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lyra2: support for SM 2.1 cards (GTX 460)

also fix the build (scrypt) for this arch.

else, 318,26 kH/s on a GTX 460...
master
Tanguy Pruvot 9 years ago
parent
commit
8fd2739a65
  1. 18
      lyra2/cuda_lyra2.cu
  2. 225
      lyra2/cuda_lyra2_sm2.cuh
  3. 11
      lyra2/cuda_lyra2v2.cu
  4. 3
      lyra2/lyra2RE.cu
  5. 5
      scrypt/nv_kernel2.cu
  6. 4
      scrypt/titan_kernel.cu

18
lyra2/cuda_lyra2.cu

@ -6,11 +6,15 @@
#include <stdio.h> #include <stdio.h>
#include <memory.h> #include <memory.h>
#include "cuda_lyra2_vectors.h"
#define TPB50 16 #define TPB50 16
#define TPB52 8 #define TPB52 8
#include "cuda_lyra2_sm2.cuh"
#if !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 500
#include "cuda_lyra2_vectors.h"
#define uint2x4 uint28 #define uint2x4 uint28
#define memshift 3 #define memshift 3
@ -238,6 +242,11 @@ void lyra2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *g_hash)
g_hash[thread + threads*3] = ((uint2*)state)[3]; g_hash[thread + threads*3] = ((uint2*)state)[3];
} }
} }
#else
/* for unsupported SM arch */
__device__ void* DMatrix;
__global__ void lyra2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *g_hash) {}
#endif
__host__ __host__
void lyra2_cpu_init(int thr_id, uint32_t threads, uint64_t* d_matrix) void lyra2_cpu_init(int thr_id, uint32_t threads, uint64_t* d_matrix)
@ -252,9 +261,14 @@ void lyra2_cpu_hash_32(int thr_id, uint32_t threads, uint32_t startNounce, uint6
int dev_id = device_map[thr_id % MAX_GPUS]; int dev_id = device_map[thr_id % MAX_GPUS];
uint32_t tpb = TPB52; uint32_t tpb = TPB52;
if (device_sm[dev_id] == 500) tpb = TPB50; if (device_sm[dev_id] == 500) tpb = TPB50;
if (device_sm[dev_id] <= 300) tpb = TPB30;
dim3 grid((threads + tpb - 1) / tpb); dim3 grid((threads + tpb - 1) / tpb);
dim3 block(tpb); dim3 block(tpb);
if (device_sm[dev_id] >= 500)
lyra2_gpu_hash_32 <<< grid, block >>> (threads, startNounce, (uint2*)d_hash); lyra2_gpu_hash_32 <<< grid, block >>> (threads, startNounce, (uint2*)d_hash);
else
lyra2_gpu_hash_32_sm2 <<< grid, block >>> (threads, startNounce, d_hash);
} }

225
lyra2/cuda_lyra2_sm2.cuh

@ -0,0 +1,225 @@
#include <memory.h>
#ifdef __INTELLISENSE__
/* just for vstudio code colors */
#undef __CUDA_ARCH__
#define __CUDA_ARCH__ 300
#endif
#include "cuda_helper.h"
#define TPB30 160
#if __CUDA_ARCH__ >= 200 && __CUDA_ARCH__ <= 350
static __constant__ uint2 blake2b_IV[8] = {
{ 0xf3bcc908, 0x6a09e667 },
{ 0x84caa73b, 0xbb67ae85 },
{ 0xfe94f82b, 0x3c6ef372 },
{ 0x5f1d36f1, 0xa54ff53a },
{ 0xade682d1, 0x510e527f },
{ 0x2b3e6c1f, 0x9b05688c },
{ 0xfb41bd6b, 0x1f83d9ab },
{ 0x137e2179, 0x5be0cd19 }
};
#define reduceDuplexRow(rowIn, rowInOut, rowOut) { \
for (int i = 0; i < 8; i++) { \
for (int j = 0; j < 12; j++) \
state[j] ^= Matrix[12 * i + j][rowIn] + Matrix[12 * i + j][rowInOut]; \
round_lyra(state); \
for (int j = 0; j < 12; j++) \
Matrix[j + 12 * i][rowOut] ^= state[j]; \
Matrix[0 + 12 * i][rowInOut] ^= state[11]; \
Matrix[1 + 12 * i][rowInOut] ^= state[0]; \
Matrix[2 + 12 * i][rowInOut] ^= state[1]; \
Matrix[3 + 12 * i][rowInOut] ^= state[2]; \
Matrix[4 + 12 * i][rowInOut] ^= state[3]; \
Matrix[5 + 12 * i][rowInOut] ^= state[4]; \
Matrix[6 + 12 * i][rowInOut] ^= state[5]; \
Matrix[7 + 12 * i][rowInOut] ^= state[6]; \
Matrix[8 + 12 * i][rowInOut] ^= state[7]; \
Matrix[9 + 12 * i][rowInOut] ^= state[8]; \
Matrix[10+ 12 * i][rowInOut] ^= state[9]; \
Matrix[11+ 12 * i][rowInOut] ^= state[10]; \
} \
}
#define absorbblock(in) { \
state[0] ^= Matrix[0][in]; \
state[1] ^= Matrix[1][in]; \
state[2] ^= Matrix[2][in]; \
state[3] ^= Matrix[3][in]; \
state[4] ^= Matrix[4][in]; \
state[5] ^= Matrix[5][in]; \
state[6] ^= Matrix[6][in]; \
state[7] ^= Matrix[7][in]; \
state[8] ^= Matrix[8][in]; \
state[9] ^= Matrix[9][in]; \
state[10] ^= Matrix[10][in]; \
state[11] ^= Matrix[11][in]; \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
round_lyra(state); \
}
static __device__ __forceinline__
void Gfunc(uint2 & a, uint2 &b, uint2 &c, uint2 &d)
{
a += b; d ^= a; d = SWAPUINT2(d);
c += d; b ^= c; b = ROR2(b, 24);
a += b; d ^= a; d = ROR2(d, 16);
c += d; b ^= c; b = ROR2(b, 63);
}
__device__ __forceinline__
static void round_lyra(uint2 *s)
{
Gfunc(s[0], s[4], s[8], s[12]);
Gfunc(s[1], s[5], s[9], s[13]);
Gfunc(s[2], s[6], s[10], s[14]);
Gfunc(s[3], s[7], s[11], s[15]);
Gfunc(s[0], s[5], s[10], s[15]);
Gfunc(s[1], s[6], s[11], s[12]);
Gfunc(s[2], s[7], s[8], s[13]);
Gfunc(s[3], s[4], s[9], s[14]);
}
__device__ __forceinline__
void reduceDuplexRowSetup(const int rowIn, const int rowInOut, const int rowOut, uint2 state[16], uint2 Matrix[96][8])
{
#if __CUDA_ARCH__ > 500
#pragma unroll
#endif
for (int i = 0; i < 8; i++)
{
#pragma unroll
for (int j = 0; j < 12; j++)
state[j] ^= Matrix[12 * i + j][rowIn] + Matrix[12 * i + j][rowInOut];
round_lyra(state);
#pragma unroll
for (int j = 0; j < 12; j++)
Matrix[j + 84 - 12 * i][rowOut] = Matrix[12 * i + j][rowIn] ^ state[j];
Matrix[0 + 12 * i][rowInOut] ^= state[11];
Matrix[1 + 12 * i][rowInOut] ^= state[0];
Matrix[2 + 12 * i][rowInOut] ^= state[1];
Matrix[3 + 12 * i][rowInOut] ^= state[2];
Matrix[4 + 12 * i][rowInOut] ^= state[3];
Matrix[5 + 12 * i][rowInOut] ^= state[4];
Matrix[6 + 12 * i][rowInOut] ^= state[5];
Matrix[7 + 12 * i][rowInOut] ^= state[6];
Matrix[8 + 12 * i][rowInOut] ^= state[7];
Matrix[9 + 12 * i][rowInOut] ^= state[8];
Matrix[10 + 12 * i][rowInOut] ^= state[9];
Matrix[11 + 12 * i][rowInOut] ^= state[10];
}
}
__global__ __launch_bounds__(TPB30, 1)
void lyra2_gpu_hash_32_sm2(uint32_t threads, uint32_t startNounce, uint64_t *g_hash)
{
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint2 state[16];
#pragma unroll
for (int i = 0; i<4; i++) {
LOHI(state[i].x, state[i].y, g_hash[threads*i + thread]);
} //password
#pragma unroll
for (int i = 0; i<4; i++) {
state[i + 4] = state[i];
} //salt
#pragma unroll
for (int i = 0; i<8; i++) {
state[i + 8] = blake2b_IV[i];
}
// blake2blyra x2
//#pragma unroll 24
for (int i = 0; i<24; i++) {
round_lyra(state);
} //because 12 is not enough
uint2 Matrix[96][8]; // not cool
// reducedSqueezeRow0
#pragma unroll 8
for (int i = 0; i < 8; i++)
{
#pragma unroll 12
for (int j = 0; j<12; j++) {
Matrix[j + 84 - 12 * i][0] = state[j];
}
round_lyra(state);
}
// reducedSqueezeRow1
#pragma unroll 8
for (int i = 0; i < 8; i++)
{
#pragma unroll 12
for (int j = 0; j<12; j++) {
state[j] ^= Matrix[j + 12 * i][0];
}
round_lyra(state);
#pragma unroll 12
for (int j = 0; j<12; j++) {
Matrix[j + 84 - 12 * i][1] = Matrix[j + 12 * i][0] ^ state[j];
}
}
reduceDuplexRowSetup(1, 0, 2, state, Matrix);
reduceDuplexRowSetup(2, 1, 3, state, Matrix);
reduceDuplexRowSetup(3, 0, 4, state, Matrix);
reduceDuplexRowSetup(4, 3, 5, state, Matrix);
reduceDuplexRowSetup(5, 2, 6, state, Matrix);
reduceDuplexRowSetup(6, 1, 7, state, Matrix);
uint32_t rowa;
rowa = state[0].x & 7;
reduceDuplexRow(7, rowa, 0);
rowa = state[0].x & 7;
reduceDuplexRow(0, rowa, 3);
rowa = state[0].x & 7;
reduceDuplexRow(3, rowa, 6);
rowa = state[0].x & 7;
reduceDuplexRow(6, rowa, 1);
rowa = state[0].x & 7;
reduceDuplexRow(1, rowa, 4);
rowa = state[0].x & 7;
reduceDuplexRow(4, rowa, 7);
rowa = state[0].x & 7;
reduceDuplexRow(7, rowa, 2);
rowa = state[0].x & 7;
reduceDuplexRow(2, rowa, 5);
absorbblock(rowa);
#pragma unroll
for (int i = 0; i<4; i++) {
g_hash[threads*i + thread] = devectorize(state[i]);
}
} //thread
}
#else
/* if __CUDA_ARCH__ < 200 .. host */
__global__ void lyra2_gpu_hash_32_sm2(uint32_t threads, uint32_t startNounce, uint64_t *g_hash) {}
#endif

11
lyra2/cuda_lyra2v2.cu

@ -1,4 +1,5 @@
#include <stdio.h> #include <stdio.h>
#include <stdint.h>
#include <memory.h> #include <memory.h>
#ifdef __INTELLISENSE__ #ifdef __INTELLISENSE__
@ -9,16 +10,12 @@
#define TPB52 10 #define TPB52 10
#define TPB50 16 #define TPB50 16
#include "cuda_lyra2_vectors.h"
#include "cuda_lyra2v2_sm3.cuh" #include "cuda_lyra2v2_sm3.cuh"
#ifndef __CUDA_ARCH__
__device__ void *DMatrix;
#endif
#if __CUDA_ARCH__ >= 500 #if __CUDA_ARCH__ >= 500
#include "cuda_lyra2_vectors.h"
#define Nrow 4 #define Nrow 4
#define Ncol 4 #define Ncol 4
#define u64type uint2 #define u64type uint2
@ -346,6 +343,8 @@ void lyra2v2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *outputHa
} }
} }
#else #else
#include "cuda_helper.h"
__device__ void* DMatrix;
__global__ void lyra2v2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *outputHash) {} __global__ void lyra2v2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *outputHash) {}
#endif #endif

3
lyra2/lyra2RE.cu

@ -15,6 +15,7 @@ static uint64_t* d_matrix[MAX_GPUS];
extern void blake256_cpu_init(int thr_id, uint32_t threads); extern void blake256_cpu_init(int thr_id, uint32_t threads);
extern void blake256_cpu_hash_80(const int thr_id, const uint32_t threads, const uint32_t startNonce, uint64_t *Hash, int order); extern void blake256_cpu_hash_80(const int thr_id, const uint32_t threads, const uint32_t startNonce, uint64_t *Hash, int order);
extern void blake256_cpu_setBlock_80(uint32_t *pdata); extern void blake256_cpu_setBlock_80(uint32_t *pdata);
extern void keccak256_cpu_hash_32(int thr_id, uint32_t threads, uint32_t startNonce, uint64_t *d_outputHash, int order); extern void keccak256_cpu_hash_32(int thr_id, uint32_t threads, uint32_t startNonce, uint64_t *d_outputHash, int order);
extern void keccak256_cpu_init(int thr_id, uint32_t threads); extern void keccak256_cpu_init(int thr_id, uint32_t threads);
extern void keccak256_cpu_free(int thr_id); extern void keccak256_cpu_free(int thr_id);
@ -110,7 +111,7 @@ extern "C" int scanhash_lyra2(int thr_id, struct work* work, uint32_t max_nonce,
init[thr_id] = true; init[thr_id] = true;
} }
uint32_t endiandata[20]; uint32_t _ALIGN(128) endiandata[20];
for (int k=0; k < 20; k++) for (int k=0; k < 20; k++)
be32enc(&endiandata[k], pdata[k]); be32enc(&endiandata[k], pdata[k]);

5
scrypt/nv_kernel2.cu

@ -24,6 +24,8 @@
#define __ldg(x) (*(x)) #define __ldg(x) (*(x))
#endif #endif
#if !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 300
// grab lane ID // grab lane ID
static __device__ __inline__ unsigned int __laneId() { unsigned int laneId; asm( "mov.u32 %0, %%laneid;" : "=r"( laneId ) ); return laneId; } static __device__ __inline__ unsigned int __laneId() { unsigned int laneId; asm( "mov.u32 %0, %%laneid;" : "=r"( laneId ) ); return laneId; }
@ -635,3 +637,6 @@ template <int ALGO> __global__ void nv2_scrypt_core_kernelB_LG(uint32_t *g_odata
__transposed_write_BC(B, C, (uint4*)(g_odata), 1); __transposed_write_BC(B, C, (uint4*)(g_odata), 1);
} }
#endif /* prevent SM 2 */

4
scrypt/titan_kernel.cu

@ -28,6 +28,8 @@ typedef enum
#define __ldg(x) (*(x)) #define __ldg(x) (*(x))
#endif #endif
#if !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 300
// scratchbuf constants (pointers to scratch buffer for each warp, i.e. 32 hashes) // scratchbuf constants (pointers to scratch buffer for each warp, i.e. 32 hashes)
__constant__ uint32_t* c_V[TOTAL_WARP_LIMIT]; __constant__ uint32_t* c_V[TOTAL_WARP_LIMIT];
@ -736,3 +738,5 @@ bool TitanKernel::run_kernel(dim3 grid, dim3 threads, int WARPS_PER_BLOCK, int t
return success; return success;
} }
#endif /* prevent SM 2 */

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