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39 lines
1.7 KiB
39 lines
1.7 KiB
# kernel8_batched_gmem.s from https://seb-v.github.io/optimization/update/2025/01/20/Fast-GPU-Matrix-multiplication.html
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# sudo PATH=/opt/homebrew/Cellar/llvm/20.1.6/bin:$PATH AMD_LLVM=0 AMD=1 DEBUG=2 python3 extra/gemm/amd_matmul.py
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import pathlib
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from dataclasses import replace
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from tinygrad import Tensor, Device, Context, GlobalCounters
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from tinygrad.helpers import getenv
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from tinygrad.engine.realize import CompiledRunner, ExecItem, get_program
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N = 4096
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run_count = 5
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if __name__ == "__main__":
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ast = (Tensor.empty(N, N)@Tensor.empty(N, N)).schedule()[-1].ast
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prg = get_program(ast, Device.default.renderer)
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if getenv("ASM") == 1:
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src = (pathlib.Path(__file__).parent / "amd_seb" / "kernel8_batched_gmem.s").read_text()
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prgfast = replace(prg, name="kernel", src=src, global_size=[N//128, N//128, 1], local_size=[128, 1, 1])
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elif getenv("ASM") == -1:
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src = (pathlib.Path(__file__).parent / "amd_seb" / "kernel3_registers.cpp").read_text()
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prgfast = replace(prg, name="kernel3_registers", src=src, global_size=[N//128, N//128, 1], local_size=[256, 1, 1])
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else:
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src = (pathlib.Path(__file__).parent / "amd_seb" / "kernel5_lds_optim.cpp").read_text()
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prgfast = replace(prg, name="kernel5_lds_optim", src=src, global_size=[N//128, N//128, 1], local_size=[128, 1, 1])
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runner = CompiledRunner(prgfast)
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a = Tensor.randn(N, N).realize()
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b = Tensor.randn(N, N).realize()
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c = Tensor.zeros(N, N).contiguous().realize()
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GlobalCounters.reset()
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with Context(DEBUG=2, BEAM=4):
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for _ in range(run_count): tc = (a@b).realize()
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GlobalCounters.reset()
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ei = ExecItem(runner, [a.uop.buffer, b.uop.buffer, c.uop.buffer])
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with Context(DEBUG=2):
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for _ in range(run_count): ei.run(wait=True)
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print(f"custom {(c-tc).square().mean().item()}")
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