GOSTcoin support for ccminer CUDA miner project, compatible with most nvidia cards
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#include <memory.h>
#include "cuda_helper.h"
#define TPB 160
static __constant__ uint2 blake2b_IV[8] = {
{ 0xf3bcc908, 0x6a09e667 },
{ 0x84caa73b, 0xbb67ae85 },
{ 0xfe94f82b, 0x3c6ef372 },
{ 0x5f1d36f1, 0xa54ff53a },
{ 0xade682d1, 0x510e527f },
{ 0x2b3e6c1f, 0x9b05688c },
{ 0xfb41bd6b, 0x1f83d9ab },
{ 0x137e2179, 0x5be0cd19 }
};
#define reduceDuplexRow(rowIn, rowInOut, rowOut) { \
for (int i = 0; i < 8; i++) { \
for (int j = 0; j < 12; j++) \
state[j] ^= Matrix[12 * i + j][rowIn] + Matrix[12 * i + j][rowInOut]; \
round_lyra(state); \
for (int j = 0; j < 12; j++) \
Matrix[j + 12 * i][rowOut] ^= state[j]; \
Matrix[0 + 12 * i][rowInOut] ^= state[11]; \
Matrix[1 + 12 * i][rowInOut] ^= state[0]; \
Matrix[2 + 12 * i][rowInOut] ^= state[1]; \
Matrix[3 + 12 * i][rowInOut] ^= state[2]; \
Matrix[4 + 12 * i][rowInOut] ^= state[3]; \
Matrix[5 + 12 * i][rowInOut] ^= state[4]; \
Matrix[6 + 12 * i][rowInOut] ^= state[5]; \
Matrix[7 + 12 * i][rowInOut] ^= state[6]; \
Matrix[8 + 12 * i][rowInOut] ^= state[7]; \
Matrix[9 + 12 * i][rowInOut] ^= state[8]; \
Matrix[10+ 12 * i][rowInOut] ^= state[9]; \
Matrix[11+ 12 * i][rowInOut] ^= state[10]; \
} \
}
#define absorbblock(in) { \
state[0] ^= Matrix[0][in]; \
state[1] ^= Matrix[1][in]; \
state[2] ^= Matrix[2][in]; \
state[3] ^= Matrix[3][in]; \
state[4] ^= Matrix[4][in]; \
state[5] ^= Matrix[5][in]; \
state[6] ^= Matrix[6][in]; \
state[7] ^= Matrix[7][in]; \
state[8] ^= Matrix[8][in]; \
state[9] ^= Matrix[9][in]; \
state[10] ^= Matrix[10][in]; \
state[11] ^= Matrix[11][in]; \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
}
static __device__ __forceinline__
void Gfunc(uint2 & a, uint2 &b, uint2 &c, uint2 &d)
{
a += b; d ^= a; d = SWAPUINT2(d);
c += d; b ^= c; b = ROR2(b, 24);
a += b; d ^= a; d = ROR2(d, 16);
c += d; b ^= c; b = ROR2(b, 63);
}
__device__ __forceinline__
static void round_lyra(uint2 *s)
{
Gfunc(s[0], s[4], s[8], s[12]);
Gfunc(s[1], s[5], s[9], s[13]);
Gfunc(s[2], s[6], s[10], s[14]);
Gfunc(s[3], s[7], s[11], s[15]);
Gfunc(s[0], s[5], s[10], s[15]);
Gfunc(s[1], s[6], s[11], s[12]);
Gfunc(s[2], s[7], s[8], s[13]);
Gfunc(s[3], s[4], s[9], s[14]);
}
__device__ __forceinline__
void reduceDuplexRowSetup(const int rowIn, const int rowInOut, const int rowOut, uint2 state[16], uint2 Matrix[96][8])
{
for (int i = 0; i < 8; i++)
{
#pragma unroll
for (int j = 0; j < 12; j++)
state[j] ^= Matrix[12 * i + j][rowIn] + Matrix[12 * i + j][rowInOut];
round_lyra(state);
#pragma unroll
for (int j = 0; j < 12; j++)
Matrix[j + 84 - 12 * i][rowOut] = Matrix[12 * i + j][rowIn] ^ state[j];
Matrix[0 + 12 * i][rowInOut] ^= state[11];
Matrix[1 + 12 * i][rowInOut] ^= state[0];
Matrix[2 + 12 * i][rowInOut] ^= state[1];
Matrix[3 + 12 * i][rowInOut] ^= state[2];
Matrix[4 + 12 * i][rowInOut] ^= state[3];
Matrix[5 + 12 * i][rowInOut] ^= state[4];
Matrix[6 + 12 * i][rowInOut] ^= state[5];
Matrix[7 + 12 * i][rowInOut] ^= state[6];
Matrix[8 + 12 * i][rowInOut] ^= state[7];
Matrix[9 + 12 * i][rowInOut] ^= state[8];
Matrix[10 + 12 * i][rowInOut] ^= state[9];
Matrix[11 + 12 * i][rowInOut] ^= state[10];
}
}
__global__ __launch_bounds__(TPB, 1)
void lyra2_gpu_hash_32(int threads, uint32_t startNounce, uint64_t *outputHash)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint2 state[16];
#pragma unroll
for (int i = 0; i<4; i++) {
LOHI(state[i].x, state[i].y, outputHash[threads*i + thread]);
} //password
#pragma unroll
for (int i = 0; i<4; i++) {
state[i + 4] = state[i];
} //salt
#pragma unroll
for (int i = 0; i<8; i++) {
state[i + 8] = blake2b_IV[i];
}
// blake2blyra x2
//#pragma unroll 24
for (int i = 0; i<24; i++) {
round_lyra(state);
} //because 12 is not enough
uint2 Matrix[96][8]; // not cool
// reducedSqueezeRow0
#pragma unroll 8
for (int i = 0; i < 8; i++)
{
#pragma unroll 12
for (int j = 0; j<12; j++) {
Matrix[j + 84 - 12 * i][0] = state[j];
}
round_lyra(state);
}
// reducedSqueezeRow1
#pragma unroll 8
for (int i = 0; i < 8; i++)
{
#pragma unroll 12
for (int j = 0; j<12; j++) {
state[j] ^= Matrix[j + 12 * i][0];
}
round_lyra(state);
#pragma unroll 12
for (int j = 0; j<12; j++) {
Matrix[j + 84 - 12 * i][1] = Matrix[j + 12 * i][0] ^ state[j];
}
}
reduceDuplexRowSetup(1, 0, 2,state, Matrix);
reduceDuplexRowSetup(2, 1, 3, state, Matrix);
reduceDuplexRowSetup(3, 0, 4, state, Matrix);
reduceDuplexRowSetup(4, 3, 5, state, Matrix);
reduceDuplexRowSetup(5, 2, 6, state, Matrix);
reduceDuplexRowSetup(6, 1, 7, state, Matrix);
uint32_t rowa;
rowa = state[0].x & 7;
reduceDuplexRow(7, rowa, 0);
rowa = state[0].x & 7;
reduceDuplexRow(0, rowa, 3);
rowa = state[0].x & 7;
reduceDuplexRow(3, rowa, 6);
rowa = state[0].x & 7;
reduceDuplexRow(6, rowa, 1);
rowa = state[0].x & 7;
reduceDuplexRow(1, rowa, 4);
rowa = state[0].x & 7;
reduceDuplexRow(4, rowa, 7);
rowa = state[0].x & 7;
reduceDuplexRow(7, rowa, 2);
rowa = state[0].x & 7;
reduceDuplexRow(2, rowa, 5);
absorbblock(rowa);
#pragma unroll
for (int i = 0; i<4; i++) {
outputHash[threads*i + thread] = devectorize(state[i]);
} //password
} //thread
}
__host__
void lyra2_cpu_hash_32(int thr_id, int threads, uint32_t startNounce, uint64_t *d_outputHash, int order)
{
const int threadsperblock = TPB;
dim3 grid((threads + threadsperblock - 1) / threadsperblock);
dim3 block(threadsperblock);
lyra2_gpu_hash_32 <<<grid, block>>> (threads, startNounce, d_outputHash);
}