Significantly improves the performance of `triton.ops.matmul` in memory-bound settings via the use of many more block configs coupled with a performance model to drive the auto-tuning process.
96 lines
3.1 KiB
C++
96 lines
3.1 KiB
C++
#include "triton/codegen/pass.h"
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#include "triton/codegen/analysis/align.h"
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#include "triton/codegen/analysis/allocation.h"
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#include "triton/codegen/analysis/axes.h"
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#include "triton/codegen/analysis/liveness.h"
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#include "triton/codegen/analysis/swizzle.h"
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#include "triton/codegen/selection/generator.h"
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#include "triton/codegen/transform/coalesce.h"
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#include "triton/codegen/transform/cts.h"
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#include "triton/codegen/transform/dce.h"
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#include "triton/codegen/transform/disassociate.h"
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#include "triton/codegen/transform/membar.h"
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#include "triton/codegen/transform/peephole.h"
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#include "triton/codegen/transform/pipeline.h"
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#include "triton/codegen/transform/prefetch.h"
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#include "triton/ir/function.h"
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#include "triton/ir/module.h"
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#include "triton/ir/print.h"
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#include "llvm/IR/Module.h"
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#include "llvm/IR/LegacyPassManager.h"
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#include "llvm/IR/Verifier.h"
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namespace triton {
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namespace codegen {
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// TODO:
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// There should be a proper pass manager there!
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std::unique_ptr<llvm::Module> add_passes_to_emit_bin(ir::module &ir, llvm::LLVMContext& ctx, codegen::target* target,
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int cc, int num_warps, int num_stages, int& shared_static) {
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// generate llvm code
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std::string name = ir.get_function_list()[0]->get_name();
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std::unique_ptr<llvm::Module> llvm(new llvm::Module(name, ctx));
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// optimizations
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bool cts_use_async = target->as_nvidia() && target->as_nvidia()->sm() >= 80;
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// create passes
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codegen::analysis::align align;
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codegen::analysis::axes axes;
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codegen::transform::cts cts(cts_use_async);
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codegen::transform::pipeline pipeline(cts_use_async, num_stages);
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codegen::transform::disassociate disassociate;
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codegen::analysis::layouts layouts(&axes, &align, num_warps, target);
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codegen::analysis::liveness liveness(&layouts);
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codegen::analysis::swizzle swizzle(&layouts, target);
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codegen::analysis::allocation allocation(&liveness);
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codegen::transform::dce dce;
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codegen::transform::peephole peephole(target, &layouts);
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codegen::transform::coalesce coalesce(&align, &layouts);
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codegen::transform::prefetch prefetch_s(target);
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codegen::transform::membar barriers(&liveness, &layouts, &allocation, &prefetch_s, target);
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codegen::generator isel(&axes, &layouts, &align, &allocation, &swizzle, target, num_warps);
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// run passes
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dce.run(ir);
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peephole.run(ir);
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dce.run(ir);
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pipeline.run(ir);
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dce.run(ir);
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disassociate.run(ir);
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dce.run(ir);
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align.run(ir);
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axes.run(ir);
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layouts.run(ir);
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peephole.run(ir);
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dce.run(ir);
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if (target->is_gpu())
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cts.run(ir);
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align.run(ir);
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axes.run(ir);
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layouts.run(ir);
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coalesce.run(ir);
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dce.run(ir);
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align.run(ir);
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dce.run(ir);
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if (target->is_gpu())
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cts.run(ir);
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dce.run(ir);
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align.run(ir);
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axes.run(ir);
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layouts.run(ir);
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peephole.run(ir);
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dce.run(ir);
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align.run(ir);
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axes.run(ir);
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layouts.run(ir);
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swizzle.run(ir);
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liveness.run(ir);
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allocation.run(ir);
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prefetch_s.run(ir);
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barriers.run(ir);
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// ir.print(std::cout);
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isel.visit(ir, *llvm);
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shared_static = allocation.allocated_size();
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return llvm;
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}
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} // namespace codegen
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} // namespace triton
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