bitsandbytes-rocm/csrc/ops.cu
2021-10-20 18:37:44 -07:00

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// Copyright (c) Facebook, Inc. and its affiliates.
//
// This source code is licensed under the MIT license found in the
// LICENSE file in the root directory of this source tree.
#include <ops.cuh>
#include <kernels.cuh>
#include <cub/device/device_scan.cuh>
#include <limits>
#include <BinSearch.h>
using namespace BinSearch;
using std::cout;
using std::endl;
#define BLOCK_SIZE 4096
struct quantize_block_args
{
BinAlgo<Scalar, float, Direct2> *bin_searcher;
float *code;
float *A;
float *absmax;
unsigned char *out;
int block_end;
int block_idx;
int threadidx;
};
void *quantize_block(void *arguments)
{
// 1. find absmax in block
// 2. divide input value by absmax to normalize into [-1.0, 1.0]
// 3. do binary search to find the closest value
// 4. check minimal distance
// 5. store index
struct quantize_block_args *args = (quantize_block_args*)arguments;
// 1. find absmax in block
float absmax_block = -FLT_MAX;
for (int i = args->block_idx; i < args->block_end; i++)
absmax_block = fmax(absmax_block, fabs(args->A[i]));
args->absmax[args->block_idx/BLOCK_SIZE] = absmax_block;
for (int i = args->block_idx; i < args->block_end; i++)
{
// 2. divide input value by absmax to normalize into [-1.0, 1.0]
// 3. do binary search to find the closest value
float normed_value = args->A[i]/absmax_block;
int idx = args->bin_searcher->scalar(normed_value);
// 4. check minimal distance
// The binary search returns always the value to the left, which might not be the closest value
if(idx < 255)
{
float dist_left = fabs(normed_value-(args->code[idx]));
float dist_right = fabs(normed_value-(args->code[idx+1]));
if(dist_right < dist_left){ idx+=1; }
}
// 5. store index
args->out[i] = (unsigned char)idx;
}
return NULL;
}
void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n)
{
// the default code is has range [-0.993, 1.0] which can cause an error in the binary search algorithm used below
code[0] = -1.0f;
int num_blocks = n/BLOCK_SIZE;
num_blocks += n % BLOCK_SIZE == 0 ? 0 : 1;
pthread_t *threads = (pthread_t*)malloc(sizeof(pthread_t)*num_blocks);
struct quantize_block_args **args = (quantize_block_args**)malloc(num_blocks*sizeof(quantize_block_args*));
for(int i = 0; i < num_blocks; i++)
args[i] = (quantize_block_args*)malloc(sizeof(quantize_block_args));
const uint32 elements_code = 256;
BinAlgo<Scalar, float, Direct2> bin_searcher(code, elements_code);
for(int block_idx = 0; block_idx < n; block_idx+=BLOCK_SIZE)
{
int valid_items = n-block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
int block_end = block_idx + valid_items;
struct quantize_block_args *arg = args[block_idx/BLOCK_SIZE];
arg->bin_searcher = &bin_searcher;
arg->code = code;
arg->A = A;
arg->absmax = absmax;
arg->out = out;
arg->block_end = block_end;
arg->block_idx = block_idx;
arg->threadidx = block_idx/BLOCK_SIZE;
pthread_create(&threads[block_idx/BLOCK_SIZE], NULL, &quantize_block, (void *)arg);
}
for(int i = 0; i < num_blocks; i++)
int err = pthread_join(threads[i], NULL);
free(threads);
for(int i = 0; i < num_blocks; i++)
free(args[i]);
free(args);
}
void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n)
{
for(int block_idx = 0; block_idx < n; block_idx+=BLOCK_SIZE)
{
int valid_items = n-block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
int block_end = block_idx + valid_items;
for (int i = block_idx; i < block_end; i++)
out[i] = code[A[i]]*absmax[block_idx/BLOCK_SIZE];
}
}
void histogramScatterAdd2D(float* histogram, int *index1, int *index2, float *src, int maxidx1, int n)
{
int threads = 512;
int blocks = n/threads;
blocks = n % threads == 0 ? blocks : blocks + 1;
kHistogramScatterAdd2D<<<blocks, 512>>>(histogram, index1, index2, src, maxidx1, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
template <typename T> void estimateQuantiles(T *A, float *code, float offset, int n)
{
int blocks = n/4096;
blocks = n % 4096 == 0 ? blocks : blocks + 1;
CUDA_CHECK_RETURN(cudaMemset(code, 0, 256*sizeof(float)));
kEstimateQuantiles<T><<<blocks, 512>>>(A, code, offset, std::numeric_limits<T>::max(), n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
void quantize(float *code, float *A, unsigned char *out, int n)
{
int blocks = n/1024;
blocks = n % 1024 == 0 ? blocks : blocks + 1;
kQuantize<<<blocks, 1024>>>(code, A, out, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
void dequantize(float *code, unsigned char *A, float *out, int n)
{
int blocks = n/1024;
blocks = n % 1024 == 0 ? blocks : blocks + 1;
kDequantize<<<blocks, 1024>>>(code, A, out, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
template <typename T, int STOCHASTIC> void quantizeBlockwise(float * code, T *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n)
{
int blocks = n/4096;
blocks = n % 4096 == 0 ? blocks : blocks + 1;
kQuantizeBlockwise<T, 4096, 4, STOCHASTIC><<<blocks, 1024>>>(code, A, absmax, out, rand, rand_offset, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
template<typename T> void dequantizeBlockwise(float *code, unsigned char *A, float *absmax, T *out, int blocksize, const int n)
{
int blocks = n/blocksize;
blocks = n % blocksize == 0 ? blocks : blocks + 1;
if(blocksize == 4096)
kDequantizeBlockwise<T, 4096, 1024, 4><<<blocks, 4096/4>>>(code, A, absmax, out, n);
else if(blocksize == 2048)
kDequantizeBlockwise<T, 2048, 512, 4><<<blocks, 2048/4>>>(code, A, absmax, out, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
template<typename T, int OPTIMIZER> void optimizer32bit(T* g, T* p,
float* state1, float* state2, float *unorm, float max_unorm, float param_norm,
const float beta1, const float beta2, const float eps, const float weight_decay,
const int step, const float lr, const float gnorm_scale, bool skip_zeros, const int n)
{
int blocks = n/4096;
blocks = n % 4096 == 0 ? blocks : blocks + 1;
switch(OPTIMIZER)
{
case ADAM:
if(max_unorm > 0.0f)
{
CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1*sizeof(float)));
kPreconditionOptimizer32bit2State<T, OPTIMIZER, 4096, 8><<<blocks, 512>>>(g, p, state1, state2, unorm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
kOptimizer32bit2State<T, OPTIMIZER><<<blocks, 1024>>>(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
break;
case MOMENTUM:
case RMSPROP:
if(max_unorm > 0.0f)
{
CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1*sizeof(float)));
kPreconditionOptimizer32bit1State<T, OPTIMIZER, 4096, 8><<<blocks, 512>>>(g, p, state1, unorm, beta1, eps, weight_decay, step, lr, gnorm_scale, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
kOptimizer32bit1State<T, OPTIMIZER><<<blocks, 1024>>>(g, p, state1, unorm, max_unorm, param_norm, beta1, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
break;
}
}
template<typename T, int OPTIMIZER> void optimizerStatic8bit(T* p, T* g,
unsigned char* state1, unsigned char* state2,
float *unorm, float max_unorm, float param_norm,
float beta1, float beta2,
float eps, int step, float lr,
float* quantiles1, float* quantiles2,
float* max1, float* max2, float* new_max1, float* new_max2,
float weight_decay,
const float gnorm_scale, int n)
{
int blocks = n/4096;
blocks = n % 4096 == 0 ? blocks : blocks + 1;
if(max_unorm > 0.0f){ CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1*sizeof(float))); }
switch(OPTIMIZER)
{
case ADAM:
CUDA_CHECK_RETURN(cudaMemset(new_max1, 0, 1*sizeof(float)));
CUDA_CHECK_RETURN(cudaMemset(new_max2, 0, 1*sizeof(float)));
kPreconditionOptimizerStatic8bit2State<T, OPTIMIZER><<<blocks, 256>>>(p, g, state1, state2, unorm, beta1, beta2, eps, step, quantiles1, quantiles2, max1, max2, new_max1, new_max2, gnorm_scale, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
kOptimizerStatic8bit2State<T, OPTIMIZER><<<blocks, 1024>>>(p, g, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr,
quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
break;
case MOMENTUM:
case RMSPROP:
CUDA_CHECK_RETURN(cudaMemset(new_max1, 0, 1*sizeof(float)));
kPreconditionOptimizerStatic8bit1State<T, OPTIMIZER><<<blocks, 256>>>(p, g, state1, unorm, beta1, eps, step, quantiles1, max1, new_max1, weight_decay, gnorm_scale, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
kOptimizerStatic8bit1State<T, OPTIMIZER><<<blocks, 1024>>>(p, g, state1, unorm, max_unorm, param_norm, beta1, eps, step, lr,
quantiles1, max1, new_max1, weight_decay, gnorm_scale, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
break;
default:
break;
}
}
#define BLOCKSIZE_2STATE 2048
#define NUM_2STATE 8
#define BLOCKSIZE_1STATE 2048
#define NUM_1STATE 8
template<typename T, int OPTIMIZER> void optimizerStatic8bitBlockwise(T* p, T* g,
unsigned char* state1, unsigned char* state2, float beta1, float beta2, float eps, int step, float lr,
float* quantiles1, float* quantiles2, float* absmax1, float* absmax2, float weight_decay, const float gnorm_scale, bool skip_zeros, int n)
{
int blocks = 0;
switch(OPTIMIZER)
{
case ADAM:
blocks = n/BLOCKSIZE_2STATE;
blocks = n % BLOCKSIZE_2STATE == 0 ? blocks : blocks + 1;
kOptimizerStatic8bit2StateBlockwise<T, OPTIMIZER, BLOCKSIZE_2STATE, NUM_2STATE><<<blocks, BLOCKSIZE_2STATE/NUM_2STATE>>>(p, g, state1, state2, beta1, beta2, eps, step, lr,
quantiles1, quantiles2, absmax1, absmax2, weight_decay, gnorm_scale, skip_zeros, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
break;
case MOMENTUM:
case RMSPROP:
blocks = n/BLOCKSIZE_1STATE;
blocks = n % BLOCKSIZE_1STATE == 0 ? blocks : blocks + 1;
kOptimizerStatic8bit1StateBlockwise<T, OPTIMIZER, BLOCKSIZE_1STATE, NUM_1STATE><<<blocks, BLOCKSIZE_1STATE/NUM_1STATE>>>(p, g, state1, beta1, beta2, eps, step, lr,
quantiles1, absmax1, weight_decay, gnorm_scale, skip_zeros, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
break;
}
}
template<typename T> void percentileClipping(T * g, float *gnorm_vec, int step, const int n)
{
int blocks = n/2048;
blocks = n % 2048 == 0 ? blocks : blocks + 1;
CUDA_CHECK_RETURN(cudaMemset(&gnorm_vec[step % 100], 0, 1*sizeof(float)));
kPercentileClipping<T, 2048, 4><<<blocks, 512>>>(g, gnorm_vec, step, n);
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
//==============================================================
// TEMPLATE DEFINITIONS
//==============================================================
template void estimateQuantiles(half *A, float *code, float offset, int n);
template void estimateQuantiles(float *A, float *code, float offset, int n);
template void quantizeBlockwise<half, 0>(float * code, half *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
template void quantizeBlockwise<float, 0>(float * code, float *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
template void quantizeBlockwise<half, 1>(float * code, half *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
template void quantizeBlockwise<float, 1>(float * code, float *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
template void dequantizeBlockwise<half>(float *code, unsigned char *A, float *absmax, half *out, int blocksize, const int n);
template void dequantizeBlockwise<float>(float *code, unsigned char *A, float *absmax, float *out, int blocksize, const int n);
#define MAKE_optimizer32bit(name, gtype) \
template void optimizer32bit<gtype, name>(gtype* g, gtype* p, \
float* state1, float* state2, float* unorm, float max_unorm, float param_norm, \
const float beta1, const float beta2, const float eps, const float weight_decay, \
const int step, const float lr, const float gnorm_scale, const bool skip_zeros, const int n);
MAKE_optimizer32bit(ADAM, half)
MAKE_optimizer32bit(ADAM, float)
MAKE_optimizer32bit(MOMENTUM, half)
MAKE_optimizer32bit(MOMENTUM, float)
MAKE_optimizer32bit(RMSPROP, half)
MAKE_optimizer32bit(RMSPROP, float)
#define MAKE_optimizerStatic8bit(name, gtype) \
template void optimizerStatic8bit<gtype, name>(gtype* p, gtype* g, unsigned char* state1, unsigned char* state2, \
float *unorm, float max_unorm, float param_norm, \
float beta1, float beta2, \
float eps, int step, float lr, \
float* quantiles1, float* quantiles2, \
float* max1, float* max2, float* new_max1, float* new_max2, \
float weight_decay, \
const float gnorm_scale, int n); \
MAKE_optimizerStatic8bit(ADAM, half)
MAKE_optimizerStatic8bit(ADAM, float)
MAKE_optimizerStatic8bit(MOMENTUM, half)
MAKE_optimizerStatic8bit(MOMENTUM, float)
MAKE_optimizerStatic8bit(RMSPROP, half)
MAKE_optimizerStatic8bit(RMSPROP, float)
#define MAKE_optimizerStatic8bitBlockwise(gtype, optim_name) \
template void optimizerStatic8bitBlockwise<gtype, optim_name>(gtype* p, gtype* g, \
unsigned char* state1, unsigned char* state2, float beta1, float beta2, float eps, int step, float lr, \
float* quantiles1, float* quantiles2, float* absmax1, float* absmax2, float weight_decay, const float gnorm_scale, bool skip_zeros, int n); \
MAKE_optimizerStatic8bitBlockwise(half, ADAM);
MAKE_optimizerStatic8bitBlockwise(float, ADAM);
MAKE_optimizerStatic8bitBlockwise(half, MOMENTUM);
MAKE_optimizerStatic8bitBlockwise(float, MOMENTUM);
MAKE_optimizerStatic8bitBlockwise(half, RMSPROP);
MAKE_optimizerStatic8bitBlockwise(float, RMSPROP);
template void percentileClipping(float * g, float *gnorm_vec, int step, const int n);
template void percentileClipping(half * g, float *gnorm_vec, int step, const int n);