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78 lines
3.6 KiB
Python
78 lines
3.6 KiB
Python
import unittest
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import functools
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from tinygrad import Tensor, Device, dtypes
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from tinygrad.uop.ops import UOp, Ops, KernelInfo
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from tinygrad.renderer import Estimates
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from tinygrad.runtime.support.compiler_amd import HIPCompiler
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from extra.assembly.amd.autogen.rdna3.ins import *
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from extra.assembly.amd.dsl import s, v, Inst
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def assemble_insts(insts:list[Inst], name:str, arch:str, kernarg_size:int=8) -> tuple[UOp, UOp]:
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kd = {"kernarg_size":kernarg_size, "user_sgpr_kernarg_segment_ptr":1, "next_free_vgpr":8, "next_free_sgpr":8, "wavefront_size32":1}
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disasm = "\n".join([inst.disasm() for inst in insts])
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hsasrc = f".text\n.globl {name}\n.p2align 8\n.type fn_name,@function\n{name}:\n{disasm}\ns_code_end\n"
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hsasrc += f".rodata\n.p2align 6\n.amdhsa_kernel {name}\n"+"\n".join([f".amdhsa_{k} {v}" for k,v in kd.items()])+"\n.end_amdhsa_kernel"
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binary = HIPCompiler(arch).compile(hsasrc)
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return UOp(Ops.SOURCE, arg=disasm), UOp(Ops.BINARY, arg=binary)
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def custom_add_one(A:UOp, arch:str) -> UOp:
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A = A.flatten()
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assert dtypes.is_float(A.dtype.base), f"buffer dtype must be float32, got {A.dtype}"
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threads = UOp.special(A.size, "lidx0")
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insts = [
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s_load_b64(s[0:1], s[0:1], soffset=NULL),
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s_waitcnt(lgkmcnt=0),
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v_lshlrev_b32_e32(v[0], 2, v[0]), # element offset
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global_load_b32(v[1], v[0], saddr=s[0:1]),
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s_waitcnt(vmcnt=0),
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v_mov_b32_e32(v[2], 1.0),
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v_add_f32_e32(v[1], v[1], v[2]),
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global_store_b32(addr=v[0], data=v[1], saddr=s[0:1]),
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s_endpgm(),
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]
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sink = UOp.sink(A.base, threads, arg=KernelInfo(name:=f"custom_add_one_{A.size}", estimates=Estimates(ops=A.size, mem=A.size*4*2)))
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return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg="AMD"), UOp(Ops.LINEAR, src=(*sink.src, sink)), *assemble_insts(insts, name, arch)))
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def custom_add_var(A:UOp, B:UOp, arch:str) -> UOp:
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A,B = A.flatten(), B.flatten()
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assert A.dtype.base == dtypes.uint32, f"buffer dtype must be uint32, got {A.dtype}"
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threads = UOp.special(A.size, "lidx0")
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var = UOp.variable("var", 0, 10)
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insts = [
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s_load_b128(s[4:7], s[0:1]),
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s_load_b32(s[8], s[0:1], offset=0x10), # all threads load the same variable
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s_waitcnt(lgkmcnt=0),
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v_lshlrev_b32_e32(v[0], 2, v[0]), # element offset, different per thread
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global_load_b32(v[1], v[0], saddr=s[6:7]),
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s_waitcnt(vmcnt=0),
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v_add_nc_u32_e32(v[1], s[8], v[1]),
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global_store_b32(addr=v[0], data=v[1], saddr=s[4:5]),
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s_endpgm(),
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]
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sink = UOp.sink(A.base, B.base, var, threads, arg=KernelInfo(name:=f"custom_add_one_{A.size}"))
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return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg="AMD"), UOp(Ops.LINEAR, src=(*sink.src, sink)),
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*assemble_insts(insts, name, arch, kernarg_size=16)))
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class TestCustomKernel(unittest.TestCase):
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def test_simple(self):
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a = Tensor.full((16, 16), 1.).contiguous().realize()
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a = Tensor.custom_kernel(a, fxn=functools.partial(custom_add_one, arch=Device[Device.DEFAULT].renderer.arch))[0]
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ei = a.schedule()[-1].lower()
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self.assertEqual(ei.prg.estimates.ops, a.numel())
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self.assertEqual(ei.prg.estimates.mem, a.nbytes()*2)
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ei.run()
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self.assertTrue((a.numpy() == 2.).all())
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def test_variable(self):
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b = Tensor.full((16, 16), 1, dtype=dtypes.uint32).contiguous().realize()
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a = Tensor.zeros_like(b).contiguous().realize()
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a = Tensor.custom_kernel(a, b, fxn=functools.partial(custom_add_var, arch=Device[Device.DEFAULT].renderer.arch))[0]
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ei = a.schedule()[-1].lower()
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for i in range(4):
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ei.run({"var":i})
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self.assertTrue((a.numpy() == 1+i).all())
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if __name__ == "__main__":
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unittest.main()
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