38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
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from tinygrad import Tensor, dtypes, Device
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from tinygrad.helpers import getenv, DEBUG
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from tinygrad.codegen.kernel import Kernel, Opt, OptOps
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from tinygrad.engine.realize import CompiledRunner, ExecItem
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from dataclasses import replace
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N = 4096
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if __name__ == "__main__":
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if getenv("GEMV"):
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A, B = Tensor.empty(1, N, dtype=dtypes.float), Tensor.empty(14336, N, dtype=dtypes.float16).T
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else:
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A, B = Tensor.empty(N, N, dtype=dtypes.float16), Tensor.empty(N, N, dtype=dtypes.float16)
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C = A.matmul(B)
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si = C.schedule()[-1]
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ast = si.ast
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k = Kernel(ast, opts=Device[Device.DEFAULT].renderer)
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if getenv("GEMV"):
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opts = [
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Opt(op=OptOps.UNROLL, axis=0, amt=8),
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Opt(op=OptOps.GROUP, axis=0, amt=32),
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]
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else:
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opts = [
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Opt(op=OptOps.TC, axis=0, amt=0),
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Opt(op=OptOps.UPCAST, axis=0, amt=4),
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Opt(op=OptOps.UPCAST, axis=1, amt=8),
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Opt(op=OptOps.LOCAL, axis=0, amt=2),
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Opt(op=OptOps.LOCAL, axis=1, amt=2),
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Opt(op=OptOps.LOCAL, axis=0, amt=2),
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]
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for opt in opts: k.apply_opt(opt)
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prg = k.to_program()
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new_src = prg.src
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# can mod source here
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prg = replace(prg, src=new_src)
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ei = ExecItem(CompiledRunner(prg), [x.ensure_allocated() for x in si.bufs], si.metadata)
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for i in range(5): ei.run(wait=True)
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