algorithm 3 is called with inputs i (generated in line 5), h, and M. Then, the most significant byte of the numeric hash is dropped, and the remaining 31 bytes are kept as value e. It should also be noted that value e can be retrieved from list R instead of being computed since e is an r value.

Line 7 – index generator#

Element index J is created using Algorithm 6 with inputs e, m,_ and nonce. Function genIndexes is a pseudorandom one-way that returns a list of k (=32) numbers in [0,N).

genIndexes function

A couple of extra steps are not shown in the pseudocode, such as a byteswap. The creation and application of genIndexes can be explained via the following example:

GenIndexes(e||m||nonce)...

• hash = Blake2b256(e||m||nonce) = [0xF963BAA1C0E8BF86, 0x317C0AFBA91C1F23, 0x56EC115FD3E46D89, 0x9817644ECA58EBFB]_
• hash64to32 = [0xC0E8BF86, 0xF963BAA1, 0xA91C1F23, 0x317C0AFB, 0xD3E46D89 0x56EC115F, 0xCA58EBFB, 0x9817644E]_
• extendedhash (i.e., byteswap and concatenate 4 bytes by repeating first 4 bytes) = [0x86BFE8C0, 0xA1BA63F9, 0x231F1CA9, 0xFB0A7C31, 0x896DE4D3, 0x5F11EC56, 0xFBEB58CA, 0x4E641798, 0x86BFE8C0]_

The following python code shows slicing the extended hash, returning k indexes. In this example we are assuming h < 614,400, thus N = 226 (67,108,864).

Slicing and mod N[1]

for i in range(8):
idxs[i << 2] = r[i] % np.uint32(ItemCount)
idxs[(i << 2) + 1] = ((r[i] << np.uint32(8)) | (r[i + 1] >> np.uint32(24))) % np.uint32(ItemCount)
idxs[(i << 2) + 2] = ((r[i] << np.uint32(16)) | (r[i + 1] >> np.uint32(16))) % np.uint32(ItemCount)
idxs[(i << 2) + 3] = ((r[i] << np.uint32(24)) | (r[i + 1] >> np.uint32(8))) % np.uint32(ItemCount)


The main takeaway is that slicing returns k indexes which are pseudorandom values derived from the seed, i.e., e, m, and nonce.

return [0x2BFE8C0, 0x3E8C0A1, 0xC0A1BA, 0xA1BA63, 0x1BA63F9, 0x263F923, 0x3F9231F, 0x1231F1C, 0x31F1CA9, 0x31CA9FB, 0xA9FB0A, 0x1FB0A7C, 0x30A7C31, 0x27C3189, 0x31896D, 0x1896DE4, 0x16DE4D3, 0x1E4D35F, 0xD35F11, 0x35F11EC, 0x311EC56, 0x1EC56FB, 0x56FBEB, 0x2FBEB58, 0x3EB58CA, 0x358CA4E, 0xCA4E64, 0x24E6417, 0x2641798, 0x179886, 0x39886BF, 0x86BFE8]

This index can be translated to values in base ten as it refers to numbers in [0, N). For instance, 0x2BFE8C0 = 46131392, 0x3E8C0A1 = 65585313, 0xC0A1BA = 12624314, and so on. The miner uses these indexes to retrieve k r values.

The genIndexes function prevents optimisations as it is extremely difficult, basically impossible, to find a seed such that genIndexes(seed) returns desired indexes.

Line 8 – sum of r elements given k#

Using the index generated in line 7, the miner retrieves the corresponding k (=32) r values from list R and sums these values. This might sound confusing but let’s break it down.

Continuing the example above, the miner stores the following indexes:

{0 | 46,131,392},
{1 | 65,585,313},
{2 | 12,624,314},
{3 | 10,599,011},
…
{31 | 8,830,952}


Given the indexes above, the miner retrieves the following r values from list R stored in memory.

{0 | 46,131,392} → _dropMsb(H(46,131,392||h||M))_
{1 | 65,585,313} → _dropMsb(H(65,585,313||h||M))_
{2 | 12,624,314} → _dropMsb(H(12,624,314||h||M))_
{3 | 10,599,011} → _dropMsb(H(10,599,011||h||M))_
…
{31 | 8,830,952} → _dropMsb(H(8,830,952||h||M))_


Note that Takeright(31) operated on a 32-byte hash can also be written as dropMsb (drop most significant byte).

Since the miner already stores list R in RAM, the miner does not need to compute k (= 32) Blake2b256 functions and instead looks up the values.

This is a key feature of ASIC resistance. An ASIC with limited memory needs to compute 32 Blake2b256 iterations to get the values that could have been looked up in memory, and fetching from memory takes much less time.

An ASIC with limited memory would require 32 Blake2b256 instances physically on the die to achieve one hash per cycle, which would require more area and higher costs. It's simple to prove that storing list R in memory is well worth the trade-off.

Assume the following, a GPU has a hash rate of G = 100MH/s, N = 226, k = 32, block interval t = 120 seconds, and elements are looked up every four hashes. We can assume that elements are looked up every four hashes because, for each nonce guess, multiple elements such as i, J, and H(f) require Algorithm 3, i.e. blake2b hash, instances.

We can estimate that each r value will be used, on average, (G * k * t)/(N*4) = 1430.51 times.

Once the 32 r values are looked up, they are summed.

Line 9, 10, 11, 12 – check if the hash of sum is below target#

The sum of the 32 r values is hashed using Algorithm 3, and if the output is below target b, the PoW is successful, m and nonce are returned to network nodes, and the miner is rewarded in ERG. If the sum hash is above the target, Lines 4 – 11 are repeated with a new nonce.

If you have made it this far, congratulations! After reading all of this information, you should have a good understanding of Autolykos v2! If you want a visual demonstration of Autolykos, please see the graphic at the end of this document. If you would like a video explanation, you can find it here.