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bump to revision 0.7

master
Christian Buchner 11 years ago
parent
commit
433d653723
  1. 255
      JHA/cuda_jha_compactionTest.cu
  2. 12
      JHA/cuda_jha_keccak512.cu
  3. 167
      JHA/jackpotcoin.cu
  4. 9
      Makefile.am
  5. 6
      README.txt
  6. 5
      ccminer.vcxproj
  7. 15
      ccminer.vcxproj.filters
  8. 2
      configure.ac
  9. 2
      cpu-miner.c
  10. 4
      cpuminer-config.h
  11. 4
      cuda_groestlcoin.cu
  12. 356
      quark/cuda_jh512.cu
  13. 482
      quark/cuda_quark_blake512.cu
  14. 397
      quark/cuda_quark_groestl512.cu
  15. 450
      quark/cuda_skein512.cu

255
JHA/cuda_jha_compactionTest.cu

@ -0,0 +1,255 @@ @@ -0,0 +1,255 @@
#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include "sm_30_intrinsics.h"
#include <stdio.h>
#include <memory.h>
#include <stdint.h>
// aus cpu-miner.c
extern int device_map[8];
// diese Struktur wird in der Init Funktion angefordert
static cudaDeviceProp props[8];
static uint32_t *d_tempBranch1Nonces[8];
static uint32_t *d_tempBranch2Nonces[8];
static size_t *d_numValid[8];
static size_t *h_numValid[8];
static uint32_t *d_partSum1[8], *d_partSum2[8]; // 2x partielle summen
static uint32_t *d_validTemp1[8], *d_validTemp2[8];
// Zwischenspeicher
static uint32_t *d_tempBranchAllNonces[8];
// aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
// Setup-Funktionen
__host__ void jackpot_compactTest_cpu_init(int thr_id, int threads)
{
cudaGetDeviceProperties(&props[thr_id], device_map[thr_id]);
// wir brauchen auch Speicherplatz auf dem Device
cudaMalloc(&d_tempBranchAllNonces[thr_id], sizeof(uint32_t) * threads);
cudaMalloc(&d_tempBranch1Nonces[thr_id], sizeof(uint32_t) * threads);
cudaMalloc(&d_tempBranch2Nonces[thr_id], sizeof(uint32_t) * threads);
cudaMalloc(&d_numValid[thr_id], 2*sizeof(size_t));
cudaMallocHost(&h_numValid[thr_id], 2*sizeof(size_t));
uint32_t s1;
s1 = threads / 256;
cudaMalloc(&d_partSum1[thr_id], sizeof(uint32_t) * s1); // BLOCKSIZE (Threads/Block)
cudaMalloc(&d_partSum2[thr_id], sizeof(uint32_t) * s1); // BLOCKSIZE (Threads/Block)
cudaMalloc(&d_validTemp1[thr_id], sizeof(uint32_t) * threads); // BLOCKSIZE (Threads/Block)
cudaMalloc(&d_validTemp2[thr_id], sizeof(uint32_t) * threads); // BLOCKSIZE (Threads/Block)
}
// Die Testfunktion (zum Erstellen der TestMap)
__global__ void jackpot_compactTest_gpu_TEST_64(int threads, uint32_t startNounce, uint32_t *inpHashes, uint32_t *d_noncesFull,
uint32_t *d_nonces1, uint32_t *d_nonces2,
uint32_t *d_validT1, uint32_t *d_validT2)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
// bestimme den aktuellen Zähler
uint32_t nounce = startNounce + thread;
uint32_t *inpHash = &inpHashes[16 * thread];
uint32_t tmp = inpHash[0] & 0x01;
uint32_t val1 = (tmp == 1);
uint32_t val2 = (tmp == 0);
d_nonces1[thread] = val1;
d_validT1[thread] = val1;
d_nonces2[thread] = val2;
d_validT2[thread] = val2;
d_noncesFull[thread] = nounce;
}
}
// Die Summenfunktion (vom NVIDIA SDK)
__global__ void jackpot_compactTest_gpu_SCAN(uint32_t *data, int width, uint32_t *partial_sums=NULL)
{
extern __shared__ uint32_t sums[];
int id = ((blockIdx.x * blockDim.x) + threadIdx.x);
//int lane_id = id % warpSize;
int lane_id = id % width;
// determine a warp_id within a block
//int warp_id = threadIdx.x / warpSize;
int warp_id = threadIdx.x / width;
// Below is the basic structure of using a shfl instruction
// for a scan.
// Record "value" as a variable - we accumulate it along the way
uint32_t value = data[id];
// Now accumulate in log steps up the chain
// compute sums, with another thread's value who is
// distance delta away (i). Note
// those threads where the thread 'i' away would have
// been out of bounds of the warp are unaffected. This
// creates the scan sum.
#pragma unroll
for (int i=1; i<=width; i*=2)
{
uint32_t n = __shfl_up((int)value, i, width);
if (lane_id >= i) value += n;
}
// value now holds the scan value for the individual thread
// next sum the largest values for each warp
// write the sum of the warp to smem
//if (threadIdx.x % warpSize == warpSize-1)
if (threadIdx.x % width == width-1)
{
sums[warp_id] = value;
}
__syncthreads();
//
// scan sum the warp sums
// the same shfl scan operation, but performed on warp sums
//
if (warp_id == 0)
{
uint32_t warp_sum = sums[lane_id];
for (int i=1; i<=width; i*=2)
{
uint32_t n = __shfl_up((int)warp_sum, i, width);
if (lane_id >= i) warp_sum += n;
}
sums[lane_id] = warp_sum;
}
__syncthreads();
// perform a uniform add across warps in the block
// read neighbouring warp's sum and add it to threads value
uint32_t blockSum = 0;
if (warp_id > 0)
{
blockSum = sums[warp_id-1];
}
value += blockSum;
// Now write out our result
data[id] = value;
// last thread has sum, write write out the block's sum
if (partial_sums != NULL && threadIdx.x == blockDim.x-1)
{
partial_sums[blockIdx.x] = value;
}
}
// Uniform add: add partial sums array
__global__ void jackpot_compactTest_gpu_ADD(uint32_t *data, uint32_t *partial_sums, int len)
{
__shared__ uint32_t buf;
int id = ((blockIdx.x * blockDim.x) + threadIdx.x);
if (id > len) return;
if (threadIdx.x == 0)
{
buf = partial_sums[blockIdx.x];
}
__syncthreads();
data[id] += buf;
}
// Der Scatter
__global__ void jackpot_compactTest_gpu_SCATTER(uint32_t *data, uint32_t *valid, uint32_t *sum, uint32_t *outp)
{
int id = ((blockIdx.x * blockDim.x) + threadIdx.x);
if( valid[id] )
{
int idx = sum[id];
if(idx > 0)
outp[idx-1] = data[id];
}
}
////// ACHTUNG: Diese funktion geht aktuell nur mit threads > 65536 (Am besten 256 * 1024 oder 256*2048)
__host__ void jackpot_compactTest_cpu_dualCompaction(int thr_id, int threads, size_t *nrm,
uint32_t *d_nonces1, uint32_t *d_nonces2)
{
// threadsPerBlock ausrechnen
int blockSize = 256;
int thr1 = threads / blockSize;
int thr2 = threads / (blockSize*blockSize);
// 1
jackpot_compactTest_gpu_SCAN<<<thr1,blockSize, 8*sizeof(uint32_t)>>>(d_tempBranch1Nonces[thr_id], 32, d_partSum1[thr_id]);
jackpot_compactTest_gpu_SCAN<<<thr2,blockSize, 8*sizeof(uint32_t)>>>(d_partSum1[thr_id], 32, d_partSum2[thr_id]);
jackpot_compactTest_gpu_SCAN<<<1, thr2, 8*sizeof(uint32_t)>>>(d_partSum2[thr_id], (thr2>32) ? 32 : thr2);
cudaStreamSynchronize(NULL);
cudaMemcpy(&nrm[0], &(d_partSum2[thr_id])[thr2-1], sizeof(uint32_t), cudaMemcpyDeviceToHost);
jackpot_compactTest_gpu_ADD<<<thr2-1, blockSize>>>(d_partSum1[thr_id]+blockSize, d_partSum2[thr_id], blockSize*thr2);
jackpot_compactTest_gpu_ADD<<<thr1-1, blockSize>>>(d_tempBranch1Nonces[thr_id]+blockSize, d_partSum1[thr_id], threads);
// 2
jackpot_compactTest_gpu_SCAN<<<thr1,blockSize, 8*sizeof(uint32_t)>>>(d_tempBranch2Nonces[thr_id], 32, d_partSum1[thr_id]);
jackpot_compactTest_gpu_SCAN<<<thr2,blockSize, 8*sizeof(uint32_t)>>>(d_partSum1[thr_id], 32, d_partSum2[thr_id]);
jackpot_compactTest_gpu_SCAN<<<1, thr2, 8*sizeof(uint32_t)>>>(d_partSum2[thr_id], (thr2>32) ? 32 : thr2);
cudaStreamSynchronize(NULL);
cudaMemcpy(&nrm[1], &(d_partSum2[thr_id])[thr2-1], sizeof(uint32_t), cudaMemcpyDeviceToHost);
jackpot_compactTest_gpu_ADD<<<thr2-1, blockSize>>>(d_partSum1[thr_id]+blockSize, d_partSum2[thr_id], blockSize*thr2);
jackpot_compactTest_gpu_ADD<<<thr1-1, blockSize>>>(d_tempBranch2Nonces[thr_id]+blockSize, d_partSum1[thr_id], threads);
// Hier ist noch eine Besonderheit: in d_tempBranch1Nonces sind die element von 1...nrm1 die Interessanten
// Schritt 3: Scatter
jackpot_compactTest_gpu_SCATTER<<<thr1,blockSize,0>>>(d_tempBranchAllNonces[thr_id], d_validTemp1[thr_id], d_tempBranch1Nonces[thr_id], d_nonces1);
jackpot_compactTest_gpu_SCATTER<<<thr1,blockSize,0>>>(d_tempBranchAllNonces[thr_id], d_validTemp2[thr_id], d_tempBranch2Nonces[thr_id], d_nonces2);
cudaStreamSynchronize(NULL);
}
__host__ void jackpot_compactTest_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *inpHashes,
uint32_t *d_nonces1, size_t *nrm1,
uint32_t *d_nonces2, size_t *nrm2,
int order)
{
// Compute 3.x und 5.x Geräte am besten mit 768 Threads ansteuern,
// alle anderen mit 512 Threads.
//int threadsperblock = (props[thr_id].major >= 3) ? 768 : 512;
int threadsperblock = 256;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
size_t shared_size = 0;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
// Schritt 1: Prüfen der Bedingung und Speicherung in d_tempBranch1/2Nonces
jackpot_compactTest_gpu_TEST_64<<<grid, block, shared_size>>>(threads, startNounce, inpHashes, d_tempBranchAllNonces[thr_id],
d_tempBranch1Nonces[thr_id], d_tempBranch2Nonces[thr_id],
d_validTemp1[thr_id], d_validTemp2[thr_id]);
// Strategisches Sleep Kommando zur Senkung der CPU Last
jackpot_compactTest_cpu_dualCompaction(thr_id, threads,
h_numValid[thr_id], d_nonces1, d_nonces2);
cudaStreamSynchronize(NULL); // Das original braucht zwar etwas CPU-Last, ist an dieser Stelle aber evtl besser
*nrm1 = h_numValid[thr_id][0];
*nrm2 = h_numValid[thr_id][1];
}

12
JHA/cuda_jha_keccak512.cu

@ -1,3 +1,5 @@ @@ -1,3 +1,5 @@
#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
@ -132,7 +134,7 @@ keccak_block(uint64_t *s, const uint32_t *in, const uint64_t *keccak_round_const @@ -132,7 +134,7 @@ keccak_block(uint64_t *s, const uint32_t *in, const uint64_t *keccak_round_const
}
}
__global__ void jackpot_keccak512_gpu_hash_88(int threads, uint32_t startNounce, uint64_t *g_hash)
__global__ void jackpot_keccak512_gpu_hash(int threads, uint32_t startNounce, uint64_t *g_hash)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
@ -518,9 +520,9 @@ void KeccakF( tKeccakLane * state, const tKeccakLane *in, int laneCount ) @@ -518,9 +520,9 @@ void KeccakF( tKeccakLane * state, const tKeccakLane *in, int laneCount )
}
}
__host__ void jackpot_keccak512_cpu_setBlock_88(void *pdata)
// inlen kann 72...143 betragen
__host__ void jackpot_keccak512_cpu_setBlock(void *pdata, size_t inlen)
{
unsigned long long inlen = 88;
const unsigned char *in = (const unsigned char*)pdata;
tKeccakLane state[5 * 5];
@ -554,7 +556,7 @@ __host__ void jackpot_keccak512_cpu_setBlock_88(void *pdata) @@ -554,7 +556,7 @@ __host__ void jackpot_keccak512_cpu_setBlock_88(void *pdata)
0, cudaMemcpyHostToDevice);
}
__host__ void jackpot_keccak512_cpu_hash_88(int thr_id, int threads, uint32_t startNounce, uint32_t *d_hash, int order)
__host__ void jackpot_keccak512_cpu_hash(int thr_id, int threads, uint32_t startNounce, uint32_t *d_hash, int order)
{
const int threadsperblock = 256;
@ -567,6 +569,6 @@ __host__ void jackpot_keccak512_cpu_hash_88(int thr_id, int threads, uint32_t st @@ -567,6 +569,6 @@ __host__ void jackpot_keccak512_cpu_hash_88(int thr_id, int threads, uint32_t st
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
jackpot_keccak512_gpu_hash_88<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash);
jackpot_keccak512_gpu_hash<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash);
MyStreamSynchronize(NULL, order, thr_id);
}

167
JHA/jackpotcoin.cu

@ -6,9 +6,9 @@ extern "C" @@ -6,9 +6,9 @@ extern "C"
#include "sph/sph_groestl.h"
#include "sph/sph_jh.h"
#include "sph/sph_skein.h"
#include "miner.h"
}
#include "miner.h"
#include <stdint.h>
// aus cpu-miner.c
@ -19,13 +19,36 @@ extern bool opt_benchmark; @@ -19,13 +19,36 @@ extern bool opt_benchmark;
static uint32_t *d_hash[8];
extern void jackpot_keccak512_cpu_init(int thr_id, int threads);
extern void jackpot_keccak512_cpu_setBlock_88(void *pdata);
extern void jackpot_keccak512_cpu_hash_88(int thr_id, int threads, uint32_t startNounce, uint32_t *d_hash, int order);
extern void jackpot_keccak512_cpu_setBlock(void *pdata, size_t inlen);
extern void jackpot_keccak512_cpu_hash(int thr_id, int threads, uint32_t startNounce, uint32_t *d_hash, int order);
extern void quark_blake512_cpu_init(int thr_id, int threads);
extern void quark_blake512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order);
extern void quark_groestl512_cpu_init(int thr_id, int threads);
extern void quark_groestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order);
extern void quark_jh512_cpu_init(int thr_id, int threads);
extern void quark_jh512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order);
extern void quark_skein512_cpu_init(int thr_id, int threads);
extern void quark_skein512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order);
extern void quark_check_cpu_init(int thr_id, int threads);
extern void quark_check_cpu_setTarget(const void *ptarget);
extern uint32_t quark_check_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_inputHash, int order);
extern void jackpot_compactTest_cpu_init(int thr_id, int threads);
extern void jackpot_compactTest_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *inpHashes,
uint32_t *d_nonces1, size_t *nrm1,
uint32_t *d_nonces2, size_t *nrm2,
int order);
// Speicher zur Generierung der Noncevektoren für die bedingten Hashes
static uint32_t *d_jackpotNonces[8];
static uint32_t *d_branch1Nonces[8];
static uint32_t *d_branch2Nonces[8];
// Original jackpothash Funktion aus einem miner Quelltext
inline unsigned int jackpothash(void *state, const void *input)
{
@ -38,55 +61,38 @@ inline unsigned int jackpothash(void *state, const void *input) @@ -38,55 +61,38 @@ inline unsigned int jackpothash(void *state, const void *input)
uint32_t hash[16];
sph_keccak512_init(&ctx_keccak);
sph_keccak512 (&ctx_keccak, input, 88);
sph_keccak512 (&ctx_keccak, input, 80);
sph_keccak512_close(&ctx_keccak, hash);
unsigned int round_mask = (
(unsigned int)(((unsigned char *)input)[84]) << 0 |
(unsigned int)(((unsigned char *)input)[85]) << 8 |
(unsigned int)(((unsigned char *)input)[86]) << 16 |
(unsigned int)(((unsigned char *)input)[87]) << 24 );
unsigned int round_max = hash[0] & round_mask;
unsigned int round;
for (round = 0; round < round_max; round++) {
switch (hash[0] & 3) {
case 0:
sph_blake512_init(&ctx_blake);
sph_blake512 (&ctx_blake, hash, 64);
sph_blake512_close(&ctx_blake, hash);
break;
case 1:
sph_groestl512_init(&ctx_groestl);
sph_groestl512 (&ctx_groestl, hash, 64);
sph_groestl512_close(&ctx_groestl, hash);
break;
case 2:
sph_jh512_init(&ctx_jh);
sph_jh512 (&ctx_jh, hash, 64);
sph_jh512_close(&ctx_jh, hash);
break;
case 3:
sph_skein512_init(&ctx_skein);
sph_skein512 (&ctx_skein, hash, 64);
sph_skein512_close(&ctx_skein, hash);
break;
for (round = 0; round < 3; round++) {
if (hash[0] & 0x01) {
sph_groestl512_init(&ctx_groestl);
sph_groestl512 (&ctx_groestl, (&hash), 64);
sph_groestl512_close(&ctx_groestl, (&hash));
}
else {
sph_skein512_init(&ctx_skein);
sph_skein512 (&ctx_skein, (&hash), 64);
sph_skein512_close(&ctx_skein, (&hash));
}
if (hash[0] & 0x01) {
sph_blake512_init(&ctx_blake);
sph_blake512 (&ctx_blake, (&hash), 64);
sph_blake512_close(&ctx_blake, (&hash));
}
else {
sph_jh512_init(&ctx_jh);
sph_jh512 (&ctx_jh, (&hash), 64);
sph_jh512_close(&ctx_jh, (&hash));
}
}
memcpy(state, hash, 32);
return round_max;
return round;
}
static int bit_population(uint32_t n){
int c =0;
while(n){
c += n&1;
n = n>>1;
}
return c;
}
extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata,
const uint32_t *ptarget, uint32_t max_nonce,
unsigned long *hashes_done)
@ -94,10 +100,8 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata, @@ -94,10 +100,8 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata,
const uint32_t first_nonce = pdata[19];
// TODO: entfernen für eine Release! Ist nur zum Testen!
if (opt_benchmark) {
((uint32_t*)ptarget)[7] = 0x00000f;
((uint32_t*)pdata)[21] = 0x07000000; // round_mask von 7 vorgeben
}
if (opt_benchmark)
((uint32_t*)ptarget)[7] = 0x0000ff;
const uint32_t Htarg = ptarget[7];
@ -111,7 +115,15 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata, @@ -111,7 +115,15 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata,
// Konstanten kopieren, Speicher belegen
cudaMalloc(&d_hash[thr_id], 16 * sizeof(uint32_t) * throughput);
jackpot_keccak512_cpu_init(thr_id, throughput);
jackpot_compactTest_cpu_init(thr_id, throughput);
quark_blake512_cpu_init(thr_id, throughput);
quark_groestl512_cpu_init(thr_id, throughput);
quark_jh512_cpu_init(thr_id, throughput);
quark_skein512_cpu_init(thr_id, throughput);
quark_check_cpu_init(thr_id, throughput);
cudaMalloc(&d_jackpotNonces[thr_id], sizeof(uint32_t)*throughput);
cudaMalloc(&d_branch1Nonces[thr_id], sizeof(uint32_t)*throughput);
cudaMalloc(&d_branch2Nonces[thr_id], sizeof(uint32_t)*throughput);
init[thr_id] = true;
}
@ -119,27 +131,41 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata, @@ -119,27 +131,41 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata,
for (int k=0; k < 22; k++)
be32enc(&endiandata[k], ((uint32_t*)pdata)[k]);
unsigned int round_mask = (
(unsigned int)(((unsigned char *)endiandata)[84]) << 0 |
(unsigned int)(((unsigned char *)endiandata)[85]) << 8 |
(unsigned int)(((unsigned char *)endiandata)[86]) << 16 |
(unsigned int)(((unsigned char *)endiandata)[87]) << 24 );
// Zählen wie viele Bits in round_mask gesetzt sind
int bitcount = bit_population(round_mask);
jackpot_keccak512_cpu_setBlock_88((void*)endiandata);
jackpot_keccak512_cpu_setBlock((void*)endiandata, 80);
quark_check_cpu_setTarget(ptarget);
do {
int order = 0;
// erstes Blake512 Hash mit CUDA
jackpot_keccak512_cpu_hash_88(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
// erstes Keccak512 Hash mit CUDA
jackpot_keccak512_cpu_hash(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
for (int round=0; round < 3; round++)
{
size_t nrm1, nrm2;
// jackpotNonces in branch1/2 aufsplitten gemäss if (hash[0] & 0x01)
jackpot_compactTest_cpu_hash_64(thr_id, throughput, pdata[19], d_hash[thr_id],
d_branch1Nonces[thr_id], &nrm1,
d_branch2Nonces[thr_id], &nrm2,
order++);
if (nrm1+nrm2 == throughput) {
quark_groestl512_cpu_hash_64(thr_id, nrm1, pdata[19], d_branch1Nonces[thr_id], d_hash[thr_id], order++);
quark_skein512_cpu_hash_64(thr_id, nrm2, pdata[19], d_branch2Nonces[thr_id], d_hash[thr_id], order++);
}
// jackpotNonces in branch1/2 aufsplitten gemäss if (hash[0] & 0x01)
jackpot_compactTest_cpu_hash_64(thr_id, throughput, pdata[19], d_hash[thr_id],
d_branch1Nonces[thr_id], &nrm1,
d_branch2Nonces[thr_id], &nrm2,
order++);
// TODO: hier fehlen jetzt natürlich noch die anderen Hashrunden.
// bei round_mask=7 haben wir eine 1:8 Chance, dass das Hash dennoch
// die Kriterien erfüllt wenn hash[0] & round_mask zufällig 0 ist.
if (nrm1+nrm2 == throughput) {
quark_blake512_cpu_hash_64(thr_id, nrm1, pdata[19], d_branch1Nonces[thr_id], d_hash[thr_id], order++);
quark_jh512_cpu_hash_64(thr_id, nrm2, pdata[19], d_branch2Nonces[thr_id], d_hash[thr_id], order++);
}
}
// Scan nach Gewinner Hashes auf der GPU
uint32_t foundNonce = quark_check_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);
@ -148,19 +174,16 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata, @@ -148,19 +174,16 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata,
uint32_t vhash64[8];
be32enc(&endiandata[19], foundNonce);
// diese jackpothash Funktion gibt die Zahl der zusätzlichen Runden zurück
// diese jackpothash Funktion gibt die Zahl der Runden zurück
unsigned int rounds = jackpothash(vhash64, endiandata);
// wir akzeptieren nur solche Hashes wo ausschliesslich Keccak verwendet wurde
if (rounds == 0) {
if ((vhash64[7]<=Htarg) && fulltest(vhash64, ptarget)) {
if ((vhash64[7]<=Htarg) && fulltest(vhash64, ptarget)) {
pdata[19] = foundNonce;
*hashes_done = (foundNonce - first_nonce + 1) / (1 << bitcount);
return 1;
} else {
applog(LOG_INFO, "GPU #%d: result for nonce $%08X does not validate on CPU (%d rounds)!", thr_id, foundNonce, rounds);
}
pdata[19] = foundNonce;
*hashes_done = (foundNonce - first_nonce + 1);
return 1;
} else {
applog(LOG_INFO, "GPU #%d: result for nonce $%08X does not validate on CPU (%d rounds)!", thr_id, foundNonce, rounds);
}
}
@ -168,6 +191,6 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata, @@ -168,6 +191,6 @@ extern "C" int scanhash_jackpot(int thr_id, uint32_t *pdata,
} while (pdata[19] < max_nonce && !work_restart[thr_id].restart);
*hashes_done = (pdata[19] - first_nonce + 1) / (1 << bitcount);
*hashes_done = (pdata[19] - first_nonce + 1);
return 0;
}

9
Makefile.am

@ -16,8 +16,8 @@ bin_PROGRAMS = ccminer @@ -16,8 +16,8 @@ bin_PROGRAMS = ccminer
ccminer_SOURCES = elist.h miner.h compat.h \
compat/inttypes.h compat/stdbool.h compat/unistd.h \
compat/sys/time.h compat/getopt/getopt.h \
cpu-miner.c util.c sph/blake.c sph/groestl.c sph/keccak.c hefty1.c scrypt.c sha2.c \
sph/sph_blake.h sph/sph_groestl.h sph/sph_keccak.h sph/sph_types.h \
cpu-miner.c util.c sph/blake.c sph/groestl.c sph/jh.c sph/keccak.c sph/skein.c hefty1.c scrypt.c sha2.c \
sph/sph_blake.h sph/sph_groestl.h sph/sph_jh.h sph/sph_keccak.h sph/sph_skein.h sph/sph_types.h \
heavy.cu \
cuda_blake512.cu cuda_blake512.h \
cuda_combine.cu cuda_combine.h \
@ -27,8 +27,9 @@ ccminer_SOURCES = elist.h miner.h compat.h \ @@ -27,8 +27,9 @@ ccminer_SOURCES = elist.h miner.h compat.h \
cuda_sha256.cu cuda_sha256.h \
fuguecoin.cpp cuda_fugue256.cu sph/fugue.c sph/sph_fugue.h uint256.h \
groestlcoin.cpp cuda_groestlcoin.cu cuda_groestlcoin.h \
JHA/jackpotcoin.cu JHA/cuda_jha_keccak512.cu sph/jh.c sph/skein.c \
sph/sph_jh.h sph/sph_skein.h quark/cuda_quark_checkhash.cu \
JHA/jackpotcoin.cu JHA/cuda_jha_keccak512.cu \
JHA/cuda_jha_compactionTest.cu quark/cuda_quark_checkhash.cu \
quark/cuda_jh512.cu quark/cuda_quark_blake512.cu quark/cuda_quark_groestl512.cu quark/cuda_skein512.cu \
myriadgroestl.cpp cuda_myriadgroestl.cu
ccminer_LDFLAGS = $(PTHREAD_FLAGS) @CUDA_LDFLAGS@

6
README.txt

@ -1,5 +1,5 @@ @@ -1,5 +1,5 @@
ccMiner release 0.6 (April 27th 2014) - "Jackpot"
ccMiner release 0.7 (May 01th 2014) - "Jackpot II"
-------------------------------------------------------------
***************************************************************
@ -116,6 +116,10 @@ from your old clunkers. @@ -116,6 +116,10 @@ from your old clunkers.
>>> RELEASE HISTORY <<<
May 1st 2014 adapt the Jackpot algorithms to changes made by the
coin developers. We keep our unique nVidia advantage
because we have a way to break up the divergence.
April, 27 2014 this release adds Myriad-Groestl and Jackpot Coin.
we apply an optimization to Jackpot that turns this
into a Keccak-only CUDA coin ;) Jackpot is tested with

5
ccminer.vcxproj

@ -305,9 +305,14 @@ copy "$(CudaToolkitBinDir)\cudart*.dll" "$(OutDir)"</Command> @@ -305,9 +305,14 @@ copy "$(CudaToolkitBinDir)\cudart*.dll" "$(OutDir)"</Command>
<CudaCompile Include="cuda_myriadgroestl.cu" />
<CudaCompile Include="cuda_sha256.cu" />
<CudaCompile Include="heavy.cu" />
<CudaCompile Include="JHA\cuda_jha_compactionTest.cu" />
<CudaCompile Include="JHA\cuda_jha_keccak512.cu" />
<CudaCompile Include="JHA\jackpotcoin.cu" />
<CudaCompile Include="quark\cuda_jh512.cu" />
<CudaCompile Include="quark\cuda_quark_blake512.cu" />
<CudaCompile Include="quark\cuda_quark_checkhash.cu" />
<CudaCompile Include="quark\cuda_quark_groestl512.cu" />
<CudaCompile Include="quark\cuda_skein512.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">

15
ccminer.vcxproj.filters

@ -286,5 +286,20 @@ @@ -286,5 +286,20 @@
<CudaCompile Include="cuda_myriadgroestl.cu">
<Filter>Source Files\CUDA</Filter>
</CudaCompile>
<CudaCompile Include="JHA\cuda_jha_compactionTest.cu">
<Filter>Source Files\CUDA\JHA</Filter>
</CudaCompile>
<CudaCompile Include="quark\cuda_jh512.cu">
<Filter>Source Files\CUDA\quark</Filter>
</CudaCompile>
<CudaCompile Include="quark\cuda_quark_blake512.cu">
<Filter>Source Files\CUDA\quark</Filter>
</CudaCompile>
<CudaCompile Include="quark\cuda_quark_groestl512.cu">
<Filter>Source Files\CUDA\quark</Filter>
</CudaCompile>
<CudaCompile Include="quark\cuda_skein512.cu">
<Filter>Source Files\CUDA\quark</Filter>
</CudaCompile>
</ItemGroup>
</Project>

2
configure.ac

@ -1,4 +1,4 @@ @@ -1,4 +1,4 @@
AC_INIT([ccminer], [2014.04.27])
AC_INIT([ccminer], [2014.05.01])
AC_PREREQ([2.59c])
AC_CANONICAL_SYSTEM

2
cpu-miner.c

@ -1404,7 +1404,7 @@ static void signal_handler(int sig) @@ -1404,7 +1404,7 @@ static void signal_handler(int sig)
}
#endif
#define PROGRAM_VERSION "0.6"
#define PROGRAM_VERSION "0.7"
int main(int argc, char *argv[])
{
struct thr_info *thr;

4
cpuminer-config.h

@ -152,7 +152,7 @@ @@ -152,7 +152,7 @@
#define PACKAGE_NAME "ccminer"
/* Define to the full name and version of this package. */
#define PACKAGE_STRING "ccminer 2014.04.27"
#define PACKAGE_STRING "ccminer 2014.05.01"
/* Define to the one symbol short name of this package. */
#undef PACKAGE_TARNAME
@ -161,7 +161,7 @@ @@ -161,7 +161,7 @@
#undef PACKAGE_URL
/* Define to the version of this package. */
#define PACKAGE_VERSION "2014.04.27"
#define PACKAGE_VERSION "2014.05.01"
/* If using the C implementation of alloca, define if you know the
direction of stack growth for your system; otherwise it will be

4
cuda_groestlcoin.cu

@ -8,7 +8,7 @@ @@ -8,7 +8,7 @@
#include <memory.h>
// it's unfortunate that this is a compile time constant.
#define MAXWELL_OR_FERMI 0
#define MAXWELL_OR_FERMI 1
// aus cpu-miner.c
extern int device_map[8];
@ -50,7 +50,7 @@ __constant__ uint32_t groestlcoin_gpu_msg[32]; @@ -50,7 +50,7 @@ __constant__ uint32_t groestlcoin_gpu_msg[32];
#define B32_3(x) __byte_perm(x, 0, 0x4443)
//((x) >> 24)
#if MAXWELL_OR_FEMRI
#if MAXWELL_OR_FERMI
#define USE_SHARED 1
// Maxwell and Fermi cards get the best speed with SHARED access it seems.
#if USE_SHARED

356
quark/cuda_jh512.cu

@ -0,0 +1,356 @@ @@ -0,0 +1,356 @@
#include <stdint.h>
// aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
typedef struct {
uint32_t x[8][4]; /*the 1024-bit state, ( x[i][0] || x[i][1] || x[i][2] || x[i][3] ) is the ith row of the state in the pseudocode*/
uint32_t buffer[16]; /*the 512-bit message block to be hashed;*/
} hashState;
/*42 round constants, each round constant is 32-byte (256-bit)*/
__constant__ uint32_t c_INIT_bitslice[8][4];
__constant__ unsigned char c_E8_bitslice_roundconstant[42][32];
const uint32_t h_INIT_bitslice[8][4] = {
{ 0x964bd16f, 0x17aa003e, 0x052e6a63, 0x43d5157a},
{ 0x8d5e228a, 0x0bef970c, 0x591234e9, 0x61c3b3f2},
{ 0xc1a01d89, 0x1e806f53, 0x6b05a92a, 0x806d2bea},
{ 0xdbcc8e58, 0xa6ba7520, 0x763a0fa9, 0xf73bf8ba},
{ 0x05e66901, 0x694ae341, 0x8e8ab546, 0x5ae66f2e},
{ 0xd0a74710, 0x243c84c1, 0xb1716e3b, 0x99c15a2d},
{ 0xecf657cf, 0x56f8b19d, 0x7c8806a7, 0x56b11657},
{ 0xdffcc2e3, 0xfb1785e6, 0x78465a54, 0x4bdd8ccc} };
const unsigned char h_E8_bitslice_roundconstant[42][32]={
{0x72,0xd5,0xde,0xa2,0xdf,0x15,0xf8,0x67,0x7b,0x84,0x15,0xa,0xb7,0x23,0x15,0x57,0x81,0xab,0xd6,0x90,0x4d,0x5a,0x87,0xf6,0x4e,0x9f,0x4f,0xc5,0xc3,0xd1,0x2b,0x40},
{0xea,0x98,0x3a,0xe0,0x5c,0x45,0xfa,0x9c,0x3,0xc5,0xd2,0x99,0x66,0xb2,0x99,0x9a,0x66,0x2,0x96,0xb4,0xf2,0xbb,0x53,0x8a,0xb5,0x56,0x14,0x1a,0x88,0xdb,0xa2,0x31},
{0x3,0xa3,0x5a,0x5c,0x9a,0x19,0xe,0xdb,0x40,0x3f,0xb2,0xa,0x87,0xc1,0x44,0x10,0x1c,0x5,0x19,0x80,0x84,0x9e,0x95,0x1d,0x6f,0x33,0xeb,0xad,0x5e,0xe7,0xcd,0xdc},
{0x10,0xba,0x13,0x92,0x2,0xbf,0x6b,0x41,0xdc,0x78,0x65,0x15,0xf7,0xbb,0x27,0xd0,0xa,0x2c,0x81,0x39,0x37,0xaa,0x78,0x50,0x3f,0x1a,0xbf,0xd2,0x41,0x0,0x91,0xd3},
{0x42,0x2d,0x5a,0xd,0xf6,0xcc,0x7e,0x90,0xdd,0x62,0x9f,0x9c,0x92,0xc0,0x97,0xce,0x18,0x5c,0xa7,0xb,0xc7,0x2b,0x44,0xac,0xd1,0xdf,0x65,0xd6,0x63,0xc6,0xfc,0x23},
{0x97,0x6e,0x6c,0x3,0x9e,0xe0,0xb8,0x1a,0x21,0x5,0x45,0x7e,0x44,0x6c,0xec,0xa8,0xee,0xf1,0x3,0xbb,0x5d,0x8e,0x61,0xfa,0xfd,0x96,0x97,0xb2,0x94,0x83,0x81,0x97},
{0x4a,0x8e,0x85,0x37,0xdb,0x3,0x30,0x2f,0x2a,0x67,0x8d,0x2d,0xfb,0x9f,0x6a,0x95,0x8a,0xfe,0x73,0x81,0xf8,0xb8,0x69,0x6c,0x8a,0xc7,0x72,0x46,0xc0,0x7f,0x42,0x14},
{0xc5,0xf4,0x15,0x8f,0xbd,0xc7,0x5e,0xc4,0x75,0x44,0x6f,0xa7,0x8f,0x11,0xbb,0x80,0x52,0xde,0x75,0xb7,0xae,0xe4,0x88,0xbc,0x82,0xb8,0x0,0x1e,0x98,0xa6,0xa3,0xf4},
{0x8e,0xf4,0x8f,0x33,0xa9,0xa3,0x63,0x15,0xaa,0x5f,0x56,0x24,0xd5,0xb7,0xf9,0x89,0xb6,0xf1,0xed,0x20,0x7c,0x5a,0xe0,0xfd,0x36,0xca,0xe9,0x5a,0x6,0x42,0x2c,0x36},
{0xce,0x29,0x35,0x43,0x4e,0xfe,0x98,0x3d,0x53,0x3a,0xf9,0x74,0x73,0x9a,0x4b,0xa7,0xd0,0xf5,0x1f,0x59,0x6f,0x4e,0x81,0x86,0xe,0x9d,0xad,0x81,0xaf,0xd8,0x5a,0x9f},
{0xa7,0x5,0x6,0x67,0xee,0x34,0x62,0x6a,0x8b,0xb,0x28,0xbe,0x6e,0xb9,0x17,0x27,0x47,0x74,0x7,0x26,0xc6,0x80,0x10,0x3f,0xe0,0xa0,0x7e,0x6f,0xc6,0x7e,0x48,0x7b},
{0xd,0x55,0xa,0xa5,0x4a,0xf8,0xa4,0xc0,0x91,0xe3,0xe7,0x9f,0x97,0x8e,0xf1,0x9e,0x86,0x76,0x72,0x81,0x50,0x60,0x8d,0xd4,0x7e,0x9e,0x5a,0x41,0xf3,0xe5,0xb0,0x62},
{0xfc,0x9f,0x1f,0xec,0x40,0x54,0x20,0x7a,0xe3,0xe4,0x1a,0x0,0xce,0xf4,0xc9,0x84,0x4f,0xd7,0x94,0xf5,0x9d,0xfa,0x95,0xd8,0x55,0x2e,0x7e,0x11,0x24,0xc3,0x54,0xa5},
{0x5b,0xdf,0x72,0x28,0xbd,0xfe,0x6e,0x28,0x78,0xf5,0x7f,0xe2,0xf,0xa5,0xc4,0xb2,0x5,0x89,0x7c,0xef,0xee,0x49,0xd3,0x2e,0x44,0x7e,0x93,0x85,0xeb,0x28,0x59,0x7f},
{0x70,0x5f,0x69,0x37,0xb3,0x24,0x31,0x4a,0x5e,0x86,0x28,0xf1,0x1d,0xd6,0xe4,0x65,0xc7,0x1b,0x77,0x4,0x51,0xb9,0x20,0xe7,0x74,0xfe,0x43,0xe8,0x23,0xd4,0x87,0x8a},
{0x7d,0x29,0xe8,0xa3,0x92,0x76,0x94,0xf2,0xdd,0xcb,0x7a,0x9,0x9b,0x30,0xd9,0xc1,0x1d,0x1b,0x30,0xfb,0x5b,0xdc,0x1b,0xe0,0xda,0x24,0x49,0x4f,0xf2,0x9c,0x82,0xbf},
{0xa4,0xe7,0xba,0x31,0xb4,0x70,0xbf,0xff,0xd,0x32,0x44,0x5,0xde,0xf8,0xbc,0x48,0x3b,0xae,0xfc,0x32,0x53,0xbb,0xd3,0x39,0x45,0x9f,0xc3,0xc1,0xe0,0x29,0x8b,0xa0},
{0xe5,0xc9,0x5,0xfd,0xf7,0xae,0x9,0xf,0x94,0x70,0x34,0x12,0x42,0x90,0xf1,0x34,0xa2,0x71,0xb7,0x1,0xe3,0x44,0xed,0x95,0xe9,0x3b,0x8e,0x36,0x4f,0x2f,0x98,0x4a},
{0x88,0x40,0x1d,0x63,0xa0,0x6c,0xf6,0x15,0x47,0xc1,0x44,0x4b,0x87,0x52,0xaf,0xff,0x7e,0xbb,0x4a,0xf1,0xe2,0xa,0xc6,0x30,0x46,0x70,0xb6,0xc5,0xcc,0x6e,0x8c,0xe6},
{0xa4,0xd5,0xa4,0x56,0xbd,0x4f,0xca,0x0,0xda,0x9d,0x84,0x4b,0xc8,0x3e,0x18,0xae,0x73,0x57,0xce,0x45,0x30,0x64,0xd1,0xad,0xe8,0xa6,0xce,0x68,0x14,0x5c,0x25,0x67},
{0xa3,0xda,0x8c,0xf2,0xcb,0xe,0xe1,0x16,0x33,0xe9,0x6,0x58,0x9a,0x94,0x99,0x9a,0x1f,0x60,0xb2,0x20,0xc2,0x6f,0x84,0x7b,0xd1,0xce,0xac,0x7f,0xa0,0xd1,0x85,0x18},
{0x32,0x59,0x5b,0xa1,0x8d,0xdd,0x19,0xd3,0x50,0x9a,0x1c,0xc0,0xaa,0xa5,0xb4,0x46,0x9f,0x3d,0x63,0x67,0xe4,0x4,0x6b,0xba,0xf6,0xca,0x19,0xab,0xb,0x56,0xee,0x7e},
{0x1f,0xb1,0x79,0xea,0xa9,0x28,0x21,0x74,0xe9,0xbd,0xf7,0x35,0x3b,0x36,0x51,0xee,0x1d,0x57,0xac,0x5a,0x75,0x50,0xd3,0x76,0x3a,0x46,0xc2,0xfe,0xa3,0x7d,0x70,0x1},
{0xf7,0x35,0xc1,0xaf,0x98,0xa4,0xd8,0x42,0x78,0xed,0xec,0x20,0x9e,0x6b,0x67,0x79,0x41,0x83,0x63,0x15,0xea,0x3a,0xdb,0xa8,0xfa,0xc3,0x3b,0x4d,0x32,0x83,0x2c,0x83},
{0xa7,0x40,0x3b,0x1f,0x1c,0x27,0x47,0xf3,0x59,0x40,0xf0,0x34,0xb7,0x2d,0x76,0x9a,0xe7,0x3e,0x4e,0x6c,0xd2,0x21,0x4f,0xfd,0xb8,0xfd,0x8d,0x39,0xdc,0x57,0x59,0xef},
{0x8d,0x9b,0xc,0x49,0x2b,0x49,0xeb,0xda,0x5b,0xa2,0xd7,0x49,0x68,0xf3,0x70,0xd,0x7d,0x3b,0xae,0xd0,0x7a,0x8d,0x55,0x84,0xf5,0xa5,0xe9,0xf0,0xe4,0xf8,0x8e,0x65},
{0xa0,0xb8,0xa2,0xf4,0x36,0x10,0x3b,0x53,0xc,0xa8,0x7,0x9e,0x75,0x3e,0xec,0x5a,0x91,0x68,0x94,0x92,0x56,0xe8,0x88,0x4f,0x5b,0xb0,0x5c,0x55,0xf8,0xba,0xbc,0x4c},
{0xe3,0xbb,0x3b,0x99,0xf3,0x87,0x94,0x7b,0x75,0xda,0xf4,0xd6,0x72,0x6b,0x1c,0x5d,0x64,0xae,0xac,0x28,0xdc,0x34,0xb3,0x6d,0x6c,0x34,0xa5,0x50,0xb8,0x28,0xdb,0x71},
{0xf8,0x61,0xe2,0xf2,0x10,0x8d,0x51,0x2a,0xe3,0xdb,0x64,0x33,0x59,0xdd,0x75,0xfc,0x1c,0xac,0xbc,0xf1,0x43,0xce,0x3f,0xa2,0x67,0xbb,0xd1,0x3c,0x2,0xe8,0x43,0xb0},
{0x33,0xa,0x5b,0xca,0x88,0x29,0xa1,0x75,0x7f,0x34,0x19,0x4d,0xb4,0x16,0x53,0x5c,0x92,0x3b,0x94,0xc3,0xe,0x79,0x4d,0x1e,0x79,0x74,0x75,0xd7,0xb6,0xee,0xaf,0x3f},
{0xea,0xa8,0xd4,0xf7,0xbe,0x1a,0x39,0x21,0x5c,0xf4,0x7e,0x9,0x4c,0x23,0x27,0x51,0x26,0xa3,0x24,0x53,0xba,0x32,0x3c,0xd2,0x44,0xa3,0x17,0x4a,0x6d,0xa6,0xd5,0xad},
{0xb5,0x1d,0x3e,0xa6,0xaf,0xf2,0xc9,0x8,0x83,0x59,0x3d,0x98,0x91,0x6b,0x3c,0x56,0x4c,0xf8,0x7c,0xa1,0x72,0x86,0x60,0x4d,0x46,0xe2,0x3e,0xcc,0x8,0x6e,0xc7,0xf6},
{0x2f,0x98,0x33,0xb3,0xb1,0xbc,0x76,0x5e,0x2b,0xd6,0x66,0xa5,0xef,0xc4,0xe6,0x2a,0x6,0xf4,0xb6,0xe8,0xbe,0xc1,0xd4,0x36,0x74,0xee,0x82,0x15,0xbc,0xef,0x21,0x63},
{0xfd,0xc1,0x4e,0xd,0xf4,0x53,0xc9,0x69,0xa7,0x7d,0x5a,0xc4,0x6,0x58,0x58,0x26,0x7e,0xc1,0x14,0x16,0x6,0xe0,0xfa,0x16,0x7e,0x90,0xaf,0x3d,0x28,0x63,0x9d,0x3f},
{0xd2,0xc9,0xf2,0xe3,0x0,0x9b,0xd2,0xc,0x5f,0xaa,0xce,0x30,0xb7,0xd4,0xc,0x30,0x74,0x2a,0x51,0x16,0xf2,0xe0,0x32,0x98,0xd,0xeb,0x30,0xd8,0xe3,0xce,0xf8,0x9a},
{0x4b,0xc5,0x9e,0x7b,0xb5,0xf1,0x79,0x92,0xff,0x51,0xe6,0x6e,0x4,0x86,0x68,0xd3,0x9b,0x23,0x4d,0x57,0xe6,0x96,0x67,0x31,0xcc,0xe6,0xa6,0xf3,0x17,0xa,0x75,0x5},
{0xb1,0x76,0x81,0xd9,0x13,0x32,0x6c,0xce,0x3c,0x17,0x52,0x84,0xf8,0x5,0xa2,0x62,0xf4,0x2b,0xcb,0xb3,0x78,0x47,0x15,0x47,0xff,0x46,0x54,0x82,0x23,0x93,0x6a,0x48},
{0x38,0xdf,0x58,0x7,0x4e,0x5e,0x65,0x65,0xf2,0xfc,0x7c,0x89,0xfc,0x86,0x50,0x8e,0x31,0x70,0x2e,0x44,0xd0,0xb,0xca,0x86,0xf0,0x40,0x9,0xa2,0x30,0x78,0x47,0x4e},
{0x65,0xa0,0xee,0x39,0xd1,0xf7,0x38,0x83,0xf7,0x5e,0xe9,0x37,0xe4,0x2c,0x3a,0xbd,0x21,0x97,0xb2,0x26,0x1,0x13,0xf8,0x6f,0xa3,0x44,0xed,0xd1,0xef,0x9f,0xde,0xe7},
{0x8b,0xa0,0xdf,0x15,0x76,0x25,0x92,0xd9,0x3c,0x85,0xf7,0xf6,0x12,0xdc,0x42,0xbe,0xd8,0xa7,0xec,0x7c,0xab,0x27,0xb0,0x7e,0x53,0x8d,0x7d,0xda,0xaa,0x3e,0xa8,0xde},
{0xaa,0x25,0xce,0x93,0xbd,0x2,0x69,0xd8,0x5a,0xf6,0x43,0xfd,0x1a,0x73,0x8,0xf9,0xc0,0x5f,0xef,0xda,0x17,0x4a,0x19,0xa5,0x97,0x4d,0x66,0x33,0x4c,0xfd,0x21,0x6a},
{0x35,0xb4,0x98,0x31,0xdb,0x41,0x15,0x70,0xea,0x1e,0xf,0xbb,0xed,0xcd,0x54,0x9b,0x9a,0xd0,0x63,0xa1,0x51,0x97,0x40,0x72,0xf6,0x75,0x9d,0xbf,0x91,0x47,0x6f,0xe2}};
/*swapping bit 2i with bit 2i+1 of 32-bit x*/
#define SWAP1(x) (x) = ((((x) & 0x55555555UL) << 1) | (((x) & 0xaaaaaaaaUL) >> 1));
/*swapping bits 4i||4i+1 with bits 4i+2||4i+3 of 32-bit x*/
#define SWAP2(x) (x) = ((((x) & 0x33333333UL) << 2) | (((x) & 0xccccccccUL) >> 2));
/*swapping bits 8i||8i+1||8i+2||8i+3 with bits 8i+4||8i+5||8i+6||8i+7 of 32-bit x*/
#define SWAP4(x) (x) = ((((x) & 0x0f0f0f0fUL) << 4) | (((x) & 0xf0f0f0f0UL) >> 4));
/*swapping bits 16i||16i+1||......||16i+7 with bits 16i+8||16i+9||......||16i+15 of 32-bit x*/
#define SWAP8(x) (x) = ((((x) & 0x00ff00ffUL) << 8) | (((x) & 0xff00ff00UL) >> 8));
/*swapping bits 32i||32i+1||......||32i+15 with bits 32i+16||32i+17||......||32i+31 of 32-bit x*/
#define SWAP16(x) (x) = ((((x) & 0x0000ffffUL) << 16) | (((x) & 0xffff0000UL) >> 16));
/*The MDS transform*/
#define L(m0,m1,m2,m3,m4,m5,m6,m7) \
(m4) ^= (m1); \
(m5) ^= (m2); \
(m6) ^= (m0) ^ (m3); \
(m7) ^= (m0); \
(m0) ^= (m5); \
(m1) ^= (m6); \
(m2) ^= (m4) ^ (m7); \
(m3) ^= (m4);
/*The Sbox*/
#define Sbox(m0,m1,m2,m3,cc) \
m3 = ~(m3); \
m0 ^= ((~(m2)) & (cc)); \
temp0 = (cc) ^ ((m0) & (m1));\
m0 ^= ((m2) & (m3)); \
m3 ^= ((~(m1)) & (m2)); \
m1 ^= ((m0) & (m2)); \
m2 ^= ((m0) & (~(m3))); \
m0 ^= ((m1) | (m3)); \
m3 ^= ((m1) & (m2)); \
m1 ^= (temp0 & (m0)); \
m2 ^= temp0;
__device__ __forceinline__ void Sbox_and_MDS_layer(hashState* state, uint32_t roundnumber)
{
uint32_t temp0;
uint32_t cc0, cc1;
//Sbox and MDS layer
#pragma unroll 4
for (int i = 0; i < 4; i++) {
cc0 = ((uint32_t*)c_E8_bitslice_roundconstant[roundnumber])[i];
cc1 = ((uint32_t*)c_E8_bitslice_roundconstant[roundnumber])[i+4];
Sbox(state->x[0][i],state->x[2][i], state->x[4][i], state->x[6][i], cc0);
Sbox(state->x[1][i],state->x[3][i], state->x[5][i], state->x[7][i], cc1);
L(state->x[0][i],state->x[2][i],state->x[4][i],state->x[6][i],state->x[1][i],state->x[3][i],state->x[5][i],state->x[7][i]);
}
}
__device__ __forceinline__ void RoundFunction0(hashState* state, uint32_t roundnumber)
{
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 4
for (int i = 0; i < 4; i++) SWAP1(state->x[j][i]);
}
}
__device__ __forceinline__ void RoundFunction1(hashState* state, uint32_t roundnumber)
{
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 4
for (int i = 0; i < 4; i++) SWAP2(state->x[j][i]);
}
}
__device__ __forceinline__ void RoundFunction2(hashState* state, uint32_t roundnumber)
{
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 4
for (int i = 0; i < 4; i++) SWAP4(state->x[j][i]);
}
}
__device__ __forceinline__ void RoundFunction3(hashState* state, uint32_t roundnumber)
{
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 4
for (int i = 0; i < 4; i++) SWAP8(state->x[j][i]);
}
}
__device__ __forceinline__ void RoundFunction4(hashState* state, uint32_t roundnumber)
{
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 4
for (int i = 0; i < 4; i++) SWAP16(state->x[j][i]);
}
}
__device__ __forceinline__ void RoundFunction5(hashState* state, uint32_t roundnumber)
{
uint32_t temp0;
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 2
for (int i = 0; i < 4; i = i+2) {
temp0 = state->x[j][i]; state->x[j][i] = state->x[j][i+1]; state->x[j][i+1] = temp0;
}
}
}
__device__ __forceinline__ void RoundFunction6(hashState* state, uint32_t roundnumber)
{
uint32_t temp0;
Sbox_and_MDS_layer(state, roundnumber);
#pragma unroll 4
for (int j = 1; j < 8; j = j+2)
{
#pragma unroll 2
for (int i = 0; i < 2; i++) {
temp0 = state->x[j][i]; state->x[j][i] = state->x[j][i+2]; state->x[j][i+2] = temp0;
}
}
}
/*The bijective function E8, in bitslice form */
__device__ __forceinline__ void E8(hashState *state)
{
/*perform 6 rounds*/
//#pragma unroll 6
for (int i = 0; i < 42; i+=7)
{
RoundFunction0(state, i);
RoundFunction1(state, i+1);
RoundFunction2(state, i+2);
RoundFunction3(state, i+3);
RoundFunction4(state, i+4);
RoundFunction5(state, i+5);
RoundFunction6(state, i+6);
}
}
/*The compression function F8 */
__device__ __forceinline__ void F8(hashState *state)
{
/*xor the 512-bit message with the fist half of the 1024-bit hash state*/
#pragma unroll 16
for (int i = 0; i < 16; i++) state->x[i >> 2][i & 3] ^= ((uint32_t*)state->buffer)[i];
/*the bijective function E8 */
E8(state);
/*xor the 512-bit message with the second half of the 1024-bit hash state*/
#pragma unroll 16
for (int i = 0; i < 16; i++) state->x[(16+i) >> 2][(16+i) & 3] ^= ((uint32_t*)state->buffer)[i];
}
__device__ __forceinline__ void JHHash(const uint32_t *data, uint32_t *hashval)
{
hashState state;
/*load the intital hash value H0 into state*/
/*
#define INIT(a,b,c,d) ((a) | ((b)<<8) | ((c)<<16) | ((d)<<24))
state.x[0][0] = INIT(0x6f,0xd1,0x4b,0x96);
state.x[0][1] = INIT(0x3e,0x00,0xaa,0x17);
state.x[0][2] = INIT(0x63,0x6a,0x2e,0x05);
state.x[0][3] = INIT(0x7a,0x15,0xd5,0x43);
state.x[1][0] = INIT(0x8a,0x22,0x5e,0x8d);
state.x[1][1] = INIT(0x0c,0x97,0xef,0x0b);
state.x[1][2] = INIT(0xe9,0x34,0x12,0x59);
state.x[1][3] = INIT(0xf2,0xb3,0xc3,0x61);
state.x[2][0] = INIT(0x89,0x1d,0xa0,0xc1);
state.x[2][1] = INIT(0x53,0x6f,0x80,0x1e);
state.x[2][2] = INIT(0x2a,0xa9,0x05,0x6b);
state.x[2][3] = INIT(0xea,0x2b,0x6d,0x80);
state.x[3][0] = INIT(0x58,0x8e,0xcc,0xdb);
state.x[3][1] = INIT(0x20,0x75,0xba,0xa6);
state.x[3][2] = INIT(0xa9,0x0f,0x3a,0x76);
state.x[3][3] = INIT(0xba,0xf8,0x3b,0xf7);
state.x[4][0] = INIT(0x01,0x69,0xe6,0x05);
state.x[4][1] = INIT(0x41,0xe3,0x4a,0x69);
state.x[4][2] = INIT(0x46,0xb5,0x8a,0x8e);
state.x[4][3] = INIT(0x2e,0x6f,0xe6,0x5a);
state.x[5][0] = INIT(0x10,0x47,0xa7,0xd0);
state.x[5][1] = INIT(0xc1,0x84,0x3c,0x24);
state.x[5][2] = INIT(0x3b,0x6e,0x71,0xb1);
state.x[5][3] = INIT(0x2d,0x5a,0xc1,0x99);
state.x[6][0] = INIT(0xcf,0x57,0xf6,0xec);
state.x[6][1] = INIT(0x9d,0xb1,0xf8,0x56);
state.x[6][2] = INIT(0xa7,0x06,0x88,0x7c);
state.x[6][3] = INIT(0x57,0x16,0xb1,0x56);
state.x[7][0] = INIT(0xe3,0xc2,0xfc,0xdf);
state.x[7][1] = INIT(0xe6,0x85,0x17,0xfb);
state.x[7][2] = INIT(0x54,0x5a,0x46,0x78);
state.x[7][3] = INIT(0xcc,0x8c,0xdd,0x4b);
*/
#pragma unroll 8
for(int j=0;j<8;j++)
{
#pragma unroll 4
for(int i=0;i<4;i++)
state.x[j][i] = c_INIT_bitslice[j][i];
}
#pragma unroll 16
for (int i=0; i < 16; ++i) state.buffer[i] = data[i];
F8(&state);
/*pad the message when databitlen is multiple of 512 bits, then process the padded block*/
state.buffer[0] = 0x80;
#pragma unroll 14
for (int i=1; i < 15; i++) state.buffer[i] = 0;
state.buffer[15] = 0x00020000;
F8(&state);
/*truncating the final hash value to generate the message digest*/
#pragma unroll 16
for (int i=0; i < 16; ++i) hashval[i] = state.x[4][i];
}
// Die Hash-Funktion
__global__ void quark_jh512_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];
JHHash(Hash, Hash);
}
}
// Setup-Funktionen
__host__ void quark_jh512_cpu_init(int thr_id, int threads)
{
cudaMemcpyToSymbol( c_E8_bitslice_roundconstant,
h_E8_bitslice_roundconstant,
sizeof(h_E8_bitslice_roundconstant),
0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol( c_INIT_bitslice,
h_INIT_bitslice,
sizeof(h_INIT_bitslice),
0, cudaMemcpyHostToDevice);
}
__host__ void quark_jh512_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;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
quark_jh512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector);
MyStreamSynchronize(NULL, order, thr_id);
}

482
quark/cuda_quark_blake512.cu

@ -0,0 +1,482 @@ @@ -0,0 +1,482 @@
#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <memory.h>
#define USE_SHUFFLE 0
// Folgende Definitionen später durch header ersetzen
typedef unsigned char uint8_t;
typedef unsigned int uint32_t;
typedef unsigned long long uint64_t;
// aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
// die Message it Padding zur Berechnung auf der GPU
__constant__ uint64_t c_PaddedMessage80[16]; // padded message (80 bytes + padding)
// ---------------------------- BEGIN CUDA quark_blake512 functions ------------------------------------
__constant__ uint8_t c_sigma[16][16];
const uint8_t host_sigma[16][16] =
{
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 },
{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 },
{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 },
{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 },
{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 },
{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 },
{12, 5, 1, 15, 14, 13, 4, 10, 0, 7, 6, 3, 9, 2, 8, 11 },
{13, 11, 7, 14, 12, 1, 3, 9, 5, 0, 15, 4, 8, 6, 2, 10 },
{ 6, 15, 14, 9, 11, 3, 0, 8, 12, 2, 13, 7, 1, 4, 10, 5 },
{10, 2, 8, 4, 7, 6, 1, 5, 15, 11, 9, 14, 3, 12, 13 , 0 },
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 },
{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 },
{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 },
{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 },
{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 },
{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 }
};
// das Hi Word aus einem 64 Bit Typen extrahieren
static __device__ uint32_t HIWORD(const uint64_t &x) {
#if __CUDA_ARCH__ >= 130
return (uint32_t)__double2hiint(__longlong_as_double(x));
#else
return (uint32_t)(x >> 32);
#endif
}
// das Hi Word in einem 64 Bit Typen ersetzen
static __device__ uint64_t REPLACE_HIWORD(const uint64_t &x, const uint32_t &y) {
return (x & 0xFFFFFFFFULL) | (((uint64_t)y) << 32ULL);
}
// das Lo Word aus einem 64 Bit Typen extrahieren
static __device__ uint32_t LOWORD(const uint64_t &x) {
#if __CUDA_ARCH__ >= 130
return (uint32_t)__double2loint(__longlong_as_double(x));
#else
return (uint32_t)(x & 0xFFFFFFFFULL);
#endif
}
// das Lo Word in einem 64 Bit Typen ersetzen
static __device__ uint64_t REPLACE_LOWORD(const uint64_t &x, const uint32_t &y) {
return (x & 0xFFFFFFFF00000000ULL) | ((uint64_t)y);
}
/*
#define SWAP32(x) \
((((x) << 24) & 0xff000000u) | (((x) << 8) & 0x00ff0000u) | \
(((x) >> 8) & 0x0000ff00u) | (((x) >> 24) & 0x000000ffu))
#define SWAP64(x) \
((uint64_t)((((uint64_t)(x) & 0xff00000000000000ULL) >> 56) | \
(((uint64_t)(x) & 0x00ff000000000000ULL) >> 40) | \
(((uint64_t)(x) & 0x0000ff0000000000ULL) >> 24) | \
(((uint64_t)(x) & 0x000000ff00000000ULL) >> 8) | \
(((uint64_t)(x) & 0x00000000ff000000ULL) << 8) | \
(((uint64_t)(x) & 0x0000000000ff0000ULL) << 24) | \
(((uint64_t)(x) & 0x000000000000ff00ULL) << 40) | \
(((uint64_t)(x) & 0x00000000000000ffULL) << 56)))
*/
/*
__device__ __forceinline__ void SWAP32(uint32_t *x)
{
// Input: 33221100
// Output: 00112233
x[0] = __byte_perm(x[0], 0, 0x0123);
}
*/
__device__ __forceinline__ uint64_t SWAP64(uint64_t x)
{
// Input: 77665544 33221100
// Output: 00112233 44556677
uint64_t temp[2];
temp[0] = __byte_perm(HIWORD(x), 0, 0x0123);
temp[1] = __byte_perm(LOWORD(x), 0, 0x0123);
return temp[0] | (temp[1]<<32);
}
__constant__ uint64_t c_u512[16];
const uint64_t host_u512[16] =
{
0x243f6a8885a308d3ULL, 0x13198a2e03707344ULL,
0xa4093822299f31d0ULL, 0x082efa98ec4e6c89ULL,
0x452821e638d01377ULL, 0xbe5466cf34e90c6cULL,
0xc0ac29b7c97c50ddULL, 0x3f84d5b5b5470917ULL,
0x9216d5d98979fb1bULL, 0xd1310ba698dfb5acULL,
0x2ffd72dbd01adfb7ULL, 0xb8e1afed6a267e96ULL,
0xba7c9045f12c7f99ULL, 0x24a19947b3916cf7ULL,
0x0801f2e2858efc16ULL, 0x636920d871574e69ULL
};
// diese 64 Bit Rotates werden unter Compute 3.5 (und besser) mit dem Funnel Shifter beschleunigt
#if __CUDA_ARCH__ >= 350
__forceinline__ __device__ uint64_t ROTR(const uint64_t value, const int offset) {
uint2 result;
if(offset < 32) {
asm("shf.r.wrap.b32 %0, %1, %2, %3;" : "=r"(result.x) : "r"(__double2loint(__longlong_as_double(value))), "r"(__double2hiint(__longlong_as_double(value))), "r"(offset));
asm("shf.r.wrap.b32 %0, %1, %2, %3;" : "=r"(result.y) : "r"(__double2hiint(__longlong_as_double(value))), "r"(__double2loint(__longlong_as_double(value))), "r"(offset));
} else {
asm("shf.r.wrap.b32 %0, %1, %2, %3;" : "=r"(result.x) : "r"(__double2hiint(__longlong_as_double(value))), "r"(__double2loint(__longlong_as_double(value))), "r"(offset));
asm("shf.r.wrap.b32 %0, %1, %2, %3;" : "=r"(result.y) : "r"(__double2loint(__longlong_as_double(value))), "r"(__double2hiint(__longlong_as_double(value))), "r"(offset));
}
return __double_as_longlong(__hiloint2double(result.y, result.x));
}
#else
#define ROTR(x, n) (((x) >> (n)) | ((x) << (64 - (n))))
#endif
#define G(a,b,c,d,e) \
v[a] += (m[sigma[i][e]] ^ u512[sigma[i][e+1]]) + v[b];\
v[d] = ROTR( v[d] ^ v[a],32); \
v[c] += v[d]; \
v[b] = ROTR( v[b] ^ v[c],25); \
v[a] += (m[sigma[i][e+1]] ^ u512[sigma[i][e]])+v[b]; \
v[d] = ROTR( v[d] ^ v[a],16); \
v[c] += v[d]; \
v[b] = ROTR( v[b] ^ v[c],11);
__device__ void quark_blake512_compress( uint64_t *h, const uint64_t *block, const uint8_t ((*sigma)[16]), const uint64_t *u512, const int bits )
{
uint64_t v[16], m[16], i;
#pragma unroll 16
for( i = 0; i < 16; ++i )
{
m[i] = SWAP64(block[i]);
}
#pragma unroll 8
for( i = 0; i < 8; ++i ) v[i] = h[i];
v[ 8] = u512[0];
v[ 9] = u512[1];
v[10] = u512[2];
v[11] = u512[3];
v[12] = u512[4];
v[13] = u512[5];
v[14] = u512[6];
v[15] = u512[7];
v[12] ^= bits;
v[13] ^= bits;
//#pragma unroll 16
for( i = 0; i < 16; ++i )
{
/* column step */
G( 0, 4, 8, 12, 0 );
G( 1, 5, 9, 13, 2 );
G( 2, 6, 10, 14, 4 );
G( 3, 7, 11, 15, 6 );
/* diagonal step */
G( 0, 5, 10, 15, 8 );
G( 1, 6, 11, 12, 10 );
G( 2, 7, 8, 13, 12 );
G( 3, 4, 9, 14, 14 );
}
#pragma unroll 16
for( i = 0; i < 16; ++i ) h[i % 8] ^= v[i];
}
// Endian Drehung für 32 Bit Typen
static __device__ uint32_t cuda_swab32(uint32_t x)
{
return __byte_perm(x, 0, 0x0123);
/*
return (((x << 24) & 0xff000000u) | ((x << 8) & 0x00ff0000u)
| ((x >> 8) & 0x0000ff00u) | ((x >> 24) & 0x000000ffu));
*/
}
/*
// Endian Drehung für 64 Bit Typen
static __device__ uint64_t cuda_swab64(uint64_t x) {
uint32_t h = (x >> 32);
uint32_t l = (x & 0xFFFFFFFFULL);
return (((uint64_t)cuda_swab32(l)) << 32) | ((uint64_t)cuda_swab32(h));
}
*/
static __constant__ uint64_t d_constMem[8];
static const uint64_t h_constMem[8] = {
0x6a09e667f3bcc908ULL,
0xbb67ae8584caa73bULL,
0x3c6ef372fe94f82bULL,
0xa54ff53a5f1d36f1ULL,
0x510e527fade682d1ULL,
0x9b05688c2b3e6c1fULL,
0x1f83d9abfb41bd6bULL,
0x5be0cd19137e2179ULL };
// Hash-Padding
static __constant__ uint64_t d_constHashPadding[8];
static const uint64_t h_constHashPadding[8] = {
0x0000000000000080ull,
0,
0,
0,
0,
0x0100000000000000ull,
0,
0x0002000000000000ull };
__global__ void quark_blake512_gpu_hash_64(int threads, uint32_t startNounce, uint32_t *g_nonceVector, uint64_t *g_hash)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
#if USE_SHUFFLE
const int warpID = threadIdx.x & 0x0F; // 16 warps
const int warpBlockID = (thread + 15)>>4; // aufrunden auf volle Warp-Blöcke
const int maxHashPosition = thread<<3;
#endif
#if USE_SHUFFLE
if (warpBlockID < ( (threads+15)>>4 ))
#else
if (thread < threads)
#endif
{
// bestimme den aktuellen Zähler
uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
//uint64_t *inpHash = &g_hash[8 * hashPosition];
uint64_t *inpHash = &g_hash[hashPosition<<3];
// State vorbereiten
uint64_t h[8];
/*
h[0] = 0x6a09e667f3bcc908ULL;
h[1] = 0xbb67ae8584caa73bULL;
h[2] = 0x3c6ef372fe94f82bULL;
h[3] = 0xa54ff53a5f1d36f1ULL;
h[4] = 0x510e527fade682d1ULL;
h[5] = 0x9b05688c2b3e6c1fULL;
h[6] = 0x1f83d9abfb41bd6bULL;
h[7] = 0x5be0cd19137e2179ULL;
*/
#pragma unroll 8
for(int i=0;i<8;i++)
h[i] = d_constMem[i];
// 128 Byte für die Message
uint64_t buf[16];
// Message für die erste Runde in Register holen
#pragma unroll 8
for (int i=0; i < 8; ++i) buf[i] = inpHash[i];
/*
buf[ 8] = 0x0000000000000080ull;
buf[ 9] = 0;
buf[10] = 0;
buf[11] = 0;
buf[12] = 0;
buf[13] = 0x0100000000000000ull;
buf[14] = 0;
buf[15] = 0x0002000000000000ull;
*/
#pragma unroll 8
for(int i=0;i<8;i++)
buf[i+8] = d_constHashPadding[i];
// die einzige Hashing-Runde
quark_blake512_compress( h, buf, c_sigma, c_u512, 512 );
// Hash rauslassen
#if __CUDA_ARCH__ >= 130
// ausschliesslich 32 bit Operationen sofern die SM1.3 double intrinsics verfügbar sind
uint32_t *outHash = (uint32_t*)&g_hash[8 * hashPosition];
#pragma unroll 8
for (int i=0; i < 8; ++i) {
outHash[2*i+0] = cuda_swab32( HIWORD(h[i]) );
outHash[2*i+1] = cuda_swab32( LOWORD(h[i]) );
}
#else
// in dieser Version passieren auch ein paar 64 Bit Shifts
uint64_t *outHash = &g_hash[8 * hashPosition];
#pragma unroll 8
for (int i=0; i < 8; ++i)
{
//outHash[i] = cuda_swab64( h[i] );
outHash[i] = SWAP64(h[i]);
}
#endif
}
}
__global__ void quark_blake512_gpu_hash_80(int threads, uint32_t startNounce, void *outputHash)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
// bestimme den aktuellen Zähler
uint32_t nounce = startNounce + thread;
// State vorbereiten
uint64_t h[8];
/*
h[0] = 0x6a09e667f3bcc908ULL;
h[1] = 0xbb67ae8584caa73bULL;
h[2] = 0x3c6ef372fe94f82bULL;
h[3] = 0xa54ff53a5f1d36f1ULL;
h[4] = 0x510e527fade682d1ULL;
h[5] = 0x9b05688c2b3e6c1fULL;
h[6] = 0x1f83d9abfb41bd6bULL;
h[7] = 0x5be0cd19137e2179ULL;
*/
#pragma unroll 8
for(int i=0;i<8;i++)
h[i] = d_constMem[i];
// 128 Byte für die Message
uint64_t buf[16];
// Message für die erste Runde in Register holen
#pragma unroll 16
for (int i=0; i < 16; ++i) buf[i] = c_PaddedMessage80[i];
// die Nounce durch die thread-spezifische ersetzen
buf[9] = REPLACE_HIWORD(buf[9], cuda_swab32(nounce));
// die einzige Hashing-Runde
quark_blake512_compress( h, buf, c_sigma, c_u512, 640 );
// Hash rauslassen
#if __CUDA_ARCH__ >= 130
// ausschliesslich 32 bit Operationen sofern die SM1.3 double intrinsics verfügbar sind
uint32_t *outHash = (uint32_t *)outputHash + 16 * thread;
#pragma unroll 8
for (int i=0; i < 8; ++i) {
outHash[2*i+0] = cuda_swab32( HIWORD(h[i]) );
outHash[2*i+1] = cuda_swab32( LOWORD(h[i]) );
}
#else
// in dieser Version passieren auch ein paar 64 Bit Shifts
uint64_t *outHash = (uint64_t *)outputHash + 8 * thread;
#pragma unroll 8
for (int i=0; i < 8; ++i)
{
//outHash[i] = cuda_swab64( h[i] );
outHash[i] = SWAP64(h[i]);
}
#endif
}
}
// ---------------------------- END CUDA quark_blake512 functions ------------------------------------
// Setup-Funktionen
__host__ void quark_blake512_cpu_init(int thr_id, int threads)
{
// Kopiere die Hash-Tabellen in den GPU-Speicher
cudaMemcpyToSymbol( c_sigma,
host_sigma,
sizeof(host_sigma),
0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol( c_u512,
host_u512,
sizeof(host_u512),
0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol( d_constMem,
h_constMem,
sizeof(h_constMem),
0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol( d_constHashPadding,
h_constHashPadding,
sizeof(h_constHashPadding),
0, cudaMemcpyHostToDevice);
}
// Blake512 für 80 Byte grosse Eingangsdaten
__host__ void quark_blake512_cpu_setBlock_80(void *pdata)
{
// Message mit Padding bereitstellen
// lediglich die korrekte Nonce ist noch ab Byte 76 einzusetzen.
unsigned char PaddedMessage[128];
memcpy(PaddedMessage, pdata, 80);
memset(PaddedMessage+80, 0, 48);
PaddedMessage[80] = 0x80;
PaddedMessage[111] = 1;
PaddedMessage[126] = 0x02;
PaddedMessage[127] = 0x80;
// die Message zur Berechnung auf der GPU
cudaMemcpyToSymbol( c_PaddedMessage80, PaddedMessage, 16*sizeof(uint64_t), 0, cudaMemcpyHostToDevice);
}
#if 0
// Blake512 für 64 Byte grosse Eingangsdaten
// evtl. macht es gar keinen Sinn, das alles ins Constant Memory to schicken. Es sind hier sowieso
// nur die letzten 64 Bytes des Blocks konstant, und die meisten Bytes davon sind 0. Das kann mnan
// auch im Kernel initialisieren.
__host__ void quark_blake512_cpu_setBlock_64(void *pdata)
{
// Message mit Padding bereitstellen
unsigned char PaddedMessage[128];
memcpy(PaddedMessage, pdata, 64); // Hinweis: diese 64 Bytes sind nonce-spezifisch und ändern sich KOMPLETT für jede Nonce!
memset(PaddedMessage+64, 0, 64);
PaddedMessage[64] = 0x80;
PaddedMessage[111] = 1;
PaddedMessage[126] = 0x02;
PaddedMessage[127] = 0x00;
// die Message zur Berechnung auf der GPU
cudaMemcpyToSymbol( c_PaddedMessage80, PaddedMessage, 16*sizeof(uint64_t), 0, cudaMemcpyHostToDevice);
}
#endif
__host__ void quark_blake512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_outputHash, 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;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
quark_blake512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_nonceVector, (uint64_t*)d_outputHash);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, order, thr_id);
}
__host__ void quark_blake512_cpu_hash_80(int thr_id, int threads, uint32_t startNounce, uint32_t *d_outputHash, 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;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
quark_blake512_gpu_hash_80<<<grid, block, shared_size>>>(threads, startNounce, d_outputHash);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, order, thr_id);
}

397
quark/cuda_quark_groestl512.cu

@ -0,0 +1,397 @@ @@ -0,0 +1,397 @@
// Auf QuarkCoin spezialisierte Version von Groestl
#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <memory.h>
// it's unfortunate that this is a compile time constant.
#define MAXWELL_OR_FERMI 0
// aus cpu-miner.c
extern int device_map[8];
// aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
// Folgende Definitionen später durch header ersetzen
typedef unsigned char uint8_t;
typedef unsigned int uint32_t;
typedef unsigned long long uint64_t;
// diese Struktur wird in der Init Funktion angefordert
static cudaDeviceProp props[8];
#define SPH_C32(x) ((uint32_t)(x ## U))
#define SPH_T32(x) ((x) & SPH_C32(0xFFFFFFFF))
#define PC32up(j, r) ((uint32_t)((j) + (r)))
#define PC32dn(j, r) 0
#define QC32up(j, r) 0xFFFFFFFF
#define QC32dn(j, r) (((uint32_t)(r) << 24) ^ SPH_T32(~((uint32_t)(j) << 24)))
#define B32_0(x) __byte_perm(x, 0, 0x4440)
//((x) & 0xFF)
#define B32_1(x) __byte_perm(x, 0, 0x4441)
//(((x) >> 8) & 0xFF)
#define B32_2(x) __byte_perm(x, 0, 0x4442)
//(((x) >> 16) & 0xFF)
#define B32_3(x) __byte_perm(x, 0, 0x4443)
//((x) >> 24)
#if MAXWELL_OR_FEMRI
#define USE_SHARED 1
// Maxwell and Fermi cards get the best speed with SHARED access it seems.
#if USE_SHARED
#define T0up(x) (*((uint32_t*)mixtabs + ( (x))))
#define T0dn(x) (*((uint32_t*)mixtabs + (256+(x))))
#define T1up(x) (*((uint32_t*)mixtabs + (512+(x))))
#define T1dn(x) (*((uint32_t*)mixtabs + (768+(x))))
#define T2up(x) (*((uint32_t*)mixtabs + (1024+(x))))
#define T2dn(x) (*((uint32_t*)mixtabs + (1280+(x))))
#define T3up(x) (*((uint32_t*)mixtabs + (1536+(x))))
#define T3dn(x) (*((uint32_t*)mixtabs + (1792+(x))))
#else
#define T0up(x) tex1Dfetch(t0up1, x)
#define T0dn(x) tex1Dfetch(t0dn1, x)
#define T1up(x) tex1Dfetch(t1up1, x)
#define T1dn(x) tex1Dfetch(t1dn1, x)
#define T2up(x) tex1Dfetch(t2up1, x)
#define T2dn(x) tex1Dfetch(t2dn1, x)
#define T3up(x) tex1Dfetch(t3up1, x)
#define T3dn(x) tex1Dfetch(t3dn1, x)
#endif
#else
#define USE_SHARED 1
// a healthy mix between shared and textured access provides the highest speed on Compute 3.0 and 3.5!
#define T0up(x) (*((uint32_t*)mixtabs + ( (x))))
#define T0dn(x) tex1Dfetch(t0dn1, x)
#define T1up(x) tex1Dfetch(t1up1, x)
#define T1dn(x) (*((uint32_t*)mixtabs + (768+(x))))
#define T2up(x) tex1Dfetch(t2up1, x)
#define T2dn(x) (*((uint32_t*)mixtabs + (1280+(x))))
#define T3up(x) (*((uint32_t*)mixtabs + (1536+(x))))
#define T3dn(x) tex1Dfetch(t3dn1, x)
#endif
texture<unsigned int, 1, cudaReadModeElementType> t0up1;
texture<unsigned int, 1, cudaReadModeElementType> t0dn1;
texture<unsigned int, 1, cudaReadModeElementType> t1up1;
texture<unsigned int, 1, cudaReadModeElementType> t1dn1;
texture<unsigned int, 1, cudaReadModeElementType> t2up1;
texture<unsigned int, 1, cudaReadModeElementType> t2dn1;
texture<unsigned int, 1, cudaReadModeElementType> t3up1;
texture<unsigned int, 1, cudaReadModeElementType> t3dn1;
extern uint32_t T0up_cpu[];
extern uint32_t T0dn_cpu[];
extern uint32_t T1up_cpu[];
extern uint32_t T1dn_cpu[];
extern uint32_t T2up_cpu[];
extern uint32_t T2dn_cpu[];
extern uint32_t T3up_cpu[];
extern uint32_t T3dn_cpu[];
__device__ __forceinline__ void quark_groestl512_perm_P(uint32_t *a, char *mixtabs)
{
uint32_t t[32];
//#pragma unroll 14
for(int r=0;r<14;r++)
{
switch(r)
{
case 0:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 0); break;
case 1:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 1); break;
case 2:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 2); break;
case 3:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 3); break;
case 4:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 4); break;
case 5:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 5); break;
case 6:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 6); break;
case 7:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 7); break;
case 8:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 8); break;
case 9:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 9); break;
case 10:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 10); break;
case 11:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 11); break;
case 12:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 12); break;
case 13:
#pragma unroll 16
for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k<< 4, 13); break;
}
// RBTT
#pragma unroll 16
for(int k=0;k<32;k+=2)
{
uint32_t t0_0 = B32_0(a[(k ) & 0x1f]), t9_0 = B32_0(a[(k + 9) & 0x1f]);
uint32_t t2_1 = B32_1(a[(k + 2) & 0x1f]), t11_1 = B32_1(a[(k + 11) & 0x1f]);
uint32_t t4_2 = B32_2(a[(k + 4) & 0x1f]), t13_2 = B32_2(a[(k + 13) & 0x1f]);
uint32_t t6_3 = B32_3(a[(k + 6) & 0x1f]), t23_3 = B32_3(a[(k + 23) & 0x1f]);
t[k + 0] = T0up( t0_0 ) ^ T1up( t2_1 ) ^ T2up( t4_2 ) ^ T3up( t6_3 ) ^
T0dn( t9_0 ) ^ T1dn( t11_1 ) ^ T2dn( t13_2 ) ^ T3dn( t23_3 );
t[k + 1] = T0dn( t0_0 ) ^ T1dn( t2_1 ) ^ T2dn( t4_2 ) ^ T3dn( t6_3 ) ^
T0up( t9_0 ) ^ T1up( t11_1 ) ^ T2up( t13_2 ) ^ T3up( t23_3 );
}
#pragma unroll 32
for(int k=0;k<32;k++)
a[k] = t[k];
}
}
__device__ __forceinline__ void quark_groestl512_perm_Q(uint32_t *a, char *mixtabs)
{
//#pragma unroll 14
for(int r=0;r<14;r++)
{
uint32_t t[32];
switch(r)
{
case 0:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 0); a[(k*2)+1] ^= QC32dn(k<< 4, 0);} break;
case 1:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 1); a[(k*2)+1] ^= QC32dn(k<< 4, 1);} break;
case 2:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 2); a[(k*2)+1] ^= QC32dn(k<< 4, 2);} break;
case 3:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 3); a[(k*2)+1] ^= QC32dn(k<< 4, 3);} break;
case 4:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 4); a[(k*2)+1] ^= QC32dn(k<< 4, 4);} break;
case 5:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 5); a[(k*2)+1] ^= QC32dn(k<< 4, 5);} break;
case 6:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 6); a[(k*2)+1] ^= QC32dn(k<< 4, 6);} break;
case 7:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 7); a[(k*2)+1] ^= QC32dn(k<< 4, 7);} break;
case 8:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 8); a[(k*2)+1] ^= QC32dn(k<< 4, 8);} break;
case 9:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 9); a[(k*2)+1] ^= QC32dn(k<< 4, 9);} break;
case 10:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 10); a[(k*2)+1] ^= QC32dn(k<< 4, 10);} break;
case 11:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 11); a[(k*2)+1] ^= QC32dn(k<< 4, 11);} break;
case 12:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 12); a[(k*2)+1] ^= QC32dn(k<< 4, 12);} break;
case 13:
#pragma unroll 16
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k<< 4, 13); a[(k*2)+1] ^= QC32dn(k<< 4, 13);} break;
}
// RBTT
#pragma unroll 16
for(int k=0;k<32;k+=2)
{
uint32_t t2_0 = B32_0(a[(k + 2) & 0x1f]), t1_0 = B32_0(a[(k + 1) & 0x1f]);
uint32_t t6_1 = B32_1(a[(k + 6) & 0x1f]), t5_1 = B32_1(a[(k + 5) & 0x1f]);
uint32_t t10_2 = B32_2(a[(k + 10) & 0x1f]), t9_2 = B32_2(a[(k + 9) & 0x1f]);
uint32_t t22_3 = B32_3(a[(k + 22) & 0x1f]), t13_3 = B32_3(a[(k + 13) & 0x1f]);
t[k + 0] = T0up( t2_0 ) ^ T1up( t6_1 ) ^ T2up( t10_2 ) ^ T3up( t22_3 ) ^
T0dn( t1_0 ) ^ T1dn( t5_1 ) ^ T2dn( t9_2 ) ^ T3dn( t13_3 );
t[k + 1] = T0dn( t2_0 ) ^ T1dn( t6_1 ) ^ T2dn( t10_2 ) ^ T3dn( t22_3 ) ^
T0up( t1_0 ) ^ T1up( t5_1 ) ^ T2up( t9_2 ) ^ T3up( t13_3 );
}
#pragma unroll 32
for(int k=0;k<32;k++)
a[k] = t[k];
}
}
__global__ void quark_groestl512_gpu_hash_64(int threads, uint32_t startNounce, uint32_t *g_hash, uint32_t *g_nonceVector)
{
#if USE_SHARED
extern __shared__ char mixtabs[];
if (threadIdx.x < 256)
{
*((uint32_t*)mixtabs + ( threadIdx.x)) = tex1Dfetch(t0up1, threadIdx.x);
*((uint32_t*)mixtabs + (256+threadIdx.x)) = tex1Dfetch(t0dn1, threadIdx.x);
*((uint32_t*)mixtabs + (512+threadIdx.x)) = tex1Dfetch(t1up1, threadIdx.x);
*((uint32_t*)mixtabs + (768+threadIdx.x)) = tex1Dfetch(t1dn1, threadIdx.x);
*((uint32_t*)mixtabs + (1024+threadIdx.x)) = tex1Dfetch(t2up1, threadIdx.x);
*((uint32_t*)mixtabs + (1280+threadIdx.x)) = tex1Dfetch(t2dn1, threadIdx.x);
*((uint32_t*)mixtabs + (1536+threadIdx.x)) = tex1Dfetch(t3up1, threadIdx.x);
*((uint32_t*)mixtabs + (1792+threadIdx.x)) = tex1Dfetch(t3dn1, threadIdx.x);
}
__syncthreads();
#endif
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
// GROESTL
uint32_t message[32];
uint32_t state[32];
uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
uint32_t *inpHash = &g_hash[16 * hashPosition];
#pragma unroll 16
for(int k=0;k<16;k++) message[k] = inpHash[k];
#pragma unroll 14
for(int k=1;k<15;k++)
message[k+16] = 0;
message[16] = 0x80;
message[31] = 0x01000000;
#pragma unroll 32
for(int u=0;u<32;u++) state[u] = message[u];
state[31] ^= 0x20000;
// Perm
#if USE_SHARED
quark_groestl512_perm_P(state, mixtabs);
state[31] ^= 0x20000;
quark_groestl512_perm_Q(message, mixtabs);
#else
quark_groestl512_perm_P(state, NULL);
state[31] ^= 0x20000;
quark_groestl512_perm_Q(message, NULL);
#endif
#pragma unroll 32
for(int u=0;u<32;u++) state[u] ^= message[u];
#pragma unroll 32
for(int u=0;u<32;u++) message[u] = state[u];
#if USE_SHARED
quark_groestl512_perm_P(message, mixtabs);
#else
quark_groestl512_perm_P(message, NULL);
#endif
#pragma unroll 32
for(int u=0;u<32;u++) state[u] ^= message[u];
// Erzeugten Hash rausschreiben
uint32_t *outpHash = &g_hash[16 * hashPosition];
#pragma unroll 16
for(int k=0;k<16;k++) outpHash[k] = state[k+16];
}
}
#define texDef(texname, texmem, texsource, texsize) \
unsigned int *texmem; \
cudaMalloc(&texmem, texsize); \
cudaMemcpy(texmem, texsource, texsize, cudaMemcpyHostToDevice); \
texname.normalized = 0; \
texname.filterMode = cudaFilterModePoint; \
texname.addressMode[0] = cudaAddressModeClamp; \
{ cudaChannelFormatDesc channelDesc = cudaCreateChannelDesc<unsigned int>(); \
cudaBindTexture(NULL, &texname, texmem, &channelDesc, texsize ); } \
// Setup-Funktionen
__host__ void quark_groestl512_cpu_init(int thr_id, int threads)
{
cudaGetDeviceProperties(&props[thr_id], device_map[thr_id]);
// Texturen mit obigem Makro initialisieren
texDef(t0up1, d_T0up, T0up_cpu, sizeof(uint32_t)*256);
texDef(t0dn1, d_T0dn, T0dn_cpu, sizeof(uint32_t)*256);
texDef(t1up1, d_T1up, T1up_cpu, sizeof(uint32_t)*256);
texDef(t1dn1, d_T1dn, T1dn_cpu, sizeof(uint32_t)*256);
texDef(t2up1, d_T2up, T2up_cpu, sizeof(uint32_t)*256);
texDef(t2dn1, d_T2dn, T2dn_cpu, sizeof(uint32_t)*256);
texDef(t3up1, d_T3up, T3up_cpu, sizeof(uint32_t)*256);
texDef(t3dn1, d_T3dn, T3dn_cpu, sizeof(uint32_t)*256);
}
__host__ void quark_groestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order)
{
// Compute 3.5 und 5.x Geräte am besten mit 768 Threads ansteuern,
// alle anderen mit 512 Threads.
int threadsperblock = ((props[thr_id].major == 3 && props[thr_id].minor == 5) || props[thr_id].major > 3) ? 768 : 512;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
// Größe des dynamischen Shared Memory Bereichs
#if USE_SHARED
size_t shared_size = 8 * 256 * sizeof(uint32_t);
#else
size_t shared_size = 0;
#endif
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
//fprintf(stderr, "ThrID: %d\n", thr_id);
quark_groestl512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, order, thr_id);
}
__host__ void quark_doublegroestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order)
{
// Compute 3.5 und 5.x Geräte am besten mit 768 Threads ansteuern,
// alle anderen mit 512 Threads.
int threadsperblock = ((props[thr_id].major == 3 && props[thr_id].minor == 5) || props[thr_id].major > 3) ? 768 : 512;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
// Größe des dynamischen Shared Memory Bereichs
#if USE_SHARED
size_t shared_size = 8 * 256 * sizeof(uint32_t);
#else
size_t shared_size = 0;
#endif
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
//fprintf(stderr, "ThrID: %d\n", thr_id);
quark_groestl512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector);
quark_groestl512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, order, thr_id);
}

450
quark/cuda_skein512.cu

@ -0,0 +1,450 @@ @@ -0,0 +1,450 @@
#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <memory.h>
// Folgende Definitionen später durch header ersetzen
typedef unsigned char uint8_t;
typedef unsigned int uint32_t;
typedef unsigned long long uint64_t;
#define SPH_C64(x) ((uint64_t)(x ## ULL))
// aus cpu-miner.c
extern "C" extern int device_map[8];
// aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
// Take a look at: https://www.schneier.com/skein1.3.pdf
#if __CUDA_ARCH__ >= 350
__forceinline__ __device__ uint64_t ROTL64(const uint64_t value, const int offset) {
uint2 result;
if(offset >= 32) {
asm("shf.l.wrap.b32 %0, %1, %2, %3;" : "=r"(result.x) : "r"(__double2loint(__longlong_as_double(value))), "r"(__double2hiint(__longlong_as_double(value))), "r"(offset));
asm("shf.l.wrap.b32 %0, %1, %2, %3;" : "=r"(result.y) : "r"(__double2hiint(__longlong_as_double(value))), "r"(__double2loint(__longlong_as_double(value))), "r"(offset));
} else {
asm("shf.l.wrap.b32 %0, %1, %2, %3;" : "=r"(result.x) : "r"(__double2hiint(__longlong_as_double(value))), "r"(__double2loint(__longlong_as_double(value))), "r"(offset));
asm("shf.l.wrap.b32 %0, %1, %2, %3;" : "=r"(result.y) : "r"(__double2loint(__longlong_as_double(value))), "r"(__double2hiint(__longlong_as_double(value))), "r"(offset));
}
return __double_as_longlong(__hiloint2double(result.y, result.x));
}
#else
#define ROTL64(x, n) (((x) << (n)) | ((x) >> (64 - (n))))
#endif
#define SHL(x, n) ((x) << (n))
#define SHR(x, n) ((x) >> (n))
// Zum testen Hostcode...
/* Hier erstmal die Tabelle mit den Konstanten für die Mix-Funktion. Kann später vll.
mal direkt in den Code eingesetzt werden
*/
/*
* M9_ ## s ## _ ## i evaluates to s+i mod 9 (0 <= s <= 18, 0 <= i <= 7).
*/
#define M9_0_0 0
#define M9_0_1 1
#define M9_0_2 2
#define M9_0_3 3
#define M9_0_4 4
#define M9_0_5 5
#define M9_0_6 6
#define M9_0_7 7
#define M9_1_0 1
#define M9_1_1 2
#define M9_1_2 3
#define M9_1_3 4
#define M9_1_4 5
#define M9_1_5 6
#define M9_1_6 7
#define M9_1_7 8
#define M9_2_0 2
#define M9_2_1 3
#define M9_2_2 4
#define M9_2_3 5
#define M9_2_4 6
#define M9_2_5 7
#define M9_2_6 8
#define M9_2_7 0
#define M9_3_0 3
#define M9_3_1 4
#define M9_3_2 5
#define M9_3_3 6
#define M9_3_4 7
#define M9_3_5 8
#define M9_3_6 0
#define M9_3_7 1
#define M9_4_0 4
#define M9_4_1 5
#define M9_4_2 6
#define M9_4_3 7
#define M9_4_4 8
#define M9_4_5 0
#define M9_4_6 1
#define M9_4_7 2
#define M9_5_0 5
#define M9_5_1 6
#define M9_5_2 7
#define M9_5_3 8
#define M9_5_4 0
#define M9_5_5 1
#define M9_5_6 2
#define M9_5_7 3
#define M9_6_0 6
#define M9_6_1 7
#define M9_6_2 8
#define M9_6_3 0
#define M9_6_4 1
#define M9_6_5 2
#define M9_6_6 3
#define M9_6_7 4
#define M9_7_0 7
#define M9_7_1 8
#define M9_7_2 0
#define M9_7_3 1
#define M9_7_4 2
#define M9_7_5 3
#define M9_7_6 4
#define M9_7_7 5
#define M9_8_0 8
#define M9_8_1 0
#define M9_8_2 1
#define M9_8_3 2
#define M9_8_4 3
#define M9_8_5 4
#define M9_8_6 5
#define M9_8_7 6
#define M9_9_0 0
#define M9_9_1 1
#define M9_9_2 2
#define M9_9_3 3
#define M9_9_4 4
#define M9_9_5 5
#define M9_9_6 6
#define M9_9_7 7
#define M9_10_0 1
#define M9_10_1 2
#define M9_10_2 3
#define M9_10_3 4
#define M9_10_4 5
#define M9_10_5 6
#define M9_10_6 7
#define M9_10_7 8
#define M9_11_0 2
#define M9_11_1 3
#define M9_11_2 4
#define M9_11_3 5
#define M9_11_4 6
#define M9_11_5 7
#define M9_11_6 8
#define M9_11_7 0
#define M9_12_0 3
#define M9_12_1 4
#define M9_12_2 5
#define M9_12_3 6
#define M9_12_4 7
#define M9_12_5 8
#define M9_12_6 0
#define M9_12_7 1
#define M9_13_0 4
#define M9_13_1 5
#define M9_13_2 6
#define M9_13_3 7
#define M9_13_4 8
#define M9_13_5 0
#define M9_13_6 1
#define M9_13_7 2
#define M9_14_0 5
#define M9_14_1 6
#define M9_14_2 7
#define M9_14_3 8
#define M9_14_4 0
#define M9_14_5 1
#define M9_14_6 2
#define M9_14_7 3
#define M9_15_0 6
#define M9_15_1 7
#define M9_15_2 8
#define M9_15_3 0
#define M9_15_4 1
#define M9_15_5 2
#define M9_15_6 3
#define M9_15_7 4
#define M9_16_0 7
#define M9_16_1 8
#define M9_16_2 0
#define M9_16_3 1
#define M9_16_4 2
#define M9_16_5 3
#define M9_16_6 4
#define M9_16_7 5
#define M9_17_0 8
#define M9_17_1 0
#define M9_17_2 1
#define M9_17_3 2
#define M9_17_4 3
#define M9_17_5 4
#define M9_17_6 5
#define M9_17_7 6
#define M9_18_0 0
#define M9_18_1 1
#define M9_18_2 2
#define M9_18_3 3
#define M9_18_4 4
#define M9_18_5 5
#define M9_18_6 6
#define M9_18_7 7
/*
* M3_ ## s ## _ ## i evaluates to s+i mod 3 (0 <= s <= 18, 0 <= i <= 1).
*/
#define M3_0_0 0
#define M3_0_1 1
#define M3_1_0 1
#define M3_1_1 2
#define M3_2_0 2
#define M3_2_1 0
#define M3_3_0 0
#define M3_3_1 1
#define M3_4_0 1
#define M3_4_1 2
#define M3_5_0 2
#define M3_5_1 0
#define M3_6_0 0
#define M3_6_1 1
#define M3_7_0 1
#define M3_7_1 2
#define M3_8_0 2
#define M3_8_1 0
#define M3_9_0 0
#define M3_9_1 1
#define M3_10_0 1
#define M3_10_1 2
#define M3_11_0 2
#define M3_11_1 0
#define M3_12_0 0
#define M3_12_1 1
#define M3_13_0 1
#define M3_13_1 2
#define M3_14_0 2
#define M3_14_1 0
#define M3_15_0 0
#define M3_15_1 1
#define M3_16_0 1
#define M3_16_1 2
#define M3_17_0 2
#define M3_17_1 0
#define M3_18_0 0
#define M3_18_1 1
#define XCAT(x, y) XCAT_(x, y)
#define XCAT_(x, y) x ## y
#define SKBI(k, s, i) XCAT(k, XCAT(XCAT(XCAT(M9_, s), _), i))
#define SKBT(t, s, v) XCAT(t, XCAT(XCAT(XCAT(M3_, s), _), v))
#define TFBIG_KINIT(k0, k1, k2, k3, k4, k5, k6, k7, k8, t0, t1, t2) { \
k8 = ((k0 ^ k1) ^ (k2 ^ k3)) ^ ((k4 ^ k5) ^ (k6 ^ k7)) \
^ SPH_C64(0x1BD11BDAA9FC1A22); \
t2 = t0 ^ t1; \
}
#define TFBIG_ADDKEY(w0, w1, w2, w3, w4, w5, w6, w7, k, t, s) { \
w0 = (w0 + SKBI(k, s, 0)); \
w1 = (w1 + SKBI(k, s, 1)); \
w2 = (w2 + SKBI(k, s, 2)); \
w3 = (w3 + SKBI(k, s, 3)); \
w4 = (w4 + SKBI(k, s, 4)); \
w5 = (w5 + SKBI(k, s, 5) + SKBT(t, s, 0)); \
w6 = (w6 + SKBI(k, s, 6) + SKBT(t, s, 1)); \
w7 = (w7 + SKBI(k, s, 7) + (uint64_t)s); \
}
#define TFBIG_MIX(x0, x1, rc) { \
x0 = x0 + x1; \
x1 = ROTL64(x1, rc) ^ x0; \
}
#define TFBIG_MIX8(w0, w1, w2, w3, w4, w5, w6, w7, rc0, rc1, rc2, rc3) { \
TFBIG_MIX(w0, w1, rc0); \
TFBIG_MIX(w2, w3, rc1); \
TFBIG_MIX(w4, w5, rc2); \
TFBIG_MIX(w6, w7, rc3); \
}
#define TFBIG_4e(s) { \
TFBIG_ADDKEY(p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], h, t, s); \
TFBIG_MIX8(p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], 46, 36, 19, 37); \
TFBIG_MIX8(p[2], p[1], p[4], p[7], p[6], p[5], p[0], p[3], 33, 27, 14, 42); \
TFBIG_MIX8(p[4], p[1], p[6], p[3], p[0], p[5], p[2], p[7], 17, 49, 36, 39); \
TFBIG_MIX8(p[6], p[1], p[0], p[7], p[2], p[5], p[4], p[3], 44, 9, 54, 56); \
}
#define TFBIG_4o(s) { \
TFBIG_ADDKEY(p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], h, t, s); \
TFBIG_MIX8(p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], 39, 30, 34, 24); \
TFBIG_MIX8(p[2], p[1], p[4], p[7], p[6], p[5], p[0], p[3], 13, 50, 10, 17); \
TFBIG_MIX8(p[4], p[1], p[6], p[3], p[0], p[5], p[2], p[7], 25, 29, 39, 43); \
TFBIG_MIX8(p[6], p[1], p[0], p[7], p[2], p[5], p[4], p[3], 8, 35, 56, 22); \
}
static __constant__ uint64_t d_constMem[8];
static uint64_t h_constMem[8] = {
SPH_C64(0x4903ADFF749C51CE),
SPH_C64(0x0D95DE399746DF03),
SPH_C64(0x8FD1934127C79BCE),
SPH_C64(0x9A255629FF352CB1),
SPH_C64(0x5DB62599DF6CA7B0),
SPH_C64(0xEABE394CA9D5C3F4),
SPH_C64(0x991112C71A75B523),
SPH_C64(0xAE18A40B660FCC33) };
__global__ void quark_skein512_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)
{
// Skein
uint64_t p[8];
uint64_t h0, h1, h2, h3, h4, h5, h6, h7, h8;
uint64_t t0, t1, t2;
uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
uint64_t *inpHash = &g_hash[8 * hashPosition];
// Initialisierung
h0 = d_constMem[0];
h1 = d_constMem[1];
h2 = d_constMem[2];
h3 = d_constMem[3];
h4 = d_constMem[4];
h5 = d_constMem[5];
h6 = d_constMem[6];
h7 = d_constMem[7];
// 1. Runde -> etype = 480, ptr = 64, bcount = 0, data = msg
#pragma unroll 8
for(int i=0;i<8;i++)
p[i] = inpHash[i];
t0 = 64; // ptr
t1 = 480ull << 55; // etype
TFBIG_KINIT(h0, h1, h2, h3, h4, h5, h6, h7, h8, t0, t1, t2);
TFBIG_4e(0);
TFBIG_4o(1);
TFBIG_4e(2);
TFBIG_4o(3);
TFBIG_4e(4);
TFBIG_4o(5);
TFBIG_4e(6);
TFBIG_4o(7);
TFBIG_4e(8);
TFBIG_4o(9);
TFBIG_4e(10);
TFBIG_4o(11);
TFBIG_4e(12);
TFBIG_4o(13);
TFBIG_4e(14);
TFBIG_4o(15);
TFBIG_4e(16);
TFBIG_4o(17);
TFBIG_ADDKEY(p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], h, t, 18);
h0 = inpHash[0] ^ p[0];
h1 = inpHash[1] ^ p[1];
h2 = inpHash[2] ^ p[2];
h3 = inpHash[3] ^ p[3];
h4 = inpHash[4] ^ p[4];
h5 = inpHash[5] ^ p[5];
h6 = inpHash[6] ^ p[6];
h7 = inpHash[7] ^ p[7];
// 2. Runde -> etype = 510, ptr = 8, bcount = 0, data = 0
#pragma unroll 8
for(int i=0;i<8;i++)
p[i] = 0;
t0 = 8; // ptr
t1 = 510ull << 55; // etype
TFBIG_KINIT(h0, h1, h2, h3, h4, h5, h6, h7, h8, t0, t1, t2);
TFBIG_4e(0);
TFBIG_4o(1);
TFBIG_4e(2);
TFBIG_4o(3);
TFBIG_4e(4);
TFBIG_4o(5);
TFBIG_4e(6);
TFBIG_4o(7);
TFBIG_4e(8);
TFBIG_4o(9);
TFBIG_4e(10);
TFBIG_4o(11);
TFBIG_4e(12);
TFBIG_4o(13);
TFBIG_4e(14);
TFBIG_4o(15);
TFBIG_4e(16);
TFBIG_4o(17);
TFBIG_ADDKEY(p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], h, t, 18);
// fertig
uint64_t *outpHash = &g_hash[8 * hashPosition];
#pragma unroll 8
for(int i=0;i<8;i++)
outpHash[i] = p[i];
}
}
// Setup-Funktionen
__host__ void quark_skein512_cpu_init(int thr_id, int threads)
{
// nix zu tun ;-)
cudaMemcpyToSymbol( d_constMem,
h_constMem,
sizeof(h_constMem),
0, cudaMemcpyHostToDevice);
}
__host__ void quark_skein512_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;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
quark_skein512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, order, thr_id);
}
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