GOSTSec
/
ccminer
mirror of https://github.com/GOSTSec/ccminer
1
0
Fork 0
Code Issues Releases Wiki Activity
Browse Source

simd: then reindent the code 

no changes, only error checks (cuda safe call)
2upstream
Tanguy Pruvot 10 years ago
parent
b465fe6825
commit
93f4409dde
2 changed files with 457 additions and 461 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 193
      x11/cuda_x11_simd512.cu
  2. 1
      x11/x11.cu

193
x11/cuda_x11_simd512.cu
Unescape View File

@ -1,13 +1,14 @@
// Parallelisierung: // Parallelization:
// //
// FFT_8 wird 2 mal 8-fach parallel ausgeführt (in FFT_64) // FFT_8 wird 2 times 8-fach parallel ausgeführt (in FFT_64)
// und 1 mal 16-fach parallel (in FFT_128_full) // and 1 time 16-fach parallel (in FFT_128_full)
// //
// STEP8_IF und STEP8_MAJ beinhalten je zwei 8-fach parallele Operationen // STEP8_IF and STEP8_MAJ beinhalten je 2x 8-fach parallel Operations
#define TPB 64 #define TPB 64
#include "cuda_helper.h" #include "cuda_helper.h"
#include <stdio.h>
// aus heavy.cu // aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id); extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
@ -20,14 +21,14 @@ texture<uint4, 1, cudaReadModeElementType> texRef1D_128;
__constant__ uint32_t c_perm[8][8]; __constant__ uint32_t c_perm[8][8];
const uint32_t h_perm[8][8] = { const uint32_t h_perm[8][8] = {
{ 2,3,6,7,0,1,4,5 }, { 2, 3, 6, 7, 0, 1, 4, 5 },
{ 6,7,2,3,4,5,0,1 }, { 6, 7, 2, 3, 4, 5, 0, 1 },
{ 7,6,5,4,3,2,1,0 }, { 7, 6, 5, 4, 3, 2, 1, 0 },
{ 1,0,3,2,5,4,7,6 }, { 1, 0, 3, 2, 5, 4, 7, 6 },
{ 0,1,4,5,6,7,2,3 }, { 0, 1, 4, 5, 6, 7, 2, 3 },
{ 6,7,2,3,0,1,4,5 }, { 6, 7, 2, 3, 0, 1, 4, 5 },
{ 6,7,0,1,4,5,2,3 }, { 6, 7, 0, 1, 4, 5, 2, 3 },
{ 4,5,2,3,6,7,0,1 } { 4, 5, 2, 3, 6, 7, 0, 1 }
}; };
__constant__ uint32_t c_IV_512[32]; __constant__ uint32_t c_IV_512[32];
@ -43,30 +44,30 @@ static const int h_FFT128_8_16_Twiddle[128] = {
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 60, 2, 120, 4, -17, 8, -34, 16, -68, 32, 121, 64, -15, 128, -30, 1, 60, 2, 120, 4, -17, 8, -34, 16, -68, 32, 121, 64, -15, 128, -30,
1, 46, 60, -67, 2, 92, 120, 123, 4, -73, -17, -11, 8, 111, -34, -22, 1, 46, 60, -67, 2, 92, 120, 123, 4, -73, -17, -11, 8, 111, -34, -22,
1, -67, 120, -73, 8, -22, -68, -70, 64, 81, -30, -46, -2, -123, 17, -111, 1, -67, 120, -73, 8, -22, -68, -70, 64, 81, -30, -46, -2,-123, 17,-111,
1, -118, 46, -31, 60, 116, -67, -61, 2, 21, 92, -62, 120, -25, 123, -122, 1,-118, 46, -31, 60, 116, -67, -61, 2, 21, 92, -62, 120, -25, 123,-122,
1, 116, 92, -122, -17, 84, -22, 18, 32, 114, 117, -49, -30, 118, 67, 62, 1, 116, 92,-122, -17, 84, -22, 18, 32, 114, 117, -49, -30, 118, 67, 62,
1, -31, -67, 21, 120, -122, -73, -50, 8, 9, -22, -89, -68, 52, -70, 114, 1, -31, -67, 21, 120, -122, -73, -50, 8, 9, -22, -89, -68, 52, -70, 114,
1, -61, 123, -50, -34, 18, -70, -99, 128, -98, 67, 25, 17, -9, 35, -79 1, -61, 123, -50, -34, 18, -70, -99, 128, -98, 67, 25, 17, -9, 35, -79
}; };
__constant__ int c_FFT256_2_128_Twiddle[128]; __constant__ int c_FFT256_2_128_Twiddle[128];
static const int h_FFT256_2_128_Twiddle[128] = { static const int h_FFT256_2_128_Twiddle[128] = {
1, 41, -118, 45, 46, 87, -31, 14, 1, 41,-118, 45, 46, 87, -31, 14,
60, -110, 116, -127, -67, 80, -61, 69, 60,-110, 116,-127, -67, 80, -61, 69,
2, 82, 21, 90, 92, -83, -62, 28, 2, 82, 21, 90, 92, -83, -62, 28,
120, 37, -25, 3, 123, -97, -122, -119, 120, 37, -25, 3, 123, -97,-122,-119,
4, -93, 42, -77, -73, 91, -124, 56, 4, -93, 42, -77, -73, 91,-124, 56,
-17, 74, -50, 6, -11, 63, 13, 19, -17, 74, -50, 6, -11, 63, 13, 19,
8, 71, 84, 103, 111, -75, 9, 112, 8, 71, 84, 103, 111, -75, 9, 112,
-34, -109, -100, 12, -22, 126, 26, 38, -34,-109,-100, 12, -22, 126, 26, 38,
16, -115, -89, -51, -35, 107, 18, -33, 16,-115, -89, -51, -35, 107, 18, -33,
-68, 39, 57, 24, -44, -5, 52, 76, -68, 39, 57, 24, -44, -5, 52, 76,
32, 27, 79, -102, -70, -43, 36, -66, 32, 27, 79,-102, -70, -43, 36, -66,
121, 78, 114, 48, -88, -10, 104, -105, 121, 78, 114, 48, -88, -10, 104,-105,
64, 54, -99, 53, 117, -86, 72, 125, 64, 54, -99, 53, 117, -86, 72, 125,
-15, -101, -29, 96, 81, -20, -49, 47, -15,-101, -29, 96, 81, -20, -49, 47,
128, 108, 59, 106, -23, 85, -113, -7, 128, 108, 59, 106, -23, 85,-113, -7,
-30, 55, -58, -65, -95, -40, -98, 94 -30, 55, -58, -65, -95, -40, -98, 94
}; };
@ -76,6 +77,7 @@ static const int h_FFT256_2_128_Twiddle[128] = {
#define IF(x, y, z) ((((y) ^ (z)) & (x)) ^ (z)) #define IF(x, y, z) ((((y) ^ (z)) & (x)) ^ (z))
#define MAJ(x, y, z) (((z) & (y)) | (((z) | (y)) & (x))) #define MAJ(x, y, z) (((z) & (y)) | (((z) | (y)) & (x)))
#include "x11/simd_functions.cu" #include "x11/simd_functions.cu"
/********************* Message expansion ************************/ /********************* Message expansion ************************/
@ -84,24 +86,26 @@ static const int h_FFT256_2_128_Twiddle[128] = {
* Reduce modulo 257; result is in [-127; 383] * Reduce modulo 257; result is in [-127; 383]
* REDUCE(x) := (x&255) - (x>>8) * REDUCE(x) := (x&255) - (x>>8)
*/ */
#define REDUCE(x) (((x)&255) - ((x)>>8)) #define REDUCE(x) \
(((x)&255) - ((x)>>8))
/* /*
* Reduce from [-127; 383] to [-128; 128] * Reduce from [-127; 383] to [-128; 128]
* EXTRA_REDUCE_S(x) := x<=128 ? x : x-257 * EXTRA_REDUCE_S(x) := x<=128 ? x : x-257
*/ */
#define EXTRA_REDUCE_S(x) \ #define EXTRA_REDUCE_S(x) \
((x)<=128 ? (x) : (x)-257) ((x)<=128 ? (x) : (x)-257)
/* /*
* Reduce modulo 257; result is in [-128; 128] * Reduce modulo 257; result is in [-128; 128]
*/ */
#define REDUCE_FULL_S(x) \ #define REDUCE_FULL_S(x) \
EXTRA_REDUCE_S(REDUCE(x)) EXTRA_REDUCE_S(REDUCE(x))
__device__ __forceinline__ void FFT_8(int *y, int stripe) { __device__ __forceinline__
void FFT_8(int *y, int stripe) {
/* /*
* FFT_8 using w=4 as 8th root of unity * FFT_8 using w=4 as 8th root of unity
* Unrolled decimation in frequency (DIF) radix-2 NTT. * Unrolled decimation in frequency (DIF) radix-2 NTT.
* Output data is in revbin_permuted order. * Output data is in revbin_permuted order.
@ -110,20 +114,20 @@ __device__ __forceinline__ void FFT_8(int *y, int stripe) {
#define X(i) y[stripe*i] #define X(i) y[stripe*i]
#define DO_REDUCE(i) \ #define DO_REDUCE(i) \
X(i) = REDUCE(X(i)) X(i) = REDUCE(X(i))
#define DO_REDUCE_FULL_S(i) \ #define DO_REDUCE_FULL_S(i) \
do { \ do { \
X(i) = REDUCE(X(i)); \ X(i) = REDUCE(X(i)); \
X(i) = EXTRA_REDUCE_S(X(i)); \ X(i) = EXTRA_REDUCE_S(X(i)); \
} while(0) } while(0)
#define BUTTERFLY(i,j,n) \ #define BUTTERFLY(i,j,n) \
do { \ do { \
int u= X(i); \ int u= X(i); \
int v= X(j); \ int v= X(j); \
X(i) = u+v; \ X(i) = u+v; \
X(j) = (u-v) << (2*n); \ X(j) = (u-v) << (2*n); \
} while(0) } while(0)
BUTTERFLY(0, 4, 0); BUTTERFLY(0, 4, 0);
@ -163,17 +167,16 @@ X(j) = (u-v) << (2*n); \
__device__ __forceinline__ void FFT_16(int *y) { __device__ __forceinline__ void FFT_16(int *y) {
/* /**
* FFT_16 using w=2 as 16th root of unity * FFT_16 using w=2 as 16th root of unity
* Unrolled decimation in frequency (DIF) radix-2 NTT. * Unrolled decimation in frequency (DIF) radix-2 NTT.
* Output data is in revbin_permuted order. * Output data is in revbin_permuted order.
*/ */
#define DO_REDUCE_FULL_S(i) \ #define DO_REDUCE_FULL_S(i) \
do { \ do { \
y[i] = REDUCE(y[i]); \ y[i] = REDUCE(y[i]); \
y[i] = EXTRA_REDUCE_S(y[i]); \ y[i] = EXTRA_REDUCE_S(y[i]); \
} while(0) } while(0)
int u,v; int u,v;
@ -186,8 +189,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY(6, 14, 6); // BUTTERFLY(6, 14, 6);
// BUTTERFLY(7, 15, 7); // BUTTERFLY(7, 15, 7);
{ {
u= y[0]; // 0..7 u = y[0]; // 0..7
v= y[1]; // 8..15 v = y[1]; // 8..15
y[0] = u+v; y[0] = u+v;
y[1] = (u-v) << (threadIdx.x&7); y[1] = (u-v) << (threadIdx.x&7);
} }
@ -204,8 +207,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY( 2, 6, 4); // BUTTERFLY( 2, 6, 4);
// BUTTERFLY( 3, 7, 6); // BUTTERFLY( 3, 7, 6);
{ {
u= __shfl((int)y[0], (threadIdx.x&3),8); // 0,1,2,3 0,1,2,3 u = __shfl((int)y[0], (threadIdx.x&3),8); // 0,1,2,3 0,1,2,3
v= __shfl((int)y[0],4+(threadIdx.x&3),8); // 4,5,6,7 4,5,6,7 v = __shfl((int)y[0],4+(threadIdx.x&3),8); // 4,5,6,7 4,5,6,7
y[0] = ((threadIdx.x&7) < 4) ? (u+v) : ((u-v) << (2*(threadIdx.x&3))); y[0] = ((threadIdx.x&7) < 4) ? (u+v) : ((u-v) << (2*(threadIdx.x&3)));
} }
@ -214,8 +217,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY(10, 14, 4); // BUTTERFLY(10, 14, 4);
// BUTTERFLY(11, 15, 6); // BUTTERFLY(11, 15, 6);
{ {
u= __shfl((int)y[1], (threadIdx.x&3),8); // 8,9,10,11 8,9,10,11 u = __shfl((int)y[1], (threadIdx.x&3),8); // 8,9,10,11 8,9,10,11
v= __shfl((int)y[1],4+(threadIdx.x&3),8); // 12,13,14,15 12,13,14,15 v = __shfl((int)y[1],4+(threadIdx.x&3),8); // 12,13,14,15 12,13,14,15
y[1] = ((threadIdx.x&7) < 4) ? (u+v) : ((u-v) << (2*(threadIdx.x&3))); y[1] = ((threadIdx.x&7) < 4) ? (u+v) : ((u-v) << (2*(threadIdx.x&3)));
} }
@ -233,8 +236,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY( 4, 6, 0); // BUTTERFLY( 4, 6, 0);
// BUTTERFLY( 5, 7, 4); // BUTTERFLY( 5, 7, 4);
{ {
u= __shfl((int)y[0], (threadIdx.x&5),8); // 0,1,0,1 4,5,4,5 u = __shfl((int)y[0], (threadIdx.x&5),8); // 0,1,0,1 4,5,4,5
v= __shfl((int)y[0],2+(threadIdx.x&5),8); // 2,3,2,3 6,7,6,7 v = __shfl((int)y[0],2+(threadIdx.x&5),8); // 2,3,2,3 6,7,6,7
y[0] = ((threadIdx.x&3) < 2) ? (u+v) : ((u-v) << (4*(threadIdx.x&1))); y[0] = ((threadIdx.x&3) < 2) ? (u+v) : ((u-v) << (4*(threadIdx.x&1)));
} }
@ -243,8 +246,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY(12, 14, 0); // BUTTERFLY(12, 14, 0);
// BUTTERFLY(13, 15, 4); // BUTTERFLY(13, 15, 4);
{ {
u= __shfl((int)y[1], (threadIdx.x&5),8); // 8,9,8,9 12,13,12,13 u = __shfl((int)y[1], (threadIdx.x&5),8); // 8,9,8,9 12,13,12,13
v= __shfl((int)y[1],2+(threadIdx.x&5),8); // 10,11,10,11 14,15,14,15 v = __shfl((int)y[1],2+(threadIdx.x&5),8); // 10,11,10,11 14,15,14,15
y[1] = ((threadIdx.x&3) < 2) ? (u+v) : ((u-v) << (4*(threadIdx.x&1))); y[1] = ((threadIdx.x&3) < 2) ? (u+v) : ((u-v) << (4*(threadIdx.x&1)));
} }
@ -253,8 +256,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY( 4, 5, 0); // BUTTERFLY( 4, 5, 0);
// BUTTERFLY( 6, 7, 0); // BUTTERFLY( 6, 7, 0);
{ {
u= __shfl((int)y[0], (threadIdx.x&6),8); // 0,0,2,2 4,4,6,6 u = __shfl((int)y[0], (threadIdx.x&6),8); // 0,0,2,2 4,4,6,6
v= __shfl((int)y[0],1+(threadIdx.x&6),8); // 1,1,3,3 5,5,7,7 v = __shfl((int)y[0],1+(threadIdx.x&6),8); // 1,1,3,3 5,5,7,7
y[0] = ((threadIdx.x&1) < 1) ? (u+v) : (u-v); y[0] = ((threadIdx.x&1) < 1) ? (u+v) : (u-v);
} }
@ -263,8 +266,8 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
// BUTTERFLY(12, 13, 0); // BUTTERFLY(12, 13, 0);
// BUTTERFLY(14, 15, 0); // BUTTERFLY(14, 15, 0);
{ {
u= __shfl((int)y[1], (threadIdx.x&6),8); // 8,8,10,10 12,12,14,14 u = __shfl((int)y[1], (threadIdx.x&6),8); // 8,8,10,10 12,12,14,14
v= __shfl((int)y[1],1+(threadIdx.x&6),8); // 9,9,11,11 13,13,15,15 v = __shfl((int)y[1],1+(threadIdx.x&6),8); // 9,9,11,11 13,13,15,15
y[1] = ((threadIdx.x&1) < 1) ? (u+v) : (u-v); y[1] = ((threadIdx.x&1) < 1) ? (u+v) : (u-v);
} }
@ -274,7 +277,9 @@ y[i] = EXTRA_REDUCE_S(y[i]); \
#undef DO_REDUCE_FULL_S #undef DO_REDUCE_FULL_S
} }
__device__ __forceinline__ void FFT_128_full(int y[128]) { __device__ __forceinline__
void FFT_128_full(int y[128])
{
int i; int i;
FFT_8(y+0,2); // eight parallel FFT8's FFT_8(y+0,2); // eight parallel FFT8's
@ -289,11 +294,9 @@ __device__ __forceinline__ void FFT_128_full(int y[128]) {
FFT_16(y+2*i); // eight sequential FFT16's, each one executed in parallel by 8 threads FFT_16(y+2*i); // eight sequential FFT16's, each one executed in parallel by 8 threads
} }
__device__ __forceinline__
__device__ __forceinline__ void FFT_256_halfzero(int y[256]) { void FFT_256_halfzero(int y[256])
{
int i;
/* /*
* FFT_256 using w=41 as 256th root of unity. * FFT_256 using w=41 as 256th root of unity.
* Decimation in frequency (DIF) NTT. * Decimation in frequency (DIF) NTT.
@ -303,10 +306,10 @@ __device__ __forceinline__ void FFT_256_halfzero(int y[256]) {
const int tmp = y[15]; const int tmp = y[15];
#pragma unroll 8 #pragma unroll 8
for (i=0; i<8; i++) for (int i=0; i<8; i++)
y[16+i] = REDUCE(y[i] * c_FFT256_2_128_Twiddle[8*i+(threadIdx.x&7)]); y[16+i] = REDUCE(y[i] * c_FFT256_2_128_Twiddle[8*i+(threadIdx.x&7)]);
#pragma unroll 8 #pragma unroll 8
for (i=8; i<16; i++) for (int i=8; i<16; i++)
y[16+i] = 0; y[16+i] = 0;
/* handle X^255 with an additional butterfly */ /* handle X^255 with an additional butterfly */
@ -323,19 +326,18 @@ __device__ __forceinline__ void FFT_256_halfzero(int y[256]) {
/***************************************************/ /***************************************************/
__device__ __forceinline__ void Expansion(const uint32_t *data, uint4 *g_temp4) __device__ __forceinline__
void Expansion(const uint32_t *data, uint4 *g_temp4)
{ {
int i;
/* Message Expansion using Number Theoretical Transform similar to FFT */ /* Message Expansion using Number Theoretical Transform similar to FFT */
int expanded[32]; int expanded[32];
#pragma unroll 4 #pragma unroll 4
for (i=0; i < 4; i++) { for (int i=0; i < 4; i++) {
expanded[ i] = __byte_perm(__shfl((int)data[0], 2*i, 8), __shfl((int)data[0], (2*i)+1, 8), threadIdx.x&7)&0xff; expanded[ i] = __byte_perm(__shfl((int)data[0], 2*i, 8), __shfl((int)data[0], (2*i)+1, 8), threadIdx.x&7)&0xff;
expanded[4+i] = __byte_perm(__shfl((int)data[1], 2*i, 8), __shfl((int)data[1], (2*i)+1, 8), threadIdx.x&7)&0xff; expanded[4+i] = __byte_perm(__shfl((int)data[1], 2*i, 8), __shfl((int)data[1], (2*i)+1, 8), threadIdx.x&7)&0xff;
} }
#pragma unroll 8 #pragma unroll 8
for (i=8; i < 16; i++) for (int i=8; i < 16; i++)
expanded[i] = 0; expanded[i] = 0;
FFT_256_halfzero(expanded); FFT_256_halfzero(expanded);
@ -447,7 +449,6 @@ __device__ __forceinline__ void Expansion(const uint32_t *data, uint4 *g_temp4)
//{ 14, 78, 46, 110, 30, 94, 62, 126 }, { 15, 79, 47, 111, 31, 95, 63, 127 }, //{ 14, 78, 46, 110, 30, 94, 62, 126 }, { 15, 79, 47, 111, 31, 95, 63, 127 },
//{ 2, 66, 34, 98, 18, 82, 50, 114 }, { 3, 67, 35, 99, 19, 83, 51, 115 }, //{ 2, 66, 34, 98, 18, 82, 50, 114 }, { 3, 67, 35, 99, 19, 83, 51, 115 },
bool sel = ((threadIdx.x+2)&7) >= 4; // 2,3,4,5 bool sel = ((threadIdx.x+2)&7) >= 4; // 2,3,4,5
P1 = sel?expanded[0]:expanded[1]; Q1 = __shfl(P1, threadIdx.x^1, 8); P1 = sel?expanded[0]:expanded[1]; Q1 = __shfl(P1, threadIdx.x^1, 8);
@ -474,7 +475,6 @@ __device__ __forceinline__ void Expansion(const uint32_t *data, uint4 *g_temp4)
// 0 8 4 12 2 10 6 14 0 8 4 12 2 10 6 14 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 // 0 8 4 12 2 10 6 14 0 8 4 12 2 10 6 14 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
// 1 9 5 13 3 11 7 15 1 9 5 13 3 11 7 15 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 // 1 9 5 13 3 11 7 15 1 9 5 13 3 11 7 15 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5
P1 = sel?expanded[1]:expanded[0]; Q1 = __shfl(P1, threadIdx.x^1, 8); P1 = sel?expanded[1]:expanded[0]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[3]:expanded[2]; P2 = __shfl(Q2, threadIdx.x^1, 8); Q2 = sel?expanded[3]:expanded[2]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2; P = even? P1 : P2; Q = even? Q1 : Q2;
@ -552,7 +552,7 @@ __device__ __forceinline__ void Expansion(const uint32_t *data, uint4 *g_temp4)
} }
/***************************************************/ /***************************************************/
// Die Hash-Funktion
__global__ void __launch_bounds__(TPB,4) __global__ void __launch_bounds__(TPB,4)
x11_simd512_gpu_expand_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector, uint4 *g_temp4) x11_simd512_gpu_expand_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector, uint4 *g_temp4)
{ {
@ -567,9 +567,10 @@ x11_simd512_gpu_expand_64(int threads, uint32_t startNounce, uint64_t *g_hash, u
// Hash einlesen und auf 8 Threads und 2 Register verteilen // Hash einlesen und auf 8 Threads und 2 Register verteilen
uint32_t Hash[2]; uint32_t Hash[2];
#pragma unroll 2
#pragma unroll 2
for (int i=0; i<2; i++) for (int i=0; i<2; i++)
Hash[i] = inpHash[8*i+(threadIdx.x&7)]; Hash[i] = inpHash[8*i + (threadIdx.x & 7)];
// Puffer für expandierte Nachricht // Puffer für expandierte Nachricht
uint4 *temp4 = &g_temp4[64 * hashPosition]; uint4 *temp4 = &g_temp4[64 * hashPosition];
@ -622,20 +623,13 @@ x11_simd512_gpu_final_64(int threads, uint32_t startNounce, uint64_t *g_hash, ui
} }
} }
// Setup-Funktionen __host__
__host__ void x11_simd512_cpu_init(int thr_id, int threads) void x11_simd512_cpu_init(int thr_id, int threads)
{ {
cudaMalloc( &d_state[thr_id], 32*sizeof(int)*threads ); CUDA_SAFE_CALL(cudaMalloc(&d_state[thr_id], 32*sizeof(int)*threads));
cudaMalloc( &d_temp4[thr_id], 64*sizeof(uint4)*threads ); CUDA_SAFE_CALL(cudaMalloc(&d_temp4[thr_id], 64*sizeof(uint4)*threads));
// Textur für 128 Bit Zugriffe
cudaChannelFormatDesc channelDesc128 = cudaCreateChannelDesc<uint4>();
texRef1D_128.normalized = 0;
texRef1D_128.filterMode = cudaFilterModePoint;
texRef1D_128.addressMode[0] = cudaAddressModeClamp;
cudaBindTexture(NULL, &texRef1D_128, d_temp4[thr_id], &channelDesc128, 64*sizeof(uint4)*threads);
cudaMemcpyToSymbol( c_perm, h_perm, sizeof(h_perm), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(c_perm, h_perm, sizeof(h_perm), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(c_IV_512, h_IV_512, sizeof(h_IV_512), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(c_IV_512, h_IV_512, sizeof(h_IV_512), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(c_FFT128_8_16_Twiddle, h_FFT128_8_16_Twiddle, sizeof(h_FFT128_8_16_Twiddle), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(c_FFT128_8_16_Twiddle, h_FFT128_8_16_Twiddle, sizeof(h_FFT128_8_16_Twiddle), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(c_FFT256_2_128_Twiddle, h_FFT256_2_128_Twiddle, sizeof(h_FFT256_2_128_Twiddle), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(c_FFT256_2_128_Twiddle, h_FFT256_2_128_Twiddle, sizeof(h_FFT256_2_128_Twiddle), 0, cudaMemcpyHostToDevice);
@ -644,28 +638,31 @@ __host__ void x11_simd512_cpu_init(int thr_id, int threads)
cudaMemcpyToSymbol(d_cw1, h_cw1, sizeof(h_cw1), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(d_cw1, h_cw1, sizeof(h_cw1), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(d_cw2, h_cw2, sizeof(h_cw2), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(d_cw2, h_cw2, sizeof(h_cw2), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(d_cw3, h_cw3, sizeof(h_cw3), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol(d_cw3, h_cw3, sizeof(h_cw3), 0, cudaMemcpyHostToDevice);
// Texture for 128-Bit Zugriffe
cudaChannelFormatDesc channelDesc128 = cudaCreateChannelDesc<uint4>();
texRef1D_128.normalized = 0;
texRef1D_128.filterMode = cudaFilterModePoint;
texRef1D_128.addressMode[0] = cudaAddressModeClamp;
CUDA_SAFE_CALL(cudaBindTexture(NULL, &texRef1D_128, d_temp4[thr_id], &channelDesc128, 64*sizeof(uint4)*threads));
} }
__host__ void x11_simd512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order) __host__
void x11_simd512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order)
{ {
const int threadsperblock = TPB; const int threadsperblock = TPB;
// Größe des dynamischen Shared Memory Bereichs
size_t shared_size = 0;
// berechne wie viele Thread Blocks wir brauchen
dim3 block(threadsperblock); dim3 block(threadsperblock);
dim3 grid8(((threads + threadsperblock-1)/threadsperblock)*8); dim3 grid8(((threads + threadsperblock-1)/threadsperblock)*8);
x11_simd512_gpu_expand_64<<<grid8, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id]);
x11_simd512_gpu_expand_64 <<<grid8, block>>> (threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id]);
dim3 grid((threads + threadsperblock-1)/threadsperblock); dim3 grid((threads + threadsperblock-1)/threadsperblock);
// künstlich die Occupancy limitieren, um das totale Erschöpfen des Texture Cache zu vermeiden x11_simd512_gpu_compress1_64 <<<grid, block>>> (threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id], d_state[thr_id]);
x11_simd512_gpu_compress1_64<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id], d_state[thr_id]); x11_simd512_gpu_compress2_64 <<<grid, block>>> (threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id], d_state[thr_id]);
x11_simd512_gpu_compress2_64<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id], d_state[thr_id]);
x11_simd512_gpu_final_64<<<grid, block, shared_size>>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id], d_state[thr_id]); x11_simd512_gpu_final_64 <<<grid, block>>> (threads, startNounce, (uint64_t*)d_hash, d_nonceVector, d_temp4[thr_id], d_state[thr_id]);
MyStreamSynchronize(NULL, order, thr_id); MyStreamSynchronize(NULL, order, thr_id);
} }

1
x11/x11.cu
Unescape View File

@ -147,7 +147,6 @@ extern "C" int scanhash_x11(int thr_id, uint32_t *pdata,
if (!init[thr_id]) if (!init[thr_id])
{ {
CUDA_SAFE_CALL(cudaSetDevice(device_map[thr_id])); CUDA_SAFE_CALL(cudaSetDevice(device_map[thr_id]));
// Konstanten kopieren, Speicher belegen
CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 16 * sizeof(uint32_t) * throughput)); CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 16 * sizeof(uint32_t) * throughput));
quark_blake512_cpu_init(thr_id, throughput); quark_blake512_cpu_init(thr_id, throughput);

Write Preview
Loading…
Cancel
Save