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GOSTCoin CUDA miner project, compatible with most nvidia cards, containing only gostd algo
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ccminer-gostd-lite/x11/cuda_x11_simd512.cu

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// Parallelization:
//
// FFT_8 wird 2 times 8-fach parallel ausgeführt (in FFT_64)
// and 1 time 16-fach parallel (in FFT_128_full)
//
// STEP8_IF and STEP8_MAJ beinhalten je 2x 8-fach parallel Operations
#define TPB 64
#include "cuda_helper.h"
#include <stdio.h>
// aus heavy.cu
extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
int *d_state[8];
uint4 *d_temp4[8];
// texture bound to d_temp4[thr_id], for read access in Compaction kernel
texture<uint4, 1, cudaReadModeElementType> texRef1D_128;
__constant__ uint32_t c_perm[8][8];
const uint32_t h_perm[8][8] = {
{ 2, 3, 6, 7, 0, 1, 4, 5 },
{ 6, 7, 2, 3, 4, 5, 0, 1 },
{ 7, 6, 5, 4, 3, 2, 1, 0 },
{ 1, 0, 3, 2, 5, 4, 7, 6 },
{ 0, 1, 4, 5, 6, 7, 2, 3 },
{ 6, 7, 2, 3, 0, 1, 4, 5 },
{ 6, 7, 0, 1, 4, 5, 2, 3 },
{ 4, 5, 2, 3, 6, 7, 0, 1 }
};
__constant__ uint32_t c_IV_512[32];
const uint32_t h_IV_512[32] = {
0x0ba16b95, 0x72f999ad, 0x9fecc2ae, 0xba3264fc, 0x5e894929, 0x8e9f30e5, 0x2f1daa37, 0xf0f2c558,
0xac506643, 0xa90635a5, 0xe25b878b, 0xaab7878f, 0x88817f7a, 0x0a02892b, 0x559a7550, 0x598f657e,
0x7eef60a1, 0x6b70e3e8, 0x9c1714d1, 0xb958e2a8, 0xab02675e, 0xed1c014f, 0xcd8d65bb, 0xfdb7a257,
0x09254899, 0xd699c7bc, 0x9019b6dc, 0x2b9022e4, 0x8fa14956, 0x21bf9bd3, 0xb94d0943, 0x6ffddc22
};
__constant__ int c_FFT128_8_16_Twiddle[128];
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, 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, -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, 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, -61, 123, -50, -34, 18, -70, -99, 128, -98, 67, 25, 17, -9, 35, -79
};
__constant__ int c_FFT256_2_128_Twiddle[128];
static const int h_FFT256_2_128_Twiddle[128] = {
1, 41,-118, 45, 46, 87, -31, 14,
60,-110, 116,-127, -67, 80, -61, 69,
2, 82, 21, 90, 92, -83, -62, 28,
120, 37, -25, 3, 123, -97,-122,-119,
4, -93, 42, -77, -73, 91,-124, 56,
-17, 74, -50, 6, -11, 63, 13, 19,
8, 71, 84, 103, 111, -75, 9, 112,
-34,-109,-100, 12, -22, 126, 26, 38,
16,-115, -89, -51, -35, 107, 18, -33,
-68, 39, 57, 24, -44, -5, 52, 76,
32, 27, 79,-102, -70, -43, 36, -66,
121, 78, 114, 48, -88, -10, 104,-105,
64, 54, -99, 53, 117, -86, 72, 125,
-15,-101, -29, 96, 81, -20, -49, 47,
128, 108, 59, 106, -23, 85,-113, -7,
-30, 55, -58, -65, -95, -40, -98, 94
};
/************* the round function ****************/
#define IF(x, y, z) ((((y) ^ (z)) & (x)) ^ (z))
#define MAJ(x, y, z) (((z) & (y)) | (((z) | (y)) & (x)))
#include "x11/simd_functions.cu"
/********************* Message expansion ************************/
/*
* Reduce modulo 257; result is in [-127; 383]
* REDUCE(x) := (x&255) - (x>>8)
*/
#define REDUCE(x) \
(((x)&255) - ((x)>>8))
/*
* Reduce from [-127; 383] to [-128; 128]
* EXTRA_REDUCE_S(x) := x<=128 ? x : x-257
*/
#define EXTRA_REDUCE_S(x) \
((x)<=128 ? (x) : (x)-257)
/*
* Reduce modulo 257; result is in [-128; 128]
*/
#define REDUCE_FULL_S(x) \
EXTRA_REDUCE_S(REDUCE(x))
__device__ __forceinline__
void FFT_8(int *y, int stripe) {
/*
* FFT_8 using w=4 as 8th root of unity
* Unrolled decimation in frequency (DIF) radix-2 NTT.
* Output data is in revbin_permuted order.
*/
#define X(i) y[stripe*i]
#define DO_REDUCE(i) \
X(i) = REDUCE(X(i))
#define DO_REDUCE_FULL_S(i) \
do { \
X(i) = REDUCE(X(i)); \
X(i) = EXTRA_REDUCE_S(X(i)); \
} while(0)
#define BUTTERFLY(i,j,n) \
do { \
int u= X(i); \
int v= X(j); \
X(i) = u+v; \
X(j) = (u-v) << (2*n); \
} while(0)
BUTTERFLY(0, 4, 0);
BUTTERFLY(1, 5, 1);
BUTTERFLY(2, 6, 2);
BUTTERFLY(3, 7, 3);
DO_REDUCE(6);
DO_REDUCE(7);
BUTTERFLY(0, 2, 0);
BUTTERFLY(4, 6, 0);
BUTTERFLY(1, 3, 2);
BUTTERFLY(5, 7, 2);
DO_REDUCE(7);
BUTTERFLY(0, 1, 0);
BUTTERFLY(2, 3, 0);
BUTTERFLY(4, 5, 0);
BUTTERFLY(6, 7, 0);
DO_REDUCE_FULL_S(0);
DO_REDUCE_FULL_S(1);
DO_REDUCE_FULL_S(2);
DO_REDUCE_FULL_S(3);
DO_REDUCE_FULL_S(4);
DO_REDUCE_FULL_S(5);
DO_REDUCE_FULL_S(6);
DO_REDUCE_FULL_S(7);
#undef X
#undef DO_REDUCE
#undef DO_REDUCE_FULL_S
#undef BUTTERFLY
}
__device__ __forceinline__ void FFT_16(int *y) {
/**
* FFT_16 using w=2 as 16th root of unity
* Unrolled decimation in frequency (DIF) radix-2 NTT.
* Output data is in revbin_permuted order.
*/
#define DO_REDUCE_FULL_S(i) \
do { \
y[i] = REDUCE(y[i]); \
y[i] = EXTRA_REDUCE_S(y[i]); \
} while(0)
int u,v;
// BUTTERFLY(0, 8, 0);
// BUTTERFLY(1, 9, 1);
// BUTTERFLY(2, 10, 2);
// BUTTERFLY(3, 11, 3);
// BUTTERFLY(4, 12, 4);
// BUTTERFLY(5, 13, 5);
// BUTTERFLY(6, 14, 6);
// BUTTERFLY(7, 15, 7);
{
u = y[0]; // 0..7
v = y[1]; // 8..15
y[0] = u+v;
y[1] = (u-v) << (threadIdx.x&7);
}
// DO_REDUCE(11);
// DO_REDUCE(12);
// DO_REDUCE(13);
// DO_REDUCE(14);
// DO_REDUCE(15);
if ((threadIdx.x&7) >=3) y[1] = REDUCE(y[1]); // 11...15
// BUTTERFLY( 0, 4, 0);
// BUTTERFLY( 1, 5, 2);
// BUTTERFLY( 2, 6, 4);
// BUTTERFLY( 3, 7, 6);
{
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
y[0] = ((threadIdx.x&7) < 4) ? (u+v) : ((u-v) << (2*(threadIdx.x&3)));
}
// BUTTERFLY( 8, 12, 0);
// BUTTERFLY( 9, 13, 2);
// BUTTERFLY(10, 14, 4);
// BUTTERFLY(11, 15, 6);
{
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
y[1] = ((threadIdx.x&7) < 4) ? (u+v) : ((u-v) << (2*(threadIdx.x&3)));
}
// DO_REDUCE(5);
// DO_REDUCE(7);
// DO_REDUCE(13);
// DO_REDUCE(15);
if ((threadIdx.x&1) && (threadIdx.x&7) >= 4) {
y[0] = REDUCE(y[0]); // 5, 7
y[1] = REDUCE(y[1]); // 13, 15
}
// BUTTERFLY( 0, 2, 0);
// BUTTERFLY( 1, 3, 4);
// BUTTERFLY( 4, 6, 0);
// BUTTERFLY( 5, 7, 4);
{
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
y[0] = ((threadIdx.x&3) < 2) ? (u+v) : ((u-v) << (4*(threadIdx.x&1)));
}
// BUTTERFLY( 8, 10, 0);
// BUTTERFLY( 9, 11, 4);
// BUTTERFLY(12, 14, 0);
// BUTTERFLY(13, 15, 4);
{
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
y[1] = ((threadIdx.x&3) < 2) ? (u+v) : ((u-v) << (4*(threadIdx.x&1)));
}
// BUTTERFLY( 0, 1, 0);
// BUTTERFLY( 2, 3, 0);
// BUTTERFLY( 4, 5, 0);
// BUTTERFLY( 6, 7, 0);
{
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
y[0] = ((threadIdx.x&1) < 1) ? (u+v) : (u-v);
}
// BUTTERFLY( 8, 9, 0);
// BUTTERFLY(10, 11, 0);
// BUTTERFLY(12, 13, 0);
// BUTTERFLY(14, 15, 0);
{
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
y[1] = ((threadIdx.x&1) < 1) ? (u+v) : (u-v);
}
DO_REDUCE_FULL_S( 0); // 0...7
DO_REDUCE_FULL_S( 1); // 8...15
#undef DO_REDUCE_FULL_S
}
__device__ __forceinline__
void FFT_128_full(int y[128])
{
int i;
FFT_8(y+0,2); // eight parallel FFT8's
FFT_8(y+1,2); // eight parallel FFT8's
#pragma unroll 16
for (i=0; i<16; i++)
/*if (i & 7)*/ y[i] = REDUCE(y[i]*c_FFT128_8_16_Twiddle[i*8+(threadIdx.x&7)]);
#pragma unroll 8
for (i=0; i<8; i++)
FFT_16(y+2*i); // eight sequential FFT16's, each one executed in parallel by 8 threads
}
__device__ __forceinline__
void FFT_256_halfzero(int y[256])
{
/*
* FFT_256 using w=41 as 256th root of unity.
* Decimation in frequency (DIF) NTT.
* Output data is in revbin_permuted order.
* In place.
*/
const int tmp = y[15];
#pragma unroll 8
for (int i=0; i<8; i++)
y[16+i] = REDUCE(y[i] * c_FFT256_2_128_Twiddle[8*i+(threadIdx.x&7)]);
#pragma unroll 8
for (int i=8; i<16; i++)
y[16+i] = 0;
/* handle X^255 with an additional butterfly */
if ((threadIdx.x&7) == 7)
{
y[15] = REDUCE(tmp + 1);
y[31] = REDUCE((tmp - 1) * c_FFT256_2_128_Twiddle[127]);
}
FFT_128_full(y);
FFT_128_full(y+16);
}
/***************************************************/
__device__ __forceinline__
void Expansion(const uint32_t *data, uint4 *g_temp4)
{
/* Message Expansion using Number Theoretical Transform similar to FFT */
int expanded[32];
#pragma unroll 4
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[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
for (int i=8; i < 16; i++)
expanded[i] = 0;
FFT_256_halfzero(expanded);
// store w matrices in global memory
#define mul_185(x) ( (x)*185 )
#define mul_233(x) ( (x)*233 )
uint4 vec0;
int P, Q, P1, Q1, P2, Q2;
bool even = (threadIdx.x & 1) == 0;
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
// 2 6 0 4
P1 = expanded[ 0]; P2 = __shfl(expanded[ 2], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[16]; Q2 = __shfl(expanded[18], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[0][threadIdx.x&7], 8);
P1 = expanded[ 8]; P2 = __shfl(expanded[10], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[24]; Q2 = __shfl(expanded[26], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[0][threadIdx.x&7], 8);
P1 = expanded[ 4]; P2 = __shfl(expanded[ 6], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[20]; Q2 = __shfl(expanded[22], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[0][threadIdx.x&7], 8);
P1 = expanded[12]; P2 = __shfl(expanded[14], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[28]; Q2 = __shfl(expanded[30], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[0][threadIdx.x&7], 8);
g_temp4[threadIdx.x&7] = vec0;
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
// 6 2 4 0
P1 = expanded[ 1]; P2 = __shfl(expanded[ 3], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[17]; Q2 = __shfl(expanded[19], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[1][threadIdx.x&7], 8);
P1 = expanded[ 9]; P2 = __shfl(expanded[11], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[25]; Q2 = __shfl(expanded[27], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[1][threadIdx.x&7], 8);
P1 = expanded[ 5]; P2 = __shfl(expanded[ 7], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[21]; Q2 = __shfl(expanded[23], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[1][threadIdx.x&7], 8);
P1 = expanded[13]; P2 = __shfl(expanded[15], (threadIdx.x-1)&7, 8); P = even ? P1 : P2;
Q1 = expanded[29]; Q2 = __shfl(expanded[31], (threadIdx.x-1)&7, 8); Q = even ? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[1][threadIdx.x&7], 8);
g_temp4[8+(threadIdx.x&7)] = vec0;
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
// 7 5 3 1
bool hi = (threadIdx.x&7)>=4;
P1 = hi?expanded[ 1]:expanded[ 0]; P2 = __shfl(hi?expanded[ 3]:expanded[ 2], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = hi?expanded[17]:expanded[16]; Q2 = __shfl(hi?expanded[19]:expanded[18], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[2][threadIdx.x&7], 8);
P1 = hi?expanded[ 9]:expanded[ 8]; P2 = __shfl(hi?expanded[11]:expanded[10], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = hi?expanded[25]:expanded[24]; Q2 = __shfl(hi?expanded[27]:expanded[26], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[2][threadIdx.x&7], 8);
P1 = hi?expanded[ 5]:expanded[ 4]; P2 = __shfl(hi?expanded[ 7]:expanded[ 6], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = hi?expanded[21]:expanded[20]; Q2 = __shfl(hi?expanded[23]:expanded[22], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[2][threadIdx.x&7], 8);
P1 = hi?expanded[13]:expanded[12]; P2 = __shfl(hi?expanded[15]:expanded[14], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = hi?expanded[29]:expanded[28]; Q2 = __shfl(hi?expanded[31]:expanded[30], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[2][threadIdx.x&7], 8);
g_temp4[16+(threadIdx.x&7)] = vec0;
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
// 1 9 5 13 3 11 7 15 17 25 21 29 19 27 23 31 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
// 0 8 4 12 2 10 6 14 16 24 20 28 18 26 22 30 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
// 1 3 5 7
bool lo = (threadIdx.x&7)<4;
P1 = lo?expanded[ 1]:expanded[ 0]; P2 = __shfl(lo?expanded[ 3]:expanded[ 2], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = lo?expanded[17]:expanded[16]; Q2 = __shfl(lo?expanded[19]:expanded[18], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[3][threadIdx.x&7], 8);
P1 = lo?expanded[ 9]:expanded[ 8]; P2 = __shfl(lo?expanded[11]:expanded[10], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = lo?expanded[25]:expanded[24]; Q2 = __shfl(lo?expanded[27]:expanded[26], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[3][threadIdx.x&7], 8);
P1 = lo?expanded[ 5]:expanded[ 4]; P2 = __shfl(lo?expanded[ 7]:expanded[ 6], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = lo?expanded[21]:expanded[20]; Q2 = __shfl(lo?expanded[23]:expanded[22], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[3][threadIdx.x&7], 8);
P1 = lo?expanded[13]:expanded[12]; P2 = __shfl(lo?expanded[15]:expanded[14], (threadIdx.x+1)&7, 8); P = !even ? P1 : P2;
Q1 = lo?expanded[29]:expanded[28]; Q2 = __shfl(lo?expanded[31]:expanded[30], (threadIdx.x+1)&7, 8); Q = !even ? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_185(P), mul_185(Q) , 0x5410), c_perm[3][threadIdx.x&7], 8);
g_temp4[24+(threadIdx.x&7)] = vec0;
// 1 9 5 13 3 11 7 15 1 9 5 13 3 11 7 15 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 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 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7
// 0 8 4 12 2 10 6 14 0 8 4 12 2 10 6 14 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3
//{ 8, 72, 40, 104, 24, 88, 56, 120 }, { 9, 73, 41, 105, 25, 89, 57, 121 },
//{ 4, 68, 36, 100, 20, 84, 52, 116 }, { 5, 69, 37, 101, 21, 85, 53, 117 },
//{ 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 },
bool sel = ((threadIdx.x+2)&7) >= 4; // 2,3,4,5
P1 = sel?expanded[0]:expanded[1]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[2]:expanded[3]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[4][threadIdx.x&7], 8);
P1 = sel?expanded[8]:expanded[9]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[10]:expanded[11]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[4][threadIdx.x&7], 8);
P1 = sel?expanded[4]:expanded[5]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[6]:expanded[7]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[4][threadIdx.x&7], 8);
P1 = sel?expanded[12]:expanded[13]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[14]:expanded[15]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[4][threadIdx.x&7], 8);
g_temp4[32+(threadIdx.x&7)] = vec0;
// 0 8 4 12 2 10 6 14 0 8 4 12 2 10 6 14 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7
// 1 9 5 13 3 11 7 15 1 9 5 13 3 11 7 15 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3
// 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
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);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[5][threadIdx.x&7], 8);
P1 = sel?expanded[9]:expanded[8]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[11]:expanded[10]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[5][threadIdx.x&7], 8);
P1 = sel?expanded[5]:expanded[4]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[7]:expanded[6]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[5][threadIdx.x&7], 8);
P1 = sel?expanded[13]:expanded[12]; Q1 = __shfl(P1, threadIdx.x^1, 8);
Q2 = sel?expanded[15]:expanded[14]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[5][threadIdx.x&7], 8);
g_temp4[40+(threadIdx.x&7)] = vec0;
// 16 24 20 28 18 26 22 30 16 24 20 28 18 26 22 30 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7
// 16 24 20 28 18 26 22 30 16 24 20 28 18 26 22 30 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
// 17 25 21 29 19 27 23 31 17 25 21 29 19 27 23 31 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
// 17 25 21 29 19 27 23 31 17 25 21 29 19 27 23 31 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7
// sel markiert threads 2,3,4,5
int t;
t = __shfl(expanded[17],(threadIdx.x+4)&7,8); P1 = sel?t:expanded[16]; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[19],(threadIdx.x+4)&7,8); Q2 = sel?t:expanded[18]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[6][threadIdx.x&7], 8);
t = __shfl(expanded[25],(threadIdx.x+4)&7,8); P1 = sel?t:expanded[24]; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[27],(threadIdx.x+4)&7,8); Q2 = sel?t:expanded[26]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[6][threadIdx.x&7], 8);
t = __shfl(expanded[21],(threadIdx.x+4)&7,8); P1 = sel?t:expanded[20]; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[23],(threadIdx.x+4)&7,8); Q2 = sel?t:expanded[22]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[6][threadIdx.x&7], 8);
t = __shfl(expanded[29],(threadIdx.x+4)&7,8); P1 = sel?t:expanded[28]; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[31],(threadIdx.x+4)&7,8); Q2 = sel?t:expanded[30]; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[6][threadIdx.x&7], 8);
g_temp4[48+(threadIdx.x&7)] = vec0;
// 17 25 21 29 19 27 23 31 17 25 21 29 19 27 23 31 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5
// 17 25 21 29 19 27 23 31 17 25 21 29 19 27 23 31 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3
// 16 24 20 28 18 26 22 30 16 24 20 28 18 26 22 30 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3
// 16 24 20 28 18 26 22 30 16 24 20 28 18 26 22 30 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5
// sel markiert threads 2,3,4,5
t = __shfl(expanded[16],(threadIdx.x+4)&7,8); P1 = sel?expanded[17]:t; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[18],(threadIdx.x+4)&7,8); Q2 = sel?expanded[19]:t; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.x = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[7][threadIdx.x&7], 8);
t = __shfl(expanded[24],(threadIdx.x+4)&7,8); P1 = sel?expanded[25]:t; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[26],(threadIdx.x+4)&7,8); Q2 = sel?expanded[27]:t; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.y = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[7][threadIdx.x&7], 8);
t = __shfl(expanded[20],(threadIdx.x+4)&7,8); P1 = sel?expanded[21]:t; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[22],(threadIdx.x+4)&7,8); Q2 = sel?expanded[23]:t; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.z = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[7][threadIdx.x&7], 8);
t = __shfl(expanded[28],(threadIdx.x+4)&7,8); P1 = sel?expanded[29]:t; Q1 = __shfl(P1, threadIdx.x^1, 8);
t = __shfl(expanded[30],(threadIdx.x+4)&7,8); Q2 = sel?expanded[31]:t; P2 = __shfl(Q2, threadIdx.x^1, 8);
P = even? P1 : P2; Q = even? Q1 : Q2;
vec0.w = __shfl((int)__byte_perm(mul_233(P), mul_233(Q) , 0x5410), c_perm[7][threadIdx.x&7], 8);
g_temp4[56+(threadIdx.x&7)] = vec0;
#undef mul_185
#undef mul_233
}
/***************************************************/
__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)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x)/8;
if (thread < threads)
{
uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
uint32_t *inpHash = (uint32_t*)&g_hash[8 * hashPosition];
// Hash einlesen und auf 8 Threads und 2 Register verteilen
uint32_t Hash[2];
#pragma unroll 2
for (int i=0; i<2; i++)
Hash[i] = inpHash[8*i + (threadIdx.x & 7)];
// Puffer für expandierte Nachricht
uint4 *temp4 = &g_temp4[64 * hashPosition];
Expansion(Hash, temp4);
}
}
__global__ void __launch_bounds__(TPB,4)
x11_simd512_gpu_compress1_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector, uint4 *g_fft4, int *g_state)
{
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];
Compression1(Hash, hashPosition, g_fft4, g_state);
}
}
__global__ void __launch_bounds__(TPB,4)
x11_simd512_gpu_compress2_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector, uint4 *g_fft4, int *g_state)
{
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;
Compression2(hashPosition, g_fft4, g_state);
}
}
__global__ void __launch_bounds__(TPB,4)
x11_simd512_gpu_final_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector, uint4 *g_fft4, int *g_state)
{
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];
Final(Hash, hashPosition, g_fft4, g_state);
}
}
__host__
void x11_simd512_cpu_init(int thr_id, int threads)
{
CUDA_SAFE_CALL(cudaMalloc(&d_state[thr_id], 32*sizeof(int)*threads));
CUDA_SAFE_CALL(cudaMalloc(&d_temp4[thr_id], 64*sizeof(uint4)*threads));
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_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(d_cw0, h_cw0, sizeof(h_cw0), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(d_cw1, h_cw1, sizeof(h_cw1), 0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(d_cw2, h_cw2, sizeof(h_cw2), 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)
{
const int threadsperblock = TPB;
dim3 block(threadsperblock);
dim3 grid8(((threads + threadsperblock-1)/threadsperblock)*8);
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);
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_compress2_64 <<<grid, block>>> (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);
}