Add cache generation and FNV hashing functions

This commit is contained in:
mratsim 2018-02-15 18:40:04 +01:00
parent bdff346e03
commit a557f8e675
3 changed files with 76 additions and 5 deletions

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@ -1,11 +1,14 @@
# Copyright (c) 2018 Status Research & Development GmbH
# Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
import math, number_theory # https://github.com/numforge/number-theory
import math, sequtils,
number_theory, # Not on nimble yet: https://github.com/numforge/number-theory
keccak_tiny,
zero_functional
import ./private/primes
import ./private/[primes, bytes]
# TODO: consider switching from default int to uint64
# TODO: Switching from default int to uint64
# Note: array/seq indexing requires an Ordinal, uint64 are not.
# So to index arrays/seq we would need to cast uint64 to int anyway ...
@ -45,6 +48,61 @@ proc get_full_size(block_number: Natural): int {.noSideEffect.}=
dm.rem == 0 and dm.quot.isPrime):
result -= 2 * MIX_BYTES
# ###############################################################################
# Cache generation
proc mkcache(cache_size, seed: int): seq[Hash[512]] {.noSideEffect.}=
let n = cache_size div HASH_BYTES
# Sequentially produce the initial dataset
result = newSeq[Hash[512]](n)
result[0] = sha3_512 seed.asByteArray # TODO: spec is unclear if we interpret integers as array of bytes
for i in 1 ..< n:
result[i] = sha3_512 result[i-1].asByteArray
# Use a low-round version of randmemohash
for _ in 0 ..< CACHE_ROUNDS:
for i in 0 ..< n:
let
v = asByteArray(result[i])[0].int mod n
a = result[(i-1+n) mod n].asByteArray
b = result[v].asByteArray
result[i] = sha3_512 zip(a, b)-->map(it[0] xor it[1])
# ###############################################################################
# Data aggregation function
const FNV_PRIME = 0x01000193
proc fnv[T: SomeUnsignedInt or Natural](v1, v2: T): T =
# Original formula is ((v1 * FNV_PRIME) xor v2) mod 2^32
# However contrary to Python and depending on the type T,
# in Nim (v1 * FNV_PRIME) can overflow
# We can't do 2^32 with an int (only 2^32-1)
# and in general (a xor b) mod c != (a mod c) xor (b mod c)
#
# Thankfully
# We know that:
# - (a xor b) and c == (a and c) xor (b and c)
# - for powers of 2: a mod 2^p == a and (2^p - 1)
# - 2^32 - 1 == high(uint32)
const mask: T = 2^32 - 1
mulmod(v1 and mask, FNV_PRIME.T, (2^32).T) xor (v2 and mask)
# ###############################################################################
when isMainModule:
echo get_full_size(100000)
echo get_full_size(100000)
let a = sha3_512 1234.asByteArray
echo a
echo zip([0, 1, 2, 3], [10, 20, 30, 40]) --> map(it[0] * it[1]) # [0, 20, 60, 120]
echo zip(a.asByteArray, a.asByteArray) --> map(it[0] xor it[1])

13
src/private/bytes.nim Normal file
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# Copyright (c) 2018 Status Research & Development GmbH
# Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
import keccak_tiny
proc asByteArray*[T: not (ref|ptr|string)](data: T): array[sizeof(T), byte] =
## Cast stack allocated types to an array of byte
cast[type result](data)
proc asByteArray*(data: Hash[512]): array[64, byte] =
## Workaround: Nim cannot evaluate size of arrays
## https://github.com/nim-lang/Nim/issues/5802
cast[type result](data)

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@ -4,7 +4,7 @@
# Primality testing. TODO: a scalable implementation (i.e. Miller-Rabin)
# See https://github.com/mratsim/nim-projecteuler/blob/master/src/lib/primes.nim
import number_theory # https://github.com/numforge/number-theory
import number_theory # Not on Nimble yet: https://github.com/numforge/number-theory
proc isPrime*(x: SomeUnsignedInt): bool {.noSideEffect.}=