284804ac53
Sources: siboehm/SGEMM_CUDA → upstream_ref/sgemm_siboehm/ (25 files) wangzyon/NVIDIA_SGEMM_PRACTICE → upstream_ref/nvidia_sgemm_practice/ (23 files, filled gaps) edtallison/sgemm-cuda → upstream_ref/sgemm_edtallison/ (41 files) All files cat'd one by one from git clone (no --depth). These are the 3 public SGEMM repos that can compile on CUDA 10.2 + CoreX ivcore10. Key files for BI-V100 porting: kernel 10 (warp tiling) — already proven on device with WARPSIZE=64 kernel 11/12 (double buffering) — next optimization target sgemm.cu + runner.cu — complete build+benchmark harness CMakeLists.txt — build system reference
34 lines
958 B
Python
34 lines
958 B
Python
banks_naive = lambda r, c: (r * 32 + c) % 32
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banks_one_extra = lambda r, c: (r * 33 + c) % 32
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ITEMS_PER_WARP = 8
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def printBankConflicts(bank_fun):
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for c in range(1):
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banks = []
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for i in range(32):
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row = (i * ITEMS_PER_WARP) // 16
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col = (i * ITEMS_PER_WARP + c) % 16
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banks.append((i, row, col, bank_fun(row, col)))
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print("Step", c, "\n", "\n".join(["(" + ",".join(str(x) for x in i) + ")" for i in banks]))
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d = {k: 0 for k in range(32)}
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for i in banks:
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d[i[-1]] += 1
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count = 0
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for key, val in d.items():
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if val > 0:
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count += 1
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print(
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f"Bank conflicts (Step {c}): {sorted(d.items(), key=lambda item: item[1], reverse=True)[0][1]}, banks accessed: {count}/32\n"
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)
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print("---NAIVE---")
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printBankConflicts(banks_naive, 32)
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print("\n---EXTRA COL---")
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printBankConflicts(banks_one_extra, 33)
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