GOSTCoin CUDA miner project, compatible with most nvidia cards, containing only gostd algo
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/*
* luffa_for_32.c
* Version 2.0 (Sep 15th 2009)
*
* Copyright (C) 2008-2009 Hitachi, Ltd. All rights reserved.
*
* Hitachi, Ltd. is the owner of this software and hereby grant
* the U.S. Government and any interested party the right to use
* this software for the purposes of the SHA-3 evaluation process,
* notwithstanding that this software is copyrighted.
*
* THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
* WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
* MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
* ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
* WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
* ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
* OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
*/
#include "cuda_helper.h"
typedef unsigned char BitSequence;
typedef struct {
uint32_t buffer[8]; /* Buffer to be hashed */
uint32_t chainv[40]; /* Chaining values */
} hashState;
#define MULT2(a,j)\
tmp = a[7+(8*j)];\
a[7+(8*j)] = a[6+(8*j)];\
a[6+(8*j)] = a[5+(8*j)];\
a[5+(8*j)] = a[4+(8*j)];\
a[4+(8*j)] = a[3+(8*j)] ^ tmp;\
a[3+(8*j)] = a[2+(8*j)] ^ tmp;\
a[2+(8*j)] = a[1+(8*j)];\
a[1+(8*j)] = a[0+(8*j)] ^ tmp;\
a[0+(8*j)] = tmp;
#if __CUDA_ARCH__ < 350
#define LROT(x,bits) ((x << bits) | (x >> (32 - bits)))
#else
#define LROT(x, bits) __funnelshift_l(x, x, bits)
#endif
#define TWEAK(a0,a1,a2,a3,j)\
a0 = LROT(a0,j);\
a1 = LROT(a1,j);\
a2 = LROT(a2,j);\
a3 = LROT(a3,j);
#define STEP(c0,c1)\
SUBCRUMB(chainv[0],chainv[1],chainv[2],chainv[3],tmp);\
SUBCRUMB(chainv[5],chainv[6],chainv[7],chainv[4],tmp);\
MIXWORD(chainv[0],chainv[4]);\
MIXWORD(chainv[1],chainv[5]);\
MIXWORD(chainv[2],chainv[6]);\
MIXWORD(chainv[3],chainv[7]);\
ADD_CONSTANT(chainv[0],chainv[4],c0,c1);
#define SUBCRUMB(a0,a1,a2,a3,a4)\
a4 = a0;\
a0 |= a1;\
a2 ^= a3;\
a1 = ~a1;\
a0 ^= a3;\
a3 &= a4;\
a1 ^= a3;\
a3 ^= a2;\
a2 &= a0;\
a0 = ~a0;\
a2 ^= a1;\
a1 |= a3;\
a4 ^= a1;\
a3 ^= a2;\
a2 &= a1;\
a1 ^= a0;\
a0 = a4;
#define MIXWORD(a0,a4)\
a4 ^= a0;\
a0 = LROT(a0,2);\
a0 ^= a4;\
a4 = LROT(a4,14);\
a4 ^= a0;\
a0 = LROT(a0,10);\
a0 ^= a4;\
a4 = LROT(a4,1);
#define ADD_CONSTANT(a0,b0,c0,c1)\
a0 ^= c0;\
b0 ^= c1;
/* initial values of chaining variables */
__device__ __constant__ uint32_t c_IV[40];
const uint32_t h_IV[40] = {
0x6d251e69,0x44b051e0,0x4eaa6fb4,0xdbf78465,
0x6e292011,0x90152df4,0xee058139,0xdef610bb,
0xc3b44b95,0xd9d2f256,0x70eee9a0,0xde099fa3,
0x5d9b0557,0x8fc944b3,0xcf1ccf0e,0x746cd581,
0xf7efc89d,0x5dba5781,0x04016ce5,0xad659c05,
0x0306194f,0x666d1836,0x24aa230a,0x8b264ae7,
0x858075d5,0x36d79cce,0xe571f7d7,0x204b1f67,
0x35870c6a,0x57e9e923,0x14bcb808,0x7cde72ce,
0x6c68e9be,0x5ec41e22,0xc825b7c7,0xaffb4363,
0xf5df3999,0x0fc688f1,0xb07224cc,0x03e86cea};
__device__ __constant__ uint32_t c_CNS[80];
const uint32_t h_CNS[80] = {
0x303994a6,0xe0337818,0xc0e65299,0x441ba90d,
0x6cc33a12,0x7f34d442,0xdc56983e,0x9389217f,
0x1e00108f,0xe5a8bce6,0x7800423d,0x5274baf4,
0x8f5b7882,0x26889ba7,0x96e1db12,0x9a226e9d,
0xb6de10ed,0x01685f3d,0x70f47aae,0x05a17cf4,
0x0707a3d4,0xbd09caca,0x1c1e8f51,0xf4272b28,
0x707a3d45,0x144ae5cc,0xaeb28562,0xfaa7ae2b,
0xbaca1589,0x2e48f1c1,0x40a46f3e,0xb923c704,
0xfc20d9d2,0xe25e72c1,0x34552e25,0xe623bb72,
0x7ad8818f,0x5c58a4a4,0x8438764a,0x1e38e2e7,
0xbb6de032,0x78e38b9d,0xedb780c8,0x27586719,
0xd9847356,0x36eda57f,0xa2c78434,0x703aace7,
0xb213afa5,0xe028c9bf,0xc84ebe95,0x44756f91,
0x4e608a22,0x7e8fce32,0x56d858fe,0x956548be,
0x343b138f,0xfe191be2,0xd0ec4e3d,0x3cb226e5,
0x2ceb4882,0x5944a28e,0xb3ad2208,0xa1c4c355,
0xf0d2e9e3,0x5090d577,0xac11d7fa,0x2d1925ab,
0x1bcb66f2,0xb46496ac,0x6f2d9bc9,0xd1925ab0,
0x78602649,0x29131ab6,0x8edae952,0x0fc053c3,
0x3b6ba548,0x3f014f0c,0xedae9520,0xfc053c31};
/***************************************************/
__device__ __forceinline__
void rnd512(hashState *state)
{
int i,j;
uint32_t t[40];
uint32_t chainv[8];
uint32_t tmp;
#pragma unroll 8
for(i=0;i<8;i++) {
t[i]=0;
#pragma unroll 5
for(j=0;j<5;j++) {
t[i] ^= state->chainv[i+8*j];
}
}
MULT2(t, 0);
#pragma unroll 5
for(j=0;j<5;j++) {
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i+8*j] ^= t[i];
}
}
#pragma unroll 5
for(j=0;j<5;j++) {
#pragma unroll 8
for(i=0;i<8;i++) {
t[i+8*j] = state->chainv[i+8*j];
}
}
#pragma unroll 5
for(j=0;j<5;j++) {
MULT2(state->chainv, j);
}
#pragma unroll 5
for(j=0;j<5;j++) {
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[8*j+i] ^= t[8*((j+1)%5)+i];
}
}
#pragma unroll 5
for(j=0;j<5;j++) {
#pragma unroll 8
for(i=0;i<8;i++) {
t[i+8*j] = state->chainv[i+8*j];
}
}
#pragma unroll 5
for(j=0;j<5;j++) {
MULT2(state->chainv, j);
}
#pragma unroll 5
for(j=0;j<5;j++) {
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[8*j+i] ^= t[8*((j+4)%5)+i];
}
}
#pragma unroll 5
for(j=0;j<5;j++) {
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i+8*j] ^= state->buffer[i];
}
MULT2(state->buffer, 0);
}
#pragma unroll 8
for(i=0;i<8;i++) {
chainv[i] = state->chainv[i];
}
#pragma unroll 8
for(i=0;i<8;i++) {
STEP(c_CNS[(2*i)],c_CNS[(2*i)+1]);
}
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i] = chainv[i];
chainv[i] = state->chainv[i+8];
}
TWEAK(chainv[4],chainv[5],chainv[6],chainv[7],1);
#pragma unroll 8
for(i=0;i<8;i++) {
STEP(c_CNS[(2*i)+16],c_CNS[(2*i)+16+1]);
}
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i+8] = chainv[i];
chainv[i] = state->chainv[i+16];
}
TWEAK(chainv[4],chainv[5],chainv[6],chainv[7],2);
#pragma unroll 8
for(i=0;i<8;i++) {
STEP(c_CNS[(2*i)+32],c_CNS[(2*i)+32+1]);
}
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i+16] = chainv[i];
chainv[i] = state->chainv[i+24];
}
TWEAK(chainv[4],chainv[5],chainv[6],chainv[7],3);
#pragma unroll 8
for(i=0;i<8;i++) {
STEP(c_CNS[(2*i)+48],c_CNS[(2*i)+48+1]);
}
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i+24] = chainv[i];
chainv[i] = state->chainv[i+32];
}
TWEAK(chainv[4],chainv[5],chainv[6],chainv[7],4);
#pragma unroll 8
for(i=0;i<8;i++) {
STEP(c_CNS[(2*i)+64],c_CNS[(2*i)+64+1]);
}
#pragma unroll 8
for(i=0;i<8;i++) {
state->chainv[i+32] = chainv[i];
}
}
__device__ __forceinline__
void Update512(hashState *state, const BitSequence *data)
{
#pragma unroll 8
for(int i=0;i<8;i++) state->buffer[i] = cuda_swab32(((uint32_t*)data)[i]);
rnd512(state);
#pragma unroll 8
for(int i=0;i<8;i++) state->buffer[i] = cuda_swab32(((uint32_t*)(data+32))[i]);
rnd512(state);
}
/***************************************************/
__device__ __forceinline__
void finalization512(hashState *state, uint32_t *b)
{
int i,j;
state->buffer[0] = 0x80000000;
#pragma unroll 7
for(int i=1;i<8;i++) state->buffer[i] = 0;
rnd512(state);
/*---- blank round with m=0 ----*/
#pragma unroll 8
for(i=0;i<8;i++) state->buffer[i] =0;
rnd512(state);
#pragma unroll 8
for(i=0;i<8;i++) {
b[i] = 0;
#pragma unroll 5
for(j=0;j<5;j++) {
b[i] ^= state->chainv[i+8*j];
}
b[i] = cuda_swab32((b[i]));
}
#pragma unroll 8
for(i=0;i<8;i++) state->buffer[i]=0;
rnd512(state);
#pragma unroll 8
for(i=0;i<8;i++) {
b[8+i] = 0;
#pragma unroll 5
for(j=0;j<5;j++) {
b[8+i] ^= state->chainv[i+8*j];
}
b[8 + i] = cuda_swab32((b[8 + i]));
}
}
/***************************************************/
// Die Hash-Funktion
__global__ void x11_luffa512_gpu_hash_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
uint32_t *Hash = (uint32_t*)&g_hash[8 * hashPosition];
hashState state;
#pragma unroll 40
for(int i=0;i<40;i++) state.chainv[i] = c_IV[i];
#pragma unroll 8
for(int i=0;i<8;i++) state.buffer[i] = 0;
Update512(&state, (BitSequence*)Hash);
finalization512(&state, (uint32_t*)Hash);
}
}
// Setup-Funktionen
__host__ void x11_luffa512_cpu_init(int thr_id, int threads)
{
cudaMemcpyToSymbol(c_IV, h_IV, sizeof(h_IV), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(c_CNS, h_CNS, sizeof(h_CNS), 0, cudaMemcpyHostToDevice);
}
__host__ void x11_luffa512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order)
{
const int threadsperblock = 256;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
// Größe des dynamischen Shared Memory Bereichs
size_t shared_size = 0;
x11_luffa512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector);
MyStreamSynchronize(NULL, order, thr_id);
}