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43 lines
1.8 KiB
43 lines
1.8 KiB
#!/usr/bin/env python3
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import numpy as np
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from tinygrad.runtime.ops_gpu import CLProgram, CLCompiler
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from tinygrad import Device, dtypes
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from tinygrad.device import Buffer
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from hexdump import hexdump
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# https://github.com/intel/intel-graphics-compiler/blob/master/documentation/visa/instructions/DPAS.md
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# https://registry.khronos.org/OpenCL/extensions/intel/cl_intel_subgroups.html
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# https://registry.khronos.org/OpenCL/extensions/intel/cl_intel_subgroup_matrix_multiply_accumulate.html
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# https://registry.khronos.org/OpenCL/extensions/intel/cl_intel_subgroup_split_matrix_multiply_accumulate.html
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# https://hc34.hotchips.org/assets/program/conference/day1/GPU%20HPC/Intel_s%20Ponte%20Vecchio%20GPU%20-%20Architecture%20Systems%20and%20Software%20FINAL.pdf
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device = Device["GPU"]
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# NOTE: only the subgroup type 8 ones work
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prog = CLProgram(device, "test", CLCompiler(device, "test").compile(f"""
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__attribute__((intel_reqd_sub_group_size(8)))
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__kernel void test(__global float* data0, const __global int* data1, const __global int8* data2) {{
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int lidx0 = get_local_id(0);
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int a = data1[lidx0];
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int8 b = data2[lidx0];
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float out = intel_sub_group_f16_f16_matrix_mad_k16(a, b, 0.0f);
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data0[lidx0] = out;
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}}
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"""))
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#with open("/tmp/test.elf", "wb") as f: f.write(prog.lib)
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a = Buffer("GPU", 8, dtypes.float32).allocate()
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b = Buffer("GPU", 0x10, dtypes.float16).allocate()
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c = Buffer("GPU", 8*0x10, dtypes.float16).allocate()
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row = np.array([1,2,3,4,5,6,7,8,1,2,3,4,5,6,7,8], np.float16)
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mat = np.random.random((8, 0x10)).astype(np.float16)
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b.copyin(row.data)
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c.copyin(mat.data)
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ret = prog(a._buf, b._buf, c._buf, global_size=[1,1,1], local_size=[8,1,1], wait=True)
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print(ret)
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out = np.frombuffer(a.as_buffer(), np.float32)
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real = row.astype(np.float32)@mat.T.astype(np.float32)
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print("out:", out)
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print("real", real)
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