mirror of
https://github.com/GOSTSec/ccminer
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bf55536ba6
fix most part of indentation and headers but ive copied whirlpool and x17 stuff in a new m7 folder
277 lines
6.7 KiB
Plaintext
277 lines
6.7 KiB
Plaintext
/*
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* tiger-192 djm34
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*
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*/
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/*
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* tiger-192 kernel implementation.
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*
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* ==========================(LICENSE BEGIN)============================
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*
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* Copyright (c) 2014 djm34
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*
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* Permission is hereby granted, free of charge, to any person obtaining
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* a copy of this software and associated documentation files (the
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* "Software"), to deal in the Software without restriction, including
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* without limitation the rights to use, copy, modify, merge, publish,
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* distribute, sublicense, and/or sell copies of the Software, and to
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* permit persons to whom the Software is furnished to do so, subject to
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* the following conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
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* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
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* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
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* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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*
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* ===========================(LICENSE END)=============================
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*
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* @author phm <phm@inbox.com>
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*/
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//#include <stdio.h>
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#include <memory.h>
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#include "cuda_helper.h"
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#define HIWORD _HIWORD
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#define LOWORD _LOWORD
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#if 0
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#define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
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inline void gpuAssert(cudaError_t code, char *file, int line, bool abort=true)
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{
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if (code != cudaSuccess)
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{
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fprintf(stderr,"GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
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if (abort) exit(code);
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}
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}
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#endif
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extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id);
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__device__ __forceinline__
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void bigmul(uint64_t *w, uint64_t* am, uint64_t* bm, int sizea, int sizeb, int thread)
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{
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int threads = 256*256*8*2;
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#pragma unroll
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for (int i=0;i<sizea+sizeb;i++) {w[i*threads+thread]=0;}
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#pragma unroll
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for (int i=0;i<sizeb;i++)
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{
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uint64_t c=0;
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uint64_t u=0,v=0;
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#pragma unroll
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for (int j=0;j<sizea;j++) {
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muladd128(u,v,am[j*threads+thread],bm[i*threads+thread],w[(i+j)*threads+thread],c);
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w[(i+j)*threads+thread]=v;
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c=u;
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}
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w[(i+sizea)*threads+thread]=u;
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}
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}
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__global__
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void m7_bigmul1_gpu(int threads, int sizea, int sizeb, uint64_t* am, uint64_t* bm, uint64_t *w)
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{
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int thread = (blockDim.x * blockIdx.x + threadIdx.x);
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if (thread < threads)
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{
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#pragma unroll
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for (int i=0;i<sizea+sizeb;i++) {w[i*threads+thread]=0;}
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#pragma unroll
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for (int i=0;i<sizeb;i++) {
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uint64_t c=0;
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uint64_t u=0,v=0;
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#pragma unroll
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for (int j=0;j<sizea;j++) {
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muladd128(u,v,am[j*threads+thread],bm[i*threads+thread],w[(i+j)*threads+thread],c);
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w[(i+j)*threads+thread]=v;
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c=u;
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}
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w[(i+sizea)*threads+thread]=u;
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}
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} // thread
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}
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__global__
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void m7_bigmul_unroll1_gpu(int threads, uint64_t* am, uint64_t* bm, uint64_t *w)
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{
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int thread = (blockDim.x * blockIdx.x + threadIdx.x);
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if (thread < threads)
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{
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#pragma unroll 32
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for (int i=0;i<32;i++) {
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w[i*threads + thread]=0;
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}
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#if __CUDA_ARCH__ < 500
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#pragma unroll 32
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#endif
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for (int i=0;i<32;i++)
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{
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uint64_t c=0;
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uint64_t u=0,v=0;
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#pragma unroll 3
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for (int j=0;j<3;j++) {
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muladd128(u,v,am[j*threads+thread],bm[i*threads+thread],w[(i+j)*threads+thread],c);
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w[(i+j)*threads+thread]=v;
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c=u;
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}
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w[(i+3)*threads+thread]=u;
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}
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} // threads
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}
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__global__
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void m7_bigmul_unroll1_gpu_std(int threads, uint64_t* amg, uint64_t* bmg, uint64_t *wg)
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{
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int thread = (blockDim.x * blockIdx.x + threadIdx.x);
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if (thread < threads)
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{
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uint64_t * am = amg + 8*thread;
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uint64_t * bm = bmg + 38*thread;
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uint64_t * w = wg + 38*thread;
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#pragma unroll 32
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for (int i=0;i<32;i++) {
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w[i]=0;
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}
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#if __CUDA_ARCH__ < 500
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#pragma unroll 32
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#endif
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for (int i=0;i<32;i++)
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{
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uint64_t c=0;
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uint64_t u=0,v=0;
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#pragma unroll 3
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for (int j=0;j<3;j++) {
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muladd128(u,v,am[j],bm[i],w[(i+j)],c);
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w[(i+j)]=v;
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c=u;
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}
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w[(i+3)]=u;
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}
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} // threads
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}
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__global__
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void m7_bigmul_unroll2_gpu(int threads, uint64_t* am, uint64_t* bm, uint64_t *w)
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{
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int thread = (blockDim.x * blockIdx.x + threadIdx.x);
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if (thread < threads)
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{
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#if __CUDA_ARCH__ < 500
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#pragma unroll
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#endif
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for (int i=0;i<38;i++) {
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w[i*threads+thread]=0;
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}
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#if __CUDA_ARCH__ < 500
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#pragma unroll
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#endif
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for (int i=0;i<35;i++)
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{
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uint64_t c=0;
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uint64_t u=0,v=0;
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#if __CUDA_ARCH__ < 500
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#pragma unroll
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#endif
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for (int j=0;j<3;j++) {
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muladd128(u,v,am[j*threads+thread],bm[i*threads+thread],w[(i+j)*threads+thread],c);
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w[(i+j)*threads+thread]=v;
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c=u;
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}
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w[(i+3)*threads+thread]=u;
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}
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} // thread
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}
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__global__
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void m7_bigmul_unroll2_gpu_std(int threads, uint64_t* amg, uint64_t* bmg, uint64_t *wg)
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{
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int thread = (blockDim.x * blockIdx.x + threadIdx.x);
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if (thread < threads)
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{
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uint64_t * am = amg + 8*thread;
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uint64_t * bm = bmg + 38*thread;
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uint64_t * w = wg + 38*thread;
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#if __CUDA_ARCH__ < 500
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#pragma unroll
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#endif
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for (int i=0;i<38;i++) {
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w[i]=0;
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}
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#if __CUDA_ARCH__ < 500
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#pragma unroll
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#endif
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for (int i=0;i<35;i++)
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{
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uint64_t c=0;
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uint64_t u=0,v=0;
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#if __CUDA_ARCH__ < 500
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#pragma unroll
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#endif
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for (int j=0;j<3;j++) {
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muladd128(u,v,am[j],bm[i],w[(i+j)],c);
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w[(i+j)]=v;
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c=u;
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}
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w[(i+3)]=u;
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}
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} // thread
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}
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__host__ void m7_bigmul1_cpu(int thr_id, int threads,int len1,int len2,uint64_t* Hash1, uint64_t* Hash2,uint64_t *finalHash,int order)
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{
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const int threadsperblock = 256;
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dim3 grid((threads + threadsperblock-1)/threadsperblock);
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dim3 block(threadsperblock);
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size_t shared_size =0;
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m7_bigmul1_gpu<<<grid, block, shared_size>>>(threads,len1,len2,Hash1,Hash2,finalHash);
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// MyStreamSynchronize(NULL, order, thr_id);
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// gpuErrchk(cudaDeviceSynchronize());
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// gpuErrchk(cudaThreadSynchronize());
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}
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__host__ void m7_bigmul_unroll1_cpu(int thr_id, int threads,uint64_t* Hash1, uint64_t* Hash2,uint64_t *finalHash,int order)
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{
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const int threadsperblock = 256;
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dim3 grid((threads + threadsperblock-1)/threadsperblock);
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dim3 block(threadsperblock);
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size_t shared_size =0;
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m7_bigmul_unroll1_gpu<<<grid, block, shared_size>>>(threads,Hash1,Hash2,finalHash);
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}
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__host__ void m7_bigmul_unroll2_cpu(int thr_id, int threads,uint64_t* Hash1, uint64_t* Hash2,uint64_t *finalHash,int order)
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{
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const int threadsperblock = 256;
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dim3 grid((threads + threadsperblock-1)/threadsperblock);
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dim3 block(threadsperblock);
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size_t shared_size =0;
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m7_bigmul_unroll2_gpu<<<grid, block, shared_size>>>(threads,Hash1,Hash2,finalHash);
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}
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__host__ void m7_bigmul_init(int thr_id, int threads)
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{
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// why I am here ?
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}
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