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Copy pathops_aot.cpp
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356 lines (332 loc) · 13.4 KB
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#include "gpu.hpp"
#include <array>
#include <cstdio>
#include <future>
#include <memory>
#include "kernels.h"
#include "ops_aot.hpp"
#include "experimental/wgsl.h" // loopUnrolling
using namespace gpu;
Kernel encoder_forward(Context& ctx, Tensor& out,
Tensor& inp, Tensor& wte, Tensor& wpe,
int B, int T, int C){
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
unsigned long v = VOCAB_SIZE;
struct EncoderParams {
uint32_t B;
uint32_t T;
uint32_t C;
};
setLogLevel(kError);
return createKernel(ctx, {kShaderEncoder, 256, kf32},
Bindings{inp, wte, wpe, out},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
EncoderParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c)
});
}
Kernel encoder_backward(Context& ctx, Tensor& dwte, Tensor& dwpe,
Tensor& dout, Tensor& inp,
int B, int T, int C) {
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
unsigned long v = VOCAB_SIZE;
struct EncoderParams {
uint32_t B;
uint32_t T;
uint32_t C;
};
setLogLevel(kError);
return createKernel(ctx, {kShaderEncoderBackward, 256, kf32},
Bindings{dwte, dwpe, dout, inp},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
EncoderParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c)
});
}
Kernel layernorm_forward(Context& ctx, Tensor& out, Tensor& mean, Tensor& rstd,
Tensor& inp, Tensor& weight, Tensor& bias,
int B, int T, int C){
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
struct LayerNormParams {
uint32_t B;
uint32_t T;
uint32_t C;
};
setLogLevel(kError);
return createKernel(ctx, {kShaderLayerNorm, 256, kf32},
Bindings{inp, weight, bias, out, mean, rstd},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
LayerNormParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c)
});
}
Kernel layernorm_backward(Context& ctx, Tensor& dinp, Tensor& dweight, Tensor& dbias,
Tensor& dout, Tensor& inp, Tensor& weight, Tensor& mean, Tensor& rstd,
int B, int T, int C){
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
struct LayerNormParams {
uint32_t B;
uint32_t T;
uint32_t C;
};
setLogLevel(kError);
return createKernel(ctx, {kShaderLayerNormBackward, 256, kf32},
Bindings{dinp, dweight, dbias, dout, inp, weight, mean, rstd},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
LayerNormParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c)
});
}
struct DurationTime {
std::chrono::high_resolution_clock::time_point start;
std::chrono::high_resolution_clock::time_point end;
std::chrono::microseconds duration;
std::string src;
bool verbose;
inline DurationTime(const std::string& src, bool verbose = true) {
this->src = src;
this->verbose = verbose;
start = std::chrono::high_resolution_clock::now();
}
inline ~DurationTime() {
end = std::chrono::high_resolution_clock::now();
duration = std::chrono::duration_cast<std::chrono::microseconds>(end - start);
if (this->verbose) {
printf("Duration(%s): %.1f microseconds\n", src.c_str(), static_cast<double>(duration.count()));
}
}
};
Kernel matmul_forward(Context& ctx, Tensor& out,
const Tensor& inp, const Tensor& weight, const Tensor& bias,
int B, int T, int C, int OC){
bool verbose = false;
DurationTime duration("matmul_forward_gpu", verbose);
struct MatmulParams {
uint32_t B;
uint32_t T;
uint32_t C;
uint32_t OC;
};
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
unsigned long oc = static_cast<unsigned long>(OC);
setLogLevel(kError);
constexpr size_t BT = 64;
constexpr size_t BC = 8;
constexpr size_t BOC = 64;
constexpr size_t TT = BT / BC;
constexpr size_t TOC = BOC / BC;
size_t num_threads = BT * BOC / (TT * TOC);
Shape wgSize = {num_threads, 1, 1};
Shape nWorkgroups = {b, cdiv(T, BT), cdiv(OC, BOC)};
std::string kShaderMatmul2DTiling_(kShaderMatmul2DTiling);
std::string kShaderMatmul2D(loopUnrolling(
replaceAll(kShaderMatmul2DTiling_,
{{"{{precision}}", toString(kf32)},
{"{{BT}}", toString(BT)},
{"{{BC}}", toString(BC)},
{"{{BOC}}", toString(BOC)},
{"{{TT}}", toString(TT)},
{"{{TOC}}", toString(TOC)},
{"{{NUM_TILEI}}", toString(BT * BC / num_threads)},
{"{{NUM_TILEW}}", toString(BOC * BC / num_threads)}
})
)
);
return createKernel(ctx, {kShaderMatmul2D, wgSize, kf32},
Bindings{inp, weight, bias, out},
nWorkgroups,
/* params */
MatmulParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c),
static_cast<uint32_t>(oc)
});
}
Kernel matmul_backward(Context& ctx, Tensor& dinp, Tensor& dweight, Tensor& dbias,
const Tensor& dout, const Tensor& inp, const Tensor& weight,
int B, int T, int C, int OC){
struct MatmulParams {
uint32_t B;
uint32_t T;
uint32_t C;
uint32_t OC;
};
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
unsigned long oc = static_cast<unsigned long>(OC);
setLogLevel(kError);
return createKernel(ctx, {kShaderMatmulBackward, 256, kf32},
Bindings{dinp, dweight, dbias, dout, inp, weight},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
MatmulParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c),
static_cast<uint32_t>(oc)
});
}
Kernel attention_forward(Context& ctx, Tensor& out, Tensor& preatt, Tensor& att,
Tensor& inp,
int B, int T, int C, int NH){
struct AttentionParams {
uint32_t B;
uint32_t T;
uint32_t C;
uint32_t NH;
};
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
unsigned long nh = static_cast<unsigned long>(NH);
setLogLevel(kError);
return createKernel(ctx, {kShaderAttention, 256, kf32},
Bindings{inp, preatt, att, out},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
AttentionParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c),
static_cast<uint32_t>(nh)
});
}
Kernel attention_backward(Context& ctx, Tensor& dinp, Tensor& dpreatt, Tensor& datt,
Tensor& dout, Tensor& inp, Tensor& att,
int B, int T, int C, int NH){
struct AttentionParams {
uint32_t B;
uint32_t T;
uint32_t C;
uint32_t NH;
};
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long c = static_cast<unsigned long>(C);
unsigned long nh = static_cast<unsigned long>(NH);
setLogLevel(kError);
return createKernel(ctx, {kShaderAttentionBackward, 256, kf32},
Bindings{dinp, dpreatt, datt, dout, inp, att},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
AttentionParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(c),
static_cast<uint32_t>(nh)
});
}
Kernel gelu_forward(Context& ctx, Tensor& out, Tensor& inp, int n) {
unsigned long N = static_cast<unsigned long>(n);
setLogLevel(kError);
return createKernel(ctx, {kShaderGelu, 256, kf32},
Bindings{inp, out},
/* nWorkgroups */ {cdiv(N, 256), 1, 1});
}
Kernel gelu_backward(Context& ctx, Tensor& dinp, Tensor& inp, Tensor& dout, int N){
unsigned long n = static_cast<unsigned long>(N);
setLogLevel(kError);
return createKernel(ctx, {kShaderGeluBackward, 256, kf32},
Bindings{inp, dout, dinp},
/* nWorkgroups */ {cdiv(n, 256), 1, 1});
}
Kernel residual_forward(Context& ctx, Tensor& out, Tensor& inp1, Tensor& inp2, int N){
unsigned long n = static_cast<unsigned long>(N);
setLogLevel(kError);
return createKernel(ctx, {kShaderResidual, 256, kf32},
Bindings{inp1, inp2, out},
/* nWorkgroups */ {cdiv(n, 256), 1, 1});
}
Kernel residual_backward(Context& ctx, Tensor& dinp1, Tensor& dinp2, Tensor& dout, int N){
unsigned long n = static_cast<unsigned long>(N);
setLogLevel(kError);
return createKernel(ctx, {kShaderResidualBackward, 256, kf32},
Bindings{dout, dinp1, dinp2},
/* nWorkgroups */ {cdiv(n, 256), 1, 1});
}
Kernel softmax_forward(Context& ctx, Tensor& probs, Tensor& logits, int B, int T, int V, int Vp) {
struct SoftmaxParam {
uint32_t N;
uint32_t C;
uint32_t Cp;
};
uint32_t b = static_cast<uint32_t>(B);
uint32_t t = static_cast<uint32_t>(T);
uint32_t c = static_cast<uint32_t>(V);
uint32_t cp = static_cast<uint32_t>(Vp);
assert( (B*T) % 256 == 0);
return createKernel(
ctx, {kShaderSoftmax1, 256, kf32}, Bindings{logits, probs},
Shape{cdiv(B * T, 256), 1, 1}, SoftmaxParam{b * t, c, cp});
}
Kernel crossentropy_forward(Context& ctx, Tensor& losses,
Tensor& probs, Tensor& targets,
int B, int T, int Vp){
struct CrossEntropyParams {
uint32_t B;
uint32_t T;
uint32_t VP;
};
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long vp = static_cast<unsigned long>(Vp);
setLogLevel(kError);
return createKernel(ctx, {kShaderCrossEntropyForward, 256, kf32},
Bindings{losses, probs, targets},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
CrossEntropyParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(vp)
});
}
Kernel crossentropy_softmax_backward(Context& ctx, Tensor& dlogits,
Tensor& dlosses, Tensor& probs, Tensor& targets,
int B, int T, int V, int Vp){
struct CrossEntropySoftmaxBackwardParams {
uint32_t B;
uint32_t T;
uint32_t V;
uint32_t VP;
};
unsigned long b = static_cast<unsigned long>(B);
unsigned long t = static_cast<unsigned long>(T);
unsigned long v = static_cast<unsigned long>(V);
unsigned long vp = static_cast<unsigned long>(Vp);
setLogLevel(kError);
return createKernel(ctx, {kShaderCrossEntropySoftmaxBackward, 256, kf32},
Bindings{dlogits, dlosses, probs, targets},
/* nWorkgroups */ {cdiv(b * t, 256), 1, 1},
/* params */
CrossEntropySoftmaxBackwardParams{
static_cast<uint32_t>(b),
static_cast<uint32_t>(t),
static_cast<uint32_t>(v),
static_cast<uint32_t>(vp)
});
}
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