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lyra2v2: improve cubehash with uint2

master
Tanguy Pruvot 9 years ago
parent
6e64383b32
commit
8f98bde4fb
3 changed files with 84 additions and 25 deletions
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  1. 85
      Algo256/cuda_cubehash256.cu
  2. 2
      configure.ac
  3. 22
      lyra2/cuda_lyra2v2.cu

85
Algo256/cuda_cubehash256.cu
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@ -9,6 +9,12 @@
#define LROT(x, bits) __funnelshift_l(x, x, bits) #define LROT(x, bits) __funnelshift_l(x, x, bits)
#endif #endif
#if __CUDA_ARCH__ < 500
#define TPB 576
#else
#define TPB 1024
#endif
#define ROTATEUPWARDS7(a) LROT(a,7) #define ROTATEUPWARDS7(a) LROT(a,7)
#define ROTATEUPWARDS11(a) LROT(a,11) #define ROTATEUPWARDS11(a) LROT(a,11)
@ -186,19 +192,65 @@ void Final(uint32_t x[2][2][2][2][2], uint32_t *hashval)
hash_fromx(hashval, x); hash_fromx(hashval, x);
} }
#if __CUDA_ARCH__ >= 500
__global__ __launch_bounds__(TPB, 1)
void cubehash256_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *g_hash)
{
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint2 Hash[4];
Hash[0] = __ldg(&g_hash[thread]);
Hash[1] = __ldg(&g_hash[thread + 1 * threads]);
Hash[2] = __ldg(&g_hash[thread + 2 * threads]);
Hash[3] = __ldg(&g_hash[thread + 3 * threads]);
uint32_t x[2][2][2][2][2] =
{
0xEA2BD4B4, 0xCCD6F29F, 0x63117E71, 0x35481EAE,
0x22512D5B, 0xE5D94E63, 0x7E624131, 0xF4CC12BE,
0xC2D0B696, 0x42AF2070, 0xD0720C35, 0x3361DA8C,
0x28CCECA4, 0x8EF8AD83, 0x4680AC00, 0x40E5FBAB,
0xD89041C3, 0x6107FBD5, 0x6C859D41, 0xF0B26679,
0x09392549, 0x5FA25603, 0x65C892FD, 0x93CB6285,
0x2AF2B5AE, 0x9E4B4E60, 0x774ABFDD, 0x85254725,
0x15815AEB, 0x4AB6AAD6, 0x9CDAF8AF, 0xD6032C0A
};
x[0][0][0][0][0] ^= Hash[0].x;
x[0][0][0][0][1] ^= Hash[0].y;
x[0][0][0][1][0] ^= Hash[1].x;
x[0][0][0][1][1] ^= Hash[1].y;
x[0][0][1][0][0] ^= Hash[2].x;
x[0][0][1][0][1] ^= Hash[2].y;
x[0][0][1][1][0] ^= Hash[3].x;
x[0][0][1][1][1] ^= Hash[3].y;
rrounds(x);
x[0][0][0][0][0] ^= 0x80U;
rrounds(x);
Final(x, (uint32_t*) Hash);
g_hash[thread] = Hash[0];
g_hash[1 * threads + thread] = Hash[1];
g_hash[2 * threads + thread] = Hash[2];
g_hash[3 * threads + thread] = Hash[3];
}
}
// Die Hash-Funktion
#if __CUDA_ARCH__ <500
__global__ __launch_bounds__(576,1)
#else #else
__global__ __launch_bounds__(576,1)
#endif __global__ __launch_bounds__(TPB, 1)
void cubehash256_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint64_t *g_hash) void cubehash256_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *d_hash)
{ {
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x); uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads) if (thread < threads)
{ {
uint32_t Hash[8]; // = &g_hash[16 * hashPosition]; uint32_t Hash[8];
uint64_t* g_hash = (uint64_t*) d_hash;
LOHI(Hash[0], Hash[1], __ldg(&g_hash[thread])); LOHI(Hash[0], Hash[1], __ldg(&g_hash[thread]));
LOHI(Hash[2], Hash[3], __ldg(&g_hash[thread + 1 * threads])); LOHI(Hash[2], Hash[3], __ldg(&g_hash[thread + 1 * threads]));
@ -207,7 +259,7 @@ void cubehash256_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint64_t *g
uint32_t x[2][2][2][2][2] = uint32_t x[2][2][2][2][2] =
{ {
0xEA2BD4B4, 0xCCD6F29F, 0x63117E71, 0x35481EAE, 0xEA2BD4B4, 0xCCD6F29F, 0x63117E71, 0x35481EAE,
0x22512D5B, 0xE5D94E63, 0x7E624131, 0xF4CC12BE, 0x22512D5B, 0xE5D94E63, 0x7E624131, 0xF4CC12BE,
0xC2D0B696, 0x42AF2070, 0xD0720C35, 0x3361DA8C, 0xC2D0B696, 0x42AF2070, 0xD0720C35, 0x3361DA8C,
0x28CCECA4, 0x8EF8AD83, 0x4680AC00, 0x40E5FBAB, 0x28CCECA4, 0x8EF8AD83, 0x4680AC00, 0x40E5FBAB,
@ -236,17 +288,18 @@ void cubehash256_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint64_t *g
g_hash[1 * threads + thread] = ((uint64_t*)Hash)[1]; g_hash[1 * threads + thread] = ((uint64_t*)Hash)[1];
g_hash[2 * threads + thread] = ((uint64_t*)Hash)[2]; g_hash[2 * threads + thread] = ((uint64_t*)Hash)[2];
g_hash[3 * threads + thread] = ((uint64_t*)Hash)[3]; g_hash[3 * threads + thread] = ((uint64_t*)Hash)[3];
} }
} }
#endif
__host__ __host__
void cubehash256_cpu_hash_32(int thr_id, uint32_t threads, uint32_t startNounce, uint64_t *d_hash, int order) void cubehash256_cpu_hash_32(int thr_id, uint32_t threads, uint32_t startNounce, uint64_t *d_hash, int order)
{ {
uint32_t tpb = 576; uint32_t tpb = TPB;
dim3 grid((threads + tpb-1)/tpb); dim3 grid((threads + tpb-1)/tpb);
dim3 block(tpb); dim3 block(tpb);
cubehash256_gpu_hash_32 <<<grid, block>>> (threads, startNounce, d_hash); cubehash256_gpu_hash_32 <<<grid, block>>> (threads, startNounce, (uint2*) d_hash);
} }

2
configure.ac
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@ -1,4 +1,4 @@
AC_INIT([ccminer], [1.6.6]) AC_INIT([ccminer], [1.6.7-dev])
AC_PREREQ([2.59c]) AC_PREREQ([2.59c])
AC_CANONICAL_SYSTEM AC_CANONICAL_SYSTEM

22
lyra2/cuda_lyra2v2.cu
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@ -78,12 +78,16 @@ void reduceDuplex(vectype state[4], uint32_t thread)
uint32_t s1 = ps1 + i*memshift; uint32_t s1 = ps1 + i*memshift;
uint32_t s2 = ps2 - i*memshift; uint32_t s2 = ps2 - i*memshift;
#pragma unroll
for (int j = 0; j < 3; j++) for (int j = 0; j < 3; j++)
state1[j] = __ldg4(&(DMatrix+s1)[j]); state1[j] = __ldg4(&(DMatrix+s1)[j]);
for (int j = 0; j < 3; j++) for (int j = 0; j < 3; j++)
state[j] ^= state1[j]; state[j] ^= state1[j];
round_lyra_v35(state); round_lyra_v35(state);
#pragma unroll
for (int j = 0; j < 3; j++) for (int j = 0; j < 3; j++)
state1[j] ^= state[j]; state1[j] ^= state[j];
@ -353,6 +357,7 @@ void lyra2v2_gpu_hash_32_v3(uint32_t threads, uint32_t startNounce, uint2 *outpu
for (int i = 0; i<12; i++) for (int i = 0; i<12; i++)
round_lyra_v35(state); round_lyra_v35(state);
state[0] ^= shuffle4(((vectype*)padding)[0], 0); state[0] ^= shuffle4(((vectype*)padding)[0], 0);
state[1] ^= shuffle4(((vectype*)padding)[1], 0); state[1] ^= shuffle4(((vectype*)padding)[1], 0);
@ -417,14 +422,14 @@ void lyra2v2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *outputHa
if (threadIdx.x == 0) { if (threadIdx.x == 0) {
((uint16*)blake2b_IV)[0] = make_uint16( ((uint16*)blake2b_IV)[0] = make_uint16(
0xf3bcc908, 0x6a09e667 , 0x84caa73b, 0xbb67ae85 , 0xf3bcc908, 0x6a09e667, 0x84caa73b, 0xbb67ae85,
0xfe94f82b, 0x3c6ef372 , 0x5f1d36f1, 0xa54ff53a , 0xfe94f82b, 0x3c6ef372, 0x5f1d36f1, 0xa54ff53a,
0xade682d1, 0x510e527f , 0x2b3e6c1f, 0x9b05688c , 0xade682d1, 0x510e527f, 0x2b3e6c1f, 0x9b05688c,
0xfb41bd6b, 0x1f83d9ab , 0x137e2179, 0x5be0cd19 0xfb41bd6b, 0x1f83d9ab, 0x137e2179, 0x5be0cd19
); );
((uint16*)padding)[0] = make_uint16( ((uint16*)padding)[0] = make_uint16(
0x20, 0x0 , 0x20, 0x0 , 0x20, 0x0 , 0x01, 0x0 , 0x20, 0x0, 0x20, 0x0, 0x20, 0x0, 0x01, 0x0,
0x04, 0x0 , 0x04, 0x0 , 0x80, 0x0 , 0x0, 0x01000000 0x04, 0x0, 0x04, 0x0, 0x80, 0x0, 0x0, 0x01000000
); );
} }
@ -497,9 +502,10 @@ __global__ void lyra2v2_gpu_hash_32_v3(uint32_t threads, uint32_t startNounce, u
#endif #endif
__host__ __host__
void lyra2v2_cpu_init(int thr_id, uint32_t threads,uint64_t *hash) void lyra2v2_cpu_init(int thr_id, uint32_t threads, uint64_t *d_hash2)
{ {
cudaMemcpyToSymbol(DMatrix, &hash, sizeof(hash), 0, cudaMemcpyHostToDevice); // just assign the device pointer allocated in main loop
cudaMemcpyToSymbol(DMatrix, &d_hash2, sizeof(uint64_t*), 0, cudaMemcpyHostToDevice);
} }
__host__ __host__

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