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mratsimmratsim
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Add Ethereum mining (⚠ no test)
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‎src/ethash.nim‎

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# Copyright (c) 2018 Status Research & Development GmbH
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# Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
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import math, endians,
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keccak_tiny
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import ./proof_of_work, mining
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import ./private/[primes, casting, functional, intmath]
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export toHex, hexToByteArrayBE, hexToSeqBytesBE, toByteArrayBE # debug functions
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export keccak_tiny
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# ###############################################################################
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# Definitions
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const
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REVISION* = 23 # Based on spec revision 23
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WORD_BYTES = 4 # bytes in word - in Nim we use 64 bits words # TODO check that
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DATASET_BYTES_INIT* = 2'u^30 # bytes in dataset at genesis
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DATASET_BYTES_GROWTH* = 2'u^23 # dataset growth per epoch
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CACHE_BYTES_INIT* = 2'u^24 # bytes in cache at genesis
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CACHE_BYTES_GROWTH* = 2'u^17 # cache growth per epoch
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CACHE_MULTIPLIER = 1024 # Size of the DAG relative to the cache
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EPOCH_LENGTH* = 30000 # blocks per epoch
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MIX_BYTES* = 128 # width of mix
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HASH_BYTES* = 64 # hash length in bytes
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DATASET_PARENTS* = 256 # number of parents of each dataset element
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CACHE_ROUNDS* = 3 # number of rounds in cache production
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ACCESSES* = 64 # number of accesses in hashimoto loop
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# ###############################################################################
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# Parameters
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proc get_cache_size*(block_number: uint): uint {.noSideEffect.}=
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result = CACHE_BYTES_INIT + CACHE_BYTES_GROWTH * (block_number div EPOCH_LENGTH)
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result -= HASH_BYTES
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while (let dm = divmod(result, HASH_BYTES);
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dm.rem == 0 and not dm.quot.isPrime):
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# In a static lang, checking that the result of a division is prime
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# Means checking that reminder == 0 and quotient is prime
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result -= 2 * HASH_BYTES
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proc get_data_size*(block_number: uint): uint {.noSideEffect.}=
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result = DATASET_BYTES_INIT + DATASET_BYTES_GROWTH * (block_number div EPOCH_LENGTH)
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result -= MIX_BYTES
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while (let dm = divmod(result, MIX_BYTES);
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dm.rem == 0 and not dm.quot.isPrime):
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result -= 2 * MIX_BYTES
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# ###############################################################################
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# Fetch from lookup tables of 2048 epochs of data sizes and cache sizes
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import ./data_sizes
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proc get_datasize_lut*(block_number: Natural): uint64 {.noSideEffect, inline.} =
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data_sizes[block_number div EPOCH_LENGTH]
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proc get_cachesize_lut*(block_number: Natural): uint64 {.noSideEffect, inline.} =
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cache_sizes[block_number div EPOCH_LENGTH]
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# ###############################################################################
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# Cache generation
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proc mkcache*(cache_size: uint64, seed: Hash[256]): seq[Hash[512]] {.noSideEffect.}=
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# Cache size
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let n = int(cache_size div HASH_BYTES)
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# Sequentially produce the initial dataset
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result = newSeq[Hash[512]](n)
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result[0] = keccak512 seed.data
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for i in 1 ..< n:
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result[i] = keccak512 result[i-1].data
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# Use a low-round version of randmemohash
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for _ in 0 ..< CACHE_ROUNDS:
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for i in 0 ..< n:
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let
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v = result[i].as_u32_words[0] mod n.uint32
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a = result[(i-1+n) mod n].data
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b = result[v.int].data
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result[i] = keccak512 zipMap(a, b, x xor y)
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# ###############################################################################
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# Data aggregation function
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const FNV_PRIME = 0x01000193
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proc fnv*[T: SomeUnsignedInt or Natural](v1, v2: T): uint32 {.inline, noSideEffect.}=
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# Original formula is ((v1 * FNV_PRIME) xor v2) mod 2^32
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# However contrary to Python and depending on the type T,
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# in Nim (v1 * FNV_PRIME) can overflow
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# We can't do 2^32 with an int (only 2^32-1)
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# and in general (a xor b) mod c != (a mod c) xor (b mod c)
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#
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# Thankfully
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# We know that:
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# - (a xor b) and c == (a and c) xor (b and c)
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# - for powers of 2: a mod 2^p == a and (2^p - 1)
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# - 2^32 - 1 == high(uint32)
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# So casting to uint32 should do the modulo and masking just fine
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(v1.uint32 * FNV_PRIME) xor v2.uint32
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# ###############################################################################
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# Full dataset calculation
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proc calc_dataset_item*(cache: seq[Hash[512]], i: Natural): Hash[512] {.noSideEffect, noInit.} =
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let n = cache.len
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const r: uint32 = HASH_BYTES div WORD_BYTES
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# Alias for the result value. Interpreted as an array of uint32 words
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var mix = cast[ptr array[16, uint32]](addr result)
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mix[] = cache[i mod n].as_u32_words
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when system.cpuEndian == littleEndian:
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mix[0] = mix[0] xor i.uint32
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else:
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mix[high(mix)] = mix[high(mix)] xor i.uint32
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result = keccak512 mix[]
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# FNV with a lots of random cache nodes based on i
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for j in 0'u32 ..< DATASET_PARENTS:
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let cache_index = fnv(i.uint32 xor j, mix[j mod r])
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mix[] = zipMap(mix[], cache[cache_index.int mod n].as_u32_words, fnv(x, y))
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result = keccak512 mix[]
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proc calc_dataset*(full_size: Natural, cache: seq[Hash[512]]): seq[Hash[512]] {.noSideEffect.} =
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result = newSeq[Hash[512]](full_size div HASH_BYTES)
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for i, hash in result.mpairs:
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hash = calc_dataset_item(cache, i)
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# ###############################################################################
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# Main loop
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type HashimotoHash = tuple[mix_digest: Hash[256], value: Hash[256]]
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type DatasetLookup = proc(i: Natural): Hash[512] {.noSideEffect.}
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proc hashimoto(header: Hash[256],
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nonce: uint64,
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full_size: Natural,
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dataset_lookup: DatasetLookup
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): HashimotoHash {.noInit, noSideEffect.}=
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let
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n = uint32 full_size div HASH_BYTES
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w = uint32 MIX_BYTES div WORD_BYTES
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mixhashes = uint32 MIX_BYTES div HASH_BYTES
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assert full_size mod HASH_BYTES == 0
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assert MIX_BYTES mod HASH_BYTES == 0
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# combine header+nonce into a 64 byte seed
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var s{.noInit.}: Hash[512]
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let s_bytes = cast[ptr array[64, byte]](addr s) # Alias for to interpret s as a byte array
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let s_words = cast[ptr array[16, uint32]](addr s) # Alias for to interpret s as an uint32 array
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s_bytes[0..<32] = header.data # We first populate the first 40 bytes of s with the concatenation
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var nonceLE{.noInit.}: array[8, byte] # the nonce should be concatenated with its LITTLE ENDIAN representation
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littleEndian64(addr nonceLE, unsafeAddr nonce)
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s_bytes[32..<40] = cast[array[8,byte]](nonceLE)
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s = keccak_512 s_bytes[0..<40] # TODO: Does this allocate a seq?
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# start the mix with replicated s
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assert MIX_BYTES div HASH_BYTES == 2
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var mix{.noInit.}: array[32, uint32]
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mix[0..<16] = s_words[]
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mix[16..<32] = s_words[]
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# mix in random dataset nodes
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for i in 0'u32 ..< ACCESSES:
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let p = fnv(i xor s_words[0], mix[i mod w]) mod (n div mixhashes) * mixhashes
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# Unrolled: for j in range(MIX_BYTES / HASH_BYTES): => for j in 0 ..< 2
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var newdata{.noInit.}: type mix
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newdata[0..<16] = cast[array[16, uint32]](dataset_lookup(p))
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newdata[16..<32] = cast[array[16, uint32]](dataset_lookup(p+1))
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mix = zipMap(mix, newdata, fnv(x, y))
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# compress mix
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var cmix{.noInit.}: array[8, uint32]
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for i in countup(0, mix.len - 1, 4):
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cmix[i div 4] = mix[i].fnv(mix[i+1]).fnv(mix[i+2]).fnv(mix[i+3])
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# ⚠⚠ Warning ⚠⚠: Another bigEndian littleEndian issue?
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# It doesn't seem like the uint32 in cmix need to be changed to big endian
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result.mix_digest = cast[Hash[256]](cmix)
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var concat{.noInit.}: array[64 + 32, byte]
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concat[0..<64] = s_bytes[]
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concat[64..<96] = cast[array[32, byte]](cmix)
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result.value = keccak_256(concat)
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proc hashimoto_light*(full_size:Natural, cache: seq[Hash[512]],
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header: Hash[256], nonce: uint64): HashimotoHash {.noSideEffect, inline.} =
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let light: DatasetLookup = proc(x: Natural): Hash[512] = calc_data_set_item(cache, x)
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hashimoto(header,
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nonce,
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full_size,
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light)
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proc hashimoto_full*(full_size:Natural, dataset: seq[Hash[512]],
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header: Hash[256], nonce: uint64): HashimotoHash {.noSideEffect, inline.} =
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# TODO spec mentions full_size but I don't think we need it (retrieve it from dataset.len)
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let full: DatasetLookup = proc(x: Natural): Hash[512] = dataset[x]
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hashimoto(header,
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nonce,
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full_size,
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full)
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# ###############################################################################
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# Defining the seed hash
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proc get_seedhash*(block_number: uint64): Hash[256] {.noSideEffect.} =
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for i in 0 ..< int(block_number div EPOCH_LENGTH):
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result = keccak256 result.data
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export proof_of_work, mining

‎src/mining.nim‎

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# Copyright (c) 2018 Status Research & Development GmbH
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# Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
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import ./proof_of_work, ./private/casting
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import ttmath, random
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let # NimVM cannot evaluate those at compile-time. So they are considered side-effects :/
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high_uint256 = 0.u256 - 1.u256
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half_max = pow(2.u256, 255)
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proc getBoundary(difficulty: uint64): UInt256 {.noInit, inline.} =
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# Boundary is 2^256/difficulty
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# We can't represent 2^256 as an uint256 so as a workaround we use:
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#
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# a mod b == (2 * a div 2) mod b
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# == (2 * (a div 2) mod b) mod b
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#
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# if 2^256 mod b = 0: # b is even (and a power of two)
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# result = 2^255 div (b div 2)
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# if 2^256 mod b != 0:
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# result = high(uint256) div b
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# TODO: review/test
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let b = difficulty.u256
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let modulo = (2.u256 * (half_max mod b)) mod b
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if modulo == 0.u256:
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result = half_max div (b shr 1)
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else:
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result = high_uint256 div b
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proc readUint256BE*(ba: ByteArrayBE[32]): UInt256 {.noSideEffect.}=
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## Convert a big-endian array of Bytes to an UInt256 (in native host endianness)
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const N = 32
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for i in 0 ..< N:
38+
result = result shl 8 or ba[i].u256
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40+
proc isValid(nonce: uint64,
41+
boundary: UInt256,
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full_size: Natural,
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dataset: seq[Hash[512]],
44+
header: Hash[256]): bool {.noSideEffect.}=
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46+
let candidate = hashimoto_full(full_size, dataset, header, nonce)
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result = readUint256BE(cast[ByteArrayBE[32]](candidate.value)) <= boundary
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proc mine*(full_size: Natural, dataset: seq[Hash[512]], header: Hash[256], difficulty: uint64): uint64 =
50+
# Returns a valid nonce
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let target = difficulty.getBoundary
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randomize() # Start with a completely random seed
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result = uint64 random(high(int)) # TODO: Nim random does not work on uint64 range.
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# Also random is deprecate and do not include the end of the range.
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while not result.isValid(target, full_size, dataset, header):
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inc(result) # we rely on uin overflow (mod 2^64) here.

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