Files
composable_kernel/codegen/driver/main.cpp
arai713 3e9711f0cb CK Instance Gen (#1145)
* Format

* Format

* Format

* Remove const

* Use the right template

* Format

* Format

* add row/col instances

* Add missing file

* fixed

* fixing block to etile error

* Format

* Updates

* Format

* fixed rrr layout

* generating a sample JSON file: currently contains includes, prologue/epilogue and instances

* version where the json is passed into the instances to generate a key

* updated run function to just launch kernel

* updated run function: only contains kernel object, json file is updated but still needs to be cleaned up, added front-end API to parse JSON into character buffer

* adding in testing files

* cleaned up comments, still need to work on including header files

* removed unneeded files

* removed/commented out JSON implementation

* added fusion(prologue/epilogue) into instance generation

* working on instance selection

* added instance selection, need to fix instance validation

* removed block2etile map validity check for testing purposes

* test running: failing due to incorrect files/input

* all grid descs/ptrs completed, but device file not found

* Update test and embed modules

* Restore older version

* added convolution operation, written test, debugging generated code for compilation

* attempting to include CK in host directory: _Float16 error

* CK header file issues

* slight fix

* don't crash when hip can't report total memory

* dump generated code to a file

* changing sizes

* creating tensor descriptors using CK methods: set up grid desc manually, also trying to set up an argument pointer - this needs to be fixed

* some fixes to call the device code

* separating test files for conv and gemm

* completed arg ptr, now have linking errors

* clang format fix

* resolved linker issues in conv test

* remove dependency on libutility from ck

* resolved num dim error

* properly passing arg ptr, errors with passing typenames: redefinition/redeclaration

* undo the commenting of device function

* hand created kernel code to find rtc issues

* dump the full src to file

* resolved redeclaration errors, cleaned up errors for Amber's kernel code

* debugging purposes: redeclaration error

* config files

* resolved errors for NumTensor and redeclaration, formatted version.h

* resolved most errors in manually added kernel and my own. error with calling kernel object: overloaded function type

* WIP: close to getting kernel compiled

* WIP: fixing rtc errors

* fixed sequence errors, formatting, still one error with run fcn

* yay: kernel compiles and runs

* updated templated/generated version to run and compile

* minor fixes

* working generated example, resolved memory access error due to padding

* adding in reference kernel, validation failing against reference

* debugging: printing kernel argsz

* reduced error in results

* debugged reference kernel and output errors, added to generated version, currently debugging prologue function issues

* working validation (using reference convolution) with prologue function for both hard-coded and generated version

* WIP: create an alt version that creates Argument on the device

* wip: added new duplicate files, fixed fusion templating errors from working example, setting up kernel arguments

* wip: making necessary methods device code

* added grid descs, working on grid pointers, errors with stl numerics

* wip: updating kernel args - issue, replacing some std functions

* replaced std::accumulate call with temp hardcoded version

* wip: args causing memory issue

* Construct Argument object inside the kernel and use it to call convolution device function. Code runs and verification passes

* adding object file dump

* temporary hardcoding of grid size, can remove device op inst + arg ptr

* minor fix for grid size

* added modified example where arg ptr is created on the device for generated version as well

* removed device op instance and arg ptr from modified examples

* moving device op file for testing purposes and to properly build CK

* commenting out print-outs

* adjust compiler args to produce a valid ELF file

* temporary removal of validation

* reverting compiler args back for working example

* retrieve necessary arguments from generated template parameters in correct format

* calculating grid size on host-side, still need to clean up process, pass parameters to host functions properly

* scaled up factory functions/wrapper structs to implement host-side launch parameter calculations using CK host side functions - in hard-coded example

* temporary change to generate ELF format binary object file

* removed unecessary code, added comments

* formatting fix

* cleaned up code, added new tests, restructured library: move helper into CK

* refactored launch parameter calculation to be more concise

* renamed files and variables for more clarity/uniformity

* more code cleaning, removed debug statements

* moved majority of my files into codegen directory, running properly

* updated Embed.cmake(string_view) in codegen directory

* updated host directory to match Embed.cmake as well

* added old tests in

* updated instance generation methods to be more concise

* removed layout from launch parameter calculation

* working test

* fixed issue with verification, all instances working

* updated verification in other tests

* removed duplicate matrix padder file, removed code dumps

* removed old hard-coded tests

* removed old host directory, all files in codegen directory now

* fixed copyright in files

* commenting out validation

* renamed files

* made changes for review: fixed copyright, renamed files for clarity, removed comments, refactored code

* updated headers

* removing duplicate file for fwd conv to gemm, merging with original file

* fix building codegen with clang++ directly

* resolving build error from conv_fwd_to_gemm

* fix for previous error

* renaming tests

* created common test file

* cleaned up code, added comments

* renamed device op

* fixed typos in comments

* removed extra space

* code cleanup: resolving Amber's comments

* removed wrapper struct for matrix padder, fixed template

* cleaned up if statements for better readability

---------

Co-authored-by: Paul <pfultz2@yahoo.com>
Co-authored-by: Jing Zhang <jizha@amd.com>
Co-authored-by: M. Amber Hassaan <amber_474@yahoo.com>
Co-authored-by: illsilin <Illia.Silin@amd.com>
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
2024-06-25 16:37:35 -05:00

106 lines
3.4 KiB
C++

#include <functional>
#include <iostream>
#include <string>
#include <unordered_map>
#include <vector>
#include "ck/host/device_gemm_multiple_d/operation.hpp"
#include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_op.hpp"
#include "ck/host/stringutils.hpp"
using ck::host::Transform;
struct Emitters
{
// retrieve the hard-coded instances provided, template them, and then store them in a map
std::unordered_map<std::string, std::function<std::vector<std::string>()>> m;
template <class T>
void Register(const std::string& name, const std::string& prologue, const std::string& epilogue)
{
m[name] = [&] {
auto configs = T::CreateOperations(prologue, epilogue);
return Transform(configs, [](const auto& ops) { return ToTuple(ops); });
};
}
// takes in an operation instance and uses it to substitute the correct values into the template
template <class T>
static std::string ToTuple(const T& ops)
{
auto templates = Transform(
ops, [](const auto& op) { return " " + op.ToSolution().ToTemplateString(); });
return "std::tuple<\n" + ck::host::JoinStrings(templates, ",\n") + ">";
}
// Join together all the strings in the map
std::string Emit(const std::string& name) { return ck::host::JoinStrings(m.at(name)(), "\n"); }
std::vector<std::string> List() const
{
return Transform(m, [](auto&& p) { return p.first; });
}
};
int main(int argc, const char* argv[])
{
std::string prog = argv[0];
std::vector<std::string> args(argv + 1, argv + argc);
// Specify problem type and problem size
ck::host::device_gemm_multiple_d::Problem prob;
prob.M = 1024;
prob.N = 1024;
prob.K = 1024;
// user provided fusion
std::string prologue = "";
std::string epilogue = R"(
struct Epilogue
{
__host__ __device__ Epilogue(float alpha, float beta) : alpha_(alpha), beta_(beta){};
template <typename E, typename D>
__host__ __device__ constexpr void operator()(E& e, const D& d) const;
template <>
__host__ __device__ constexpr void operator()<ck::half_t, ck::half_t>(ck::half_t& e,
const ck::half_t& d) const
{
e = ck::type_convert<ck::half_t>(alpha_ * e + beta_ * ck::type_convert<float>(d));
}
float alpha_;
float beta_;
};)";
// Load in operations into the Register
Emitters e;
e.Register<ck::host::device_gemm_multiple_d::Operation_Xdl_CShuffle>(
"DeviceGemmMultipleD_Xdl_CShuffle", prologue, epilogue);
if(args.empty() or std::any_of(args.begin(), args.end(), [](auto arg) {
return arg == "-h" or arg == "--help";
}))
{
std::cout << "USAGE:" << std::endl;
std::cout << " " << prog << " [TEMPLATE]" << std::endl;
std::cout << std::endl;
std::cout << "FLAGS:" << std::endl;
std::cout << " -h, --help Show help" << std::endl;
std::cout << std::endl;
std::cout << "TEMPLATES:" << std::endl;
for(auto x : e.List())
std::cout << " " << x << std::endl;
std::cout << std::endl;
return 0;
}
// print out all the instances for the operation that was chosen at the command line
for(auto name : args)
std::cout << e.Emit(name) << std::endl;
return 0;
}