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[CK-Tile] Universal gemm memory bound pipeline (#1558)

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* CK-Tile GEMM with memory bound pipeline.

* Memory bound gemm pipeline.

* Fix not closed namespace.

* Block gemm mem pipeline draft.

* Do not use ck_tile:: within ck_tile namespace.

* Refactoring & Move Layout info to pipeline problem.

* Get hot loop and TailNum information before lunching kernel.

* Fixes in pipeline.

* Add comment to load_tile_raw and change variable naming style.

* Few small changes & formatting.

* Do not use macro.

* Add gtests.

* Use AccDataType for Output of MFMA instruction.

* Formatting.

* Refactor gemm examples.

* Switch over to current block gemm.

* Use currently available pipeline policy.

* Refactoring and review comment.s

* Fixes after merge.

* Add missing include.

* Add load tile overload which accepts output tensor as parameter.

* This give 8% perf boost at the cost of using more registers.

* Rename example.

* Small changes.

* Fix compilation err and lower K.

* Support different layouts for A/B

* Fix vector size for different layouts.

* Rename Alignment into VectorSize

* Unblock tests.
This commit is contained in:
Adam Osewski
2024-10-30 10:05:15 +01:00
committed by GitHub
parent 3d60953477
commit 24d996aae1
29 changed files with 1660 additions and 561 deletions
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32
example/ck_tile/03_gemm/gemm_basic.hpp
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@@ -4,12 +4,10 @@
#pragma once
#include <string>
#include "ck_tile/core.hpp"
#include "ck_tile/host/kernel_launch.hpp"
#include "ck_tile/ops/epilogue.hpp"
#include "ck_tile/ops/gemm.hpp"
#include "ck_tile/host.hpp"
#include <string>
template <typename DataType>
struct GemmBasicTypeConfig;
@@ -20,7 +18,7 @@ struct GemmBasicTypeConfig<ck_tile::half_t>
using ADataType = ck_tile::half_t;
using BDataType = ck_tile::half_t;
using AccDataType = float;
using CDataType = ck_tile::half_t; // type convert
using CDataType = ck_tile::half_t;
// ToDo: Add more bias config to support different categories of GEMM.
};
@@ -58,7 +56,6 @@ struct gemm_basic_args
const void* p_a;
const void* p_b;
void* p_c;
float epsilon;
ck_tile::index_t kbatch;
ck_tile::index_t M;
ck_tile::index_t N;
@@ -68,5 +65,28 @@ struct gemm_basic_args
ck_tile::index_t stride_C;
};
auto create_args(int argc, char* argv[])
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("b", "1", "batch size")
.insert("m", "3840", "m dimension")
.insert("n", "4096", "n dimension")
.insert("k", "2048", "k dimension")
.insert("a_layout", "R", "A tensor data layout - Row by default")
.insert("b_layout", "R", "B tensor data layout - Row by default")
.insert("c_layout", "R", "C tensor data layout - Row by default")
.insert("stride_a", "0", "Tensor A stride")
.insert("stride_b", "0", "Tensor B stride")
.insert("stride_c", "0", "Tensor C stride")
.insert("v", "2", "0. No validation, 1. Validation on CPU, 2. Validation on GPU")
.insert("prec", "fp16", "data type. fp16/bf16/fp8/bf8")
.insert("warmup", "50", "number of iterations before benchmark the kernel")
.insert("repeat", "100", "number of iterations to benchmark the kernel")
.insert("timer", "gpu", "gpu:gpu timer, cpu:cpu timer");
bool result = arg_parser.parse(argc, argv);
return std::make_tuple(result, arg_parser);
}
// host API
float gemm_calc(gemm_basic_args args, const ck_tile::stream_config& s);