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GOSTcoin support for ccminer CUDA miner project, compatible with most nvidia cards
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ccminer/scrypt/kepler_kernel.cu

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import and adapt scrypt from cudaminer project scrypt-jane under work...
10 years ago
/* Copyright (C) 2013 David G. Andersen. All rights reserved.
* with modifications by Christian Buchner
*
* Use of this code is covered under the Apache 2.0 license, which
* can be found in the file "LICENSE"
*/
// TODO: attempt V.Volkov style ILP (factor 4)
#include <map>
scrypt: clean some defines and prevent error reports on Ctrl+C
10 years ago
#include <cuda_runtime.h>
import and adapt scrypt from cudaminer project scrypt-jane under work...
10 years ago
#include "miner.h"
#include "salsa_kernel.h"
#include "kepler_kernel.h"
#define TEXWIDTH 32768
#define THREADS_PER_WU 4 // four threads per hash
typedef enum
{
ANDERSEN,
SIMPLE
} MemoryAccess;
// scratchbuf constants (pointers to scratch buffer for each warp, i.e. 32 hashes)
__constant__ uint32_t* c_V[TOTAL_WARP_LIMIT];
// iteration count N
__constant__ uint32_t c_N;
__constant__ uint32_t c_N_1; // N-1
// scratch buffer size SCRATCH
__constant__ uint32_t c_SCRATCH;
__constant__ uint32_t c_SCRATCH_WU_PER_WARP; // (SCRATCH * WU_PER_WARP)
__constant__ uint32_t c_SCRATCH_WU_PER_WARP_1; // (SCRATCH * WU_PER_WARP) - 1
// using texture references for the "tex" variants of the B kernels
texture<uint4, 1, cudaReadModeElementType> texRef1D_4_V;
texture<uint4, 2, cudaReadModeElementType> texRef2D_4_V;
template <int ALGO> __device__ __forceinline__ void block_mixer(uint4 &b, uint4 &bx, const int x1, const int x2, const int x3);
static __host__ __device__ uint4& operator ^= (uint4& left, const uint4& right) {
left.x ^= right.x;
left.y ^= right.y;
left.z ^= right.z;
left.w ^= right.w;
return left;
}
static __host__ __device__ uint4& operator += (uint4& left, const uint4& right) {
left.x += right.x;
left.y += right.y;
left.z += right.z;
left.w += right.w;
return left;
}
static __device__ uint4 __shfl(const uint4 bx, int target_thread) {
return make_uint4(
__shfl((int)bx.x, target_thread),
__shfl((int)bx.y, target_thread),
__shfl((int)bx.z, target_thread),
__shfl((int)bx.w, target_thread)
);
}
/* write_keys writes the 8 keys being processed by a warp to the global
* scratchpad. To effectively use memory bandwidth, it performs the writes
* (and reads, for read_keys) 128 bytes at a time per memory location
* by __shfl'ing the 4 entries in bx to the threads in the next-up
* thread group. It then has eight threads together perform uint4
* (128 bit) writes to the destination region. This seems to make
* quite effective use of memory bandwidth. An approach that spread
* uint32s across more threads was slower because of the increased
* computation it required.
*
* "start" is the loop iteration producing the write - the offset within
* the block's memory.
*
* Internally, this algorithm first __shfl's the 4 bx entries to
* the next up thread group, and then uses a conditional move to
* ensure that odd-numbered thread groups exchange the b/bx ordering
* so that the right parts are written together.
*
* Thanks to Babu for helping design the 128-bit-per-write version.
*
* _direct lets the caller specify the absolute start location instead of
* the relative start location, as an attempt to reduce some recomputation.
*/
template <MemoryAccess SCHEME> __device__ __forceinline__
void write_keys_direct(const uint4 &b, const uint4 &bx, uint32_t start)
{
uint32_t *scratch = c_V[(blockIdx.x*blockDim.x + threadIdx.x)/32];
if (SCHEME == ANDERSEN) {
int target_thread = (threadIdx.x + 4)%32;
uint4 t=b, t2=__shfl(bx, target_thread);
int t2_start = __shfl((int)start, target_thread) + 4;
bool c = (threadIdx.x & 0x4);
*((uint4 *)(&scratch[c ? t2_start : start])) = (c ? t2 : t);
*((uint4 *)(&scratch[c ? start : t2_start])) = (c ? t : t2);
} else if (SCHEME == SIMPLE) {
*((uint4 *)(&scratch[start ])) = b;
*((uint4 *)(&scratch[start+16])) = bx;
}
}
template <MemoryAccess SCHEME, int TEX_DIM> __device__ __forceinline__
void read_keys_direct(uint4 &b, uint4 &bx, uint32_t start)
{
uint32_t *scratch;
if (TEX_DIM == 0) scratch = c_V[(blockIdx.x*blockDim.x + threadIdx.x)/32];
if (SCHEME == ANDERSEN) {
int t2_start = __shfl((int)start, (threadIdx.x + 4)%32) + 4;
if (TEX_DIM > 0) { start /= 4; t2_start /= 4; }
bool c = (threadIdx.x & 0x4);
if (TEX_DIM == 0) {
b = *((uint4 *)(&scratch[c ? t2_start : start]));
bx = *((uint4 *)(&scratch[c ? start : t2_start]));
} else if (TEX_DIM == 1) {
b = tex1Dfetch(texRef1D_4_V, c ? t2_start : start);
bx = tex1Dfetch(texRef1D_4_V, c ? start : t2_start);
} else if (TEX_DIM == 2) {
b = tex2D(texRef2D_4_V, 0.5f + ((c ? t2_start : start)%TEXWIDTH), 0.5f + ((c ? t2_start : start)/TEXWIDTH));
bx = tex2D(texRef2D_4_V, 0.5f + ((c ? start : t2_start)%TEXWIDTH), 0.5f + ((c ? start : t2_start)/TEXWIDTH));
}
uint4 tmp = b; b = (c ? bx : b); bx = (c ? tmp : bx);
bx = __shfl(bx, (threadIdx.x + 28)%32);
} else {
if (TEX_DIM == 0) b = *((uint4 *)(&scratch[start]));
else if (TEX_DIM == 1) b = tex1Dfetch(texRef1D_4_V, start/4);
else if (TEX_DIM == 2) b = tex2D(texRef2D_4_V, 0.5f + ((start/4)%TEXWIDTH), 0.5f + ((start/4)/TEXWIDTH));
if (TEX_DIM == 0) bx = *((uint4 *)(&scratch[start+16]));
else if (TEX_DIM == 1) bx = tex1Dfetch(texRef1D_4_V, (start+16)/4);
else if (TEX_DIM == 2) bx = tex2D(texRef2D_4_V, 0.5f + (((start+16)/4)%TEXWIDTH), 0.5f + (((start+16)/4)/TEXWIDTH));
}
}
__device__ __forceinline__
void primary_order_shuffle(uint4 &b, uint4 &bx)
{
/* Inner loop shuffle targets */
int x1 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+1)&0x3);
int x2 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+2)&0x3);
int x3 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+3)&0x3);
b.w = __shfl((int)b.w, x1);
b.z = __shfl((int)b.z, x2);
b.y = __shfl((int)b.y, x3);
uint32_t tmp = b.y; b.y = b.w; b.w = tmp;
bx.w = __shfl((int)bx.w, x1);
bx.z = __shfl((int)bx.z, x2);
bx.y = __shfl((int)bx.y, x3);
tmp = bx.y; bx.y = bx.w; bx.w = tmp;
}
/*
* load_key loads a 32*32bit key from a contiguous region of memory in B.
* The input keys are in external order (i.e., 0, 1, 2, 3, ...).
* After loading, each thread has its four b and four bx keys stored
* in internal processing order.
*/
__device__ __forceinline__
void load_key_salsa(const uint32_t *B, uint4 &b, uint4 &bx)
{
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int key_offset = scrypt_block * 32;
uint32_t thread_in_block = threadIdx.x % 4;
// Read in permuted order. Key loads are not our bottleneck right now.
b.x = B[key_offset + 4*thread_in_block + (thread_in_block+0)%4];
b.y = B[key_offset + 4*thread_in_block + (thread_in_block+1)%4];
b.z = B[key_offset + 4*thread_in_block + (thread_in_block+2)%4];
b.w = B[key_offset + 4*thread_in_block + (thread_in_block+3)%4];
bx.x = B[key_offset + 4*thread_in_block + (thread_in_block+0)%4 + 16];
bx.y = B[key_offset + 4*thread_in_block + (thread_in_block+1)%4 + 16];
bx.z = B[key_offset + 4*thread_in_block + (thread_in_block+2)%4 + 16];
bx.w = B[key_offset + 4*thread_in_block + (thread_in_block+3)%4 + 16];
primary_order_shuffle(b, bx);
}
/*
* store_key performs the opposite transform as load_key, taking
* internally-ordered b and bx and storing them into a contiguous
* region of B in external order.
*/
__device__ __forceinline__
void store_key_salsa(uint32_t *B, uint4 &b, uint4 &bx)
{
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int key_offset = scrypt_block * 32;
uint32_t thread_in_block = threadIdx.x % 4;
primary_order_shuffle(b, bx);
B[key_offset + 4*thread_in_block + (thread_in_block+0)%4] = b.x;
B[key_offset + 4*thread_in_block + (thread_in_block+1)%4] = b.y;
B[key_offset + 4*thread_in_block + (thread_in_block+2)%4] = b.z;
B[key_offset + 4*thread_in_block + (thread_in_block+3)%4] = b.w;
B[key_offset + 4*thread_in_block + (thread_in_block+0)%4 + 16] = bx.x;
B[key_offset + 4*thread_in_block + (thread_in_block+1)%4 + 16] = bx.y;
B[key_offset + 4*thread_in_block + (thread_in_block+2)%4 + 16] = bx.z;
B[key_offset + 4*thread_in_block + (thread_in_block+3)%4 + 16] = bx.w;
}
/*
* load_key loads a 32*32bit key from a contiguous region of memory in B.
* The input keys are in external order (i.e., 0, 1, 2, 3, ...).
* After loading, each thread has its four b and four bx keys stored
* in internal processing order.
*/
__device__ __forceinline__
void load_key_chacha(const uint32_t *B, uint4 &b, uint4 &bx)
{
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int key_offset = scrypt_block * 32;
uint32_t thread_in_block = threadIdx.x % 4;
// Read in permuted order. Key loads are not our bottleneck right now.
b.x = B[key_offset + 4*0 + thread_in_block%4];
b.y = B[key_offset + 4*1 + thread_in_block%4];
b.z = B[key_offset + 4*2 + thread_in_block%4];
b.w = B[key_offset + 4*3 + thread_in_block%4];
bx.x = B[key_offset + 4*0 + thread_in_block%4 + 16];
bx.y = B[key_offset + 4*1 + thread_in_block%4 + 16];
bx.z = B[key_offset + 4*2 + thread_in_block%4 + 16];
bx.w = B[key_offset + 4*3 + thread_in_block%4 + 16];
}
/*
* store_key performs the opposite transform as load_key, taking
* internally-ordered b and bx and storing them into a contiguous
* region of B in external order.
*/
__device__ __forceinline__
void store_key_chacha(uint32_t *B, const uint4 &b, const uint4 &bx)
{
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int key_offset = scrypt_block * 32;
uint32_t thread_in_block = threadIdx.x % 4;
B[key_offset + 4*0 + thread_in_block%4] = b.x;
B[key_offset + 4*1 + thread_in_block%4] = b.y;
B[key_offset + 4*2 + thread_in_block%4] = b.z;
B[key_offset + 4*3 + thread_in_block%4] = b.w;
B[key_offset + 4*0 + thread_in_block%4 + 16] = bx.x;
B[key_offset + 4*1 + thread_in_block%4 + 16] = bx.y;
B[key_offset + 4*2 + thread_in_block%4 + 16] = bx.z;
B[key_offset + 4*3 + thread_in_block%4 + 16] = bx.w;
}
template <int ALGO> __device__ __forceinline__
void load_key(const uint32_t *B, uint4 &b, uint4 &bx)
{
switch(ALGO) {
case A_SCRYPT: load_key_salsa(B, b, bx); break;
case A_SCRYPT_JANE: load_key_chacha(B, b, bx); break;
}
}
template <int ALGO> __device__ __forceinline__
void store_key(uint32_t *B, uint4 &b, uint4 &bx)
{
switch(ALGO) {
case A_SCRYPT: store_key_salsa(B, b, bx); break;
case A_SCRYPT_JANE: store_key_chacha(B, b, bx); break;
}
}
/*
* salsa_xor_core (Salsa20/8 cypher)
* The original scrypt called:
* xor_salsa8(&X[0], &X[16]); <-- the "b" loop
* xor_salsa8(&X[16], &X[0]); <-- the "bx" loop
* This version is unrolled to handle both of these loops in a single
* call to avoid unnecessary data movement.
*/
#define XOR_ROTATE_ADD(dst, s1, s2, amt) { uint32_t tmp = s1+s2; dst ^= ((tmp<<amt)|(tmp>>(32-amt))); }
__device__ __forceinline__
void salsa_xor_core(uint4 &b, uint4 &bx, const int x1, const int x2, const int x3)
{
uint4 x;
b ^= bx;
x = b;
// Enter in "primary order" (t0 has 0, 4, 8, 12)
// (t1 has 5, 9, 13, 1)
// (t2 has 10, 14, 2, 6)
// (t3 has 15, 3, 7, 11)
#pragma unroll
for (int j = 0; j < 4; j++) {
// Mixing phase of salsa
XOR_ROTATE_ADD(x.y, x.x, x.w, 7);
XOR_ROTATE_ADD(x.z, x.y, x.x, 9);
XOR_ROTATE_ADD(x.w, x.z, x.y, 13);
XOR_ROTATE_ADD(x.x, x.w, x.z, 18);
/* Transpose rows and columns. */
/* Unclear if this optimization is needed: These are ordered based
* upon the dependencies needed in the later xors. Compiler should be
* able to figure this out, but might as well give it a hand. */
x.y = __shfl((int)x.y, x3);
x.w = __shfl((int)x.w, x1);
x.z = __shfl((int)x.z, x2);
/* The next XOR_ROTATE_ADDS could be written to be a copy-paste of the first,
* but the register targets are rewritten here to swap x[1] and x[3] so that
* they can be directly shuffled to and from our peer threads without
* reassignment. The reverse shuffle then puts them back in the right place.
*/
XOR_ROTATE_ADD(x.w, x.x, x.y, 7);
XOR_ROTATE_ADD(x.z, x.w, x.x, 9);
XOR_ROTATE_ADD(x.y, x.z, x.w, 13);
XOR_ROTATE_ADD(x.x, x.y, x.z, 18);
x.w = __shfl((int)x.w, x3);
x.y = __shfl((int)x.y, x1);
x.z = __shfl((int)x.z, x2);
}
b += x;
// The next two lines are the beginning of the BX-centric loop iteration
bx ^= b;
x = bx;
// This is a copy of the same loop above, identical but stripped of comments.
// Duplicated so that we can complete a bx-based loop with fewer register moves.
#pragma unroll
for (int j = 0; j < 4; j++) {
XOR_ROTATE_ADD(x.y, x.x, x.w, 7);
XOR_ROTATE_ADD(x.z, x.y, x.x, 9);
XOR_ROTATE_ADD(x.w, x.z, x.y, 13);
XOR_ROTATE_ADD(x.x, x.w, x.z, 18);
x.y = __shfl((int)x.y, x3);
x.w = __shfl((int)x.w, x1);
x.z = __shfl((int)x.z, x2);
XOR_ROTATE_ADD(x.w, x.x, x.y, 7);
XOR_ROTATE_ADD(x.z, x.w, x.x, 9);
XOR_ROTATE_ADD(x.y, x.z, x.w, 13);
XOR_ROTATE_ADD(x.x, x.y, x.z, 18);
x.w = __shfl((int)x.w, x3);
x.y = __shfl((int)x.y, x1);
x.z = __shfl((int)x.z, x2);
}
// At the end of these iterations, the data is in primary order again.
#undef XOR_ROTATE_ADD
bx += x;
}
/*
* chacha_xor_core (ChaCha20/8 cypher)
* This version is unrolled to handle both of these loops in a single
* call to avoid unnecessary data movement.
*
* load_key and store_key must not use primary order when
* using ChaCha20/8, but rather the basic transposed order
* (referred to as "column mode" below)
*/
#define CHACHA_PRIMITIVE(pt, rt, ps, amt) { uint32_t tmp = rt ^ (pt += ps); rt = ((tmp<<amt)|(tmp>>(32-amt))); }
__device__ __forceinline__
void chacha_xor_core(uint4 &b, uint4 &bx, const int x1, const int x2, const int x3)
{
uint4 x;
b ^= bx;
x = b;
// Enter in "column" mode (t0 has 0, 4, 8, 12)
// (t1 has 1, 5, 9, 13)
// (t2 has 2, 6, 10, 14)
// (t3 has 3, 7, 11, 15)
#pragma unroll
for (int j = 0; j < 4; j++) {
// Column Mixing phase of chacha
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 16)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 12)
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 8)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 7)
x.y = __shfl((int)x.y, x1);
x.z = __shfl((int)x.z, x2);
x.w = __shfl((int)x.w, x3);
// Diagonal Mixing phase of chacha
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 16)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 12)
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 8)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 7)
x.y = __shfl((int)x.y, x3);
x.z = __shfl((int)x.z, x2);
x.w = __shfl((int)x.w, x1);
}
b += x;
// The next two lines are the beginning of the BX-centric loop iteration
bx ^= b;
x = bx;
#pragma unroll
for (int j = 0; j < 4; j++) {
// Column Mixing phase of chacha
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 16)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 12)
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 8)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 7)
x.y = __shfl((int)x.y, x1);
x.z = __shfl((int)x.z, x2);
x.w = __shfl((int)x.w, x3);
// Diagonal Mixing phase of chacha
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 16)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 12)
CHACHA_PRIMITIVE(x.x ,x.w, x.y, 8)
CHACHA_PRIMITIVE(x.z ,x.y, x.w, 7)
x.y = __shfl((int)x.y, x3);
x.z = __shfl((int)x.z, x2);
x.w = __shfl((int)x.w, x1);
}
#undef CHACHA_PRIMITIVE
bx += x;
}
template <int ALGO> __device__ __forceinline__
void block_mixer(uint4 &b, uint4 &bx, const int x1, const int x2, const int x3)
{
switch(ALGO) {
case A_SCRYPT: salsa_xor_core(b, bx, x1, x2, x3); break;
case A_SCRYPT_JANE: chacha_xor_core(b, bx, x1, x2, x3); break;
}
}
/*
* The hasher_gen_kernel operates on a group of 1024-bit input keys
* in B, stored as:
* B = { k1B k1Bx k2B k2Bx ... }
* and fills up the scratchpad with the iterative hashes derived from
* those keys:
* scratch { k1h1B k1h1Bx K1h2B K1h2Bx ... K2h1B K2h1Bx K2h2B K2h2Bx ... }
* scratch is 1024 times larger than the input keys B.
* It is extremely important to stream writes effectively into scratch;
* less important to coalesce the reads from B.
*
* Key ordering note: Keys are input from B in "original" order:
* K = {k1, k2, k3, k4, k5, ..., kx15, kx16, kx17, ..., kx31 }
* After inputting into kernel_gen, each component k and kx of the
* key is transmuted into a permuted internal order to make processing faster:
* K = k, kx with:
* k = 0, 4, 8, 12, 5, 9, 13, 1, 10, 14, 2, 6, 15, 3, 7, 11
* and similarly for kx.
*/
template <int ALGO, MemoryAccess SCHEME> __global__
void kepler_scrypt_core_kernelA(const uint32_t *d_idata, int begin, int end)
{
uint4 b, bx;
int x1 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+1)&0x3);
int x2 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+2)&0x3);
int x3 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+3)&0x3);
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int start = (scrypt_block*c_SCRATCH + (SCHEME==ANDERSEN?8:4)*(threadIdx.x%4)) % c_SCRATCH_WU_PER_WARP;
int i=begin;
if (i == 0) {
load_key<ALGO>(d_idata, b, bx);
write_keys_direct<SCHEME>(b, bx, start);
++i;
} else read_keys_direct<SCHEME,0>(b, bx, start+32*(i-1));
while (i < end) {
block_mixer<ALGO>(b, bx, x1, x2, x3);
write_keys_direct<SCHEME>(b, bx, start+32*i);
++i;
}
}
template <int ALGO, MemoryAccess SCHEME> __global__
void kepler_scrypt_core_kernelA_LG(const uint32_t *d_idata, int begin, int end, unsigned int LOOKUP_GAP)
{
uint4 b, bx;
int x1 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+1)&0x3);
int x2 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+2)&0x3);
int x3 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+3)&0x3);
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int start = (scrypt_block*c_SCRATCH + (SCHEME==ANDERSEN?8:4)*(threadIdx.x%4)) % c_SCRATCH_WU_PER_WARP;
int i=begin;
if (i == 0) {
load_key<ALGO>(d_idata, b, bx);
write_keys_direct<SCHEME>(b, bx, start);
++i;
} else {
int pos = (i-1)/LOOKUP_GAP, loop = (i-1)-pos*LOOKUP_GAP;
read_keys_direct<SCHEME,0>(b, bx, start+32*pos);
while(loop--) block_mixer<ALGO>(b, bx, x1, x2, x3);
}
while (i < end) {
block_mixer<ALGO>(b, bx, x1, x2, x3);
if (i % LOOKUP_GAP == 0)
write_keys_direct<SCHEME>(b, bx, start+32*(i/LOOKUP_GAP));
++i;
}
}
/*
* hasher_hash_kernel runs the second phase of scrypt after the scratch
* buffer is filled with the iterative hashes: It bounces through
* the scratch buffer in pseudorandom order, mixing the key as it goes.
*/
template <int ALGO, MemoryAccess SCHEME, int TEX_DIM> __global__
void kepler_scrypt_core_kernelB(uint32_t *d_odata, int begin, int end)
{
uint4 b, bx;
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int start = (scrypt_block*c_SCRATCH) + (SCHEME==ANDERSEN?8:4)*(threadIdx.x%4);
if (TEX_DIM == 0) start %= c_SCRATCH_WU_PER_WARP;
int x1 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+1)&0x3);
int x2 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+2)&0x3);
int x3 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+3)&0x3);
if (begin == 0) {
read_keys_direct<SCHEME, TEX_DIM>(b, bx, start+32*c_N_1);
block_mixer<ALGO>(b, bx, x1, x2, x3);
} else load_key<ALGO>(d_odata, b, bx);
for (int i = begin; i < end; i++) {
int j = (__shfl((int)bx.x, (threadIdx.x & 0x1c)) & (c_N_1));
uint4 t, tx; read_keys_direct<SCHEME, TEX_DIM>(t, tx, start+32*j);
b ^= t; bx ^= tx;
block_mixer<ALGO>(b, bx, x1, x2, x3);
}
store_key<ALGO>(d_odata, b, bx);
}
template <int ALGO, MemoryAccess SCHEME, int TEX_DIM> __global__
void kepler_scrypt_core_kernelB_LG(uint32_t *d_odata, int begin, int end, unsigned int LOOKUP_GAP)
{
uint4 b, bx;
int scrypt_block = (blockIdx.x*blockDim.x + threadIdx.x)/THREADS_PER_WU;
int start = (scrypt_block*c_SCRATCH) + (SCHEME==ANDERSEN?8:4)*(threadIdx.x%4);
if (TEX_DIM == 0) start %= c_SCRATCH_WU_PER_WARP;
int x1 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+1)&0x3);
int x2 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+2)&0x3);
int x3 = (threadIdx.x & 0x1c) + (((threadIdx.x & 0x03)+3)&0x3);
if (begin == 0) {
int pos = c_N_1/LOOKUP_GAP, loop = 1 + (c_N_1-pos*LOOKUP_GAP);
read_keys_direct<SCHEME,TEX_DIM>(b, bx, start+32*pos);
while(loop--) block_mixer<ALGO>(b, bx, x1, x2, x3);
} else load_key<ALGO>(d_odata, b, bx);
if (SCHEME == SIMPLE)
{
// better divergent thread handling submitted by nVidia engineers, but
// supposedly this does not run with the ANDERSEN memory access scheme
int j = (__shfl((int)bx.x, (threadIdx.x & 0x1c)) & (c_N_1));
int pos = j/LOOKUP_GAP;
int loop = -1;
uint4 t, tx;
int i = begin;
while(i < end) {
if (loop==-1) {
j = (__shfl((int)bx.x, (threadIdx.x & 0x1c)) & (c_N_1));
pos = j/LOOKUP_GAP;
loop = j-pos*LOOKUP_GAP;
read_keys_direct<SCHEME,TEX_DIM>(t, tx, start+32*pos);
}
if (loop==0) {
b ^= t; bx ^= tx;
t=b;tx=bx;
}
block_mixer<ALGO>(t, tx, x1, x2, x3);
if (loop==0) {
b=t;bx=tx;
i++;
}
loop--;
}
}
else
{
// this is my original implementation, now used with the ANDERSEN
// memory access scheme only.
for (int i = begin; i < end; i++) {
int j = (__shfl((int)bx.x, (threadIdx.x & 0x1c)) & (c_N_1));
int pos = j/LOOKUP_GAP, loop = j-pos*LOOKUP_GAP;
uint4 t, tx; read_keys_direct<SCHEME,TEX_DIM>(t, tx, start+32*pos);
while(loop--) block_mixer<ALGO>(t, tx, x1, x2, x3);
b ^= t; bx ^= tx;
block_mixer<ALGO>(b, bx, x1, x2, x3);
}
}
//for (int i = begin; i < end; i++) {
// int j = (__shfl((int)bx.x, (threadIdx.x & 0x1c)) & (c_N_1));
// int pos = j/LOOKUP_GAP, loop = j-pos*LOOKUP_GAP;
// uint4 t, tx; read_keys_direct<SCHEME,TEX_DIM>(t, tx, start+32*pos);
// while(loop--) block_mixer<ALGO>(t, tx, x1, x2, x3);
// b ^= t; bx ^= tx;
// block_mixer<ALGO>(b, bx, x1, x2, x3);
//}
store_key<ALGO>(d_odata, b, bx);
}
KeplerKernel::KeplerKernel() : KernelInterface()
{
}
bool KeplerKernel::bindtexture_1D(uint32_t *d_V, size_t size)
{
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cudaChannelFormatDesc channelDesc4 = cudaCreateChannelDesc<uint4>();
texRef1D_4_V.normalized = 0;
texRef1D_4_V.filterMode = cudaFilterModePoint;
texRef1D_4_V.addressMode[0] = cudaAddressModeClamp;
checkCudaErrors(cudaBindTexture(NULL, &texRef1D_4_V, d_V, &channelDesc4, size));
return true;
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}
bool KeplerKernel::bindtexture_2D(uint32_t *d_V, int width, int height, size_t pitch)
{
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cudaChannelFormatDesc channelDesc4 = cudaCreateChannelDesc<uint4>();
texRef2D_4_V.normalized = 0;
texRef2D_4_V.filterMode = cudaFilterModePoint;
texRef2D_4_V.addressMode[0] = cudaAddressModeClamp;
texRef2D_4_V.addressMode[1] = cudaAddressModeClamp;
// maintain texture width of TEXWIDTH (max. limit is 65000)
while (width > TEXWIDTH) { width /= 2; height *= 2; pitch /= 2; }
while (width < TEXWIDTH) { width *= 2; height = (height+1)/2; pitch *= 2; }
checkCudaErrors(cudaBindTexture2D(NULL, &texRef2D_4_V, d_V, &channelDesc4, width, height, pitch));
return true;
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}
bool KeplerKernel::unbindtexture_1D()
{
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checkCudaErrors(cudaUnbindTexture(texRef1D_4_V));
return true;
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}
bool KeplerKernel::unbindtexture_2D()
{
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checkCudaErrors(cudaUnbindTexture(texRef2D_4_V));
return true;
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}
void KeplerKernel::set_scratchbuf_constants(int MAXWARPS, uint32_t** h_V)
{
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checkCudaErrors(cudaMemcpyToSymbol(c_V, h_V, MAXWARPS*sizeof(uint32_t*), 0, cudaMemcpyHostToDevice));
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}
bool KeplerKernel::run_kernel(dim3 grid, dim3 threads, int WARPS_PER_BLOCK, int thr_id, cudaStream_t stream,
uint32_t* d_idata, uint32_t* d_odata, unsigned int N, unsigned int LOOKUP_GAP, bool interactive, bool benchmark, int texture_cache)
{
bool success = true;
// make some constants available to kernel, update only initially and when changing
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static uint32_t prev_N[MAX_GPUS] = { 0 };
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if (N != prev_N[thr_id]) {
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uint32_t h_N = N;
uint32_t h_N_1 = N-1;
uint32_t h_SCRATCH = SCRATCH;
uint32_t h_SCRATCH_WU_PER_WARP = (SCRATCH * WU_PER_WARP);
uint32_t h_SCRATCH_WU_PER_WARP_1 = (SCRATCH * WU_PER_WARP) - 1;
cudaMemcpyToSymbolAsync(c_N, &h_N, sizeof(uint32_t), 0, cudaMemcpyHostToDevice, stream);
cudaMemcpyToSymbolAsync(c_N_1, &h_N_1, sizeof(uint32_t), 0, cudaMemcpyHostToDevice, stream);
cudaMemcpyToSymbolAsync(c_SCRATCH, &h_SCRATCH, sizeof(uint32_t), 0, cudaMemcpyHostToDevice, stream);
cudaMemcpyToSymbolAsync(c_SCRATCH_WU_PER_WARP, &h_SCRATCH_WU_PER_WARP, sizeof(uint32_t), 0, cudaMemcpyHostToDevice, stream);
cudaMemcpyToSymbolAsync(c_SCRATCH_WU_PER_WARP_1, &h_SCRATCH_WU_PER_WARP_1, sizeof(uint32_t), 0, cudaMemcpyHostToDevice, stream);
prev_N[thr_id] = N;
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}
// First phase: Sequential writes to scratchpad.
int batch = device_batchsize[thr_id];
//int num_sleeps = 2* ((N + (batch-1)) / batch);
//int sleeptime = 100;
unsigned int pos = 0;
do
{
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if (LOOKUP_GAP == 1) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelA<A_SCRYPT, ANDERSEN> <<< grid, threads, 0, stream >>>(d_idata, pos, min(pos+batch, N));
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelA<A_SCRYPT_JANE, SIMPLE> <<< grid, threads, 0, stream >>>(d_idata, pos, min(pos+batch, N));
} else {
if (IS_SCRYPT()) kepler_scrypt_core_kernelA_LG<A_SCRYPT, ANDERSEN> <<< grid, threads, 0, stream >>>(d_idata, pos, min(pos+batch, N), LOOKUP_GAP);
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelA_LG<A_SCRYPT_JANE, SIMPLE> <<< grid, threads, 0, stream >>>(d_idata, pos, min(pos+batch, N), LOOKUP_GAP);
}
pos += batch;
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} while (pos < N);
// Second phase: Random read access from scratchpad.
pos = 0;
do
{
if (LOOKUP_GAP == 1) {
if (texture_cache == 0) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelB<A_SCRYPT ,ANDERSEN, 0><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N));
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelB<A_SCRYPT_JANE,SIMPLE, 0><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N));
} else if (texture_cache == 1) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelB<A_SCRYPT ,ANDERSEN,1><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N));
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelB<A_SCRYPT_JANE,SIMPLE, 1><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N));
} else if (texture_cache == 2) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelB<A_SCRYPT ,ANDERSEN,2><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N));
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelB<A_SCRYPT_JANE,SIMPLE, 2><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N));
}
} else {
if (texture_cache == 0) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelB_LG<A_SCRYPT ,ANDERSEN,0><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N), LOOKUP_GAP);
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelB_LG<A_SCRYPT_JANE,SIMPLE, 0><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N), LOOKUP_GAP);
} else if (texture_cache == 1) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelB_LG<A_SCRYPT ,ANDERSEN,1><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N), LOOKUP_GAP);
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelB_LG<A_SCRYPT_JANE,SIMPLE, 1><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N), LOOKUP_GAP);
} else if (texture_cache == 2) {
if (IS_SCRYPT()) kepler_scrypt_core_kernelB_LG<A_SCRYPT ,ANDERSEN,2><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N), LOOKUP_GAP);
if (IS_SCRYPT_JANE()) kepler_scrypt_core_kernelB_LG<A_SCRYPT_JANE,SIMPLE, 2><<< grid, threads, 0, stream >>>(d_odata, pos, min(pos+batch, N), LOOKUP_GAP);
}
}
pos += batch;
} while (pos < N);
return success;
}