[Benchmark] Add H800 SXM Benchmark results

benchmark/matmul_fp8/README.md

@@ -0,0 +1,36 @@
+# FP8 Matmul Benchmark (8192×8192)
+
+This document records the throughput achieved by `benchmark_matmul.py` when multiplying FP8 matrices sized `M = N = 8192` across different `K` dimensions. Each measurement relies on the default autotuning search space bundled with the benchmark.
+
+## Environment
+
+- Repository commit: `6b1faf71faf18c564f5f77e0f5c1671cd91dfbc3`
+- GPUs: `NVIDIA H800 SXM` on driver `560.35.05`
+
+## How to Reproduce
+
+```bash
+cd benchmark/matmul_fp8
+python - <<'PY'
+from benchmark_matmul import matmul
+
+M = 8192
+N = 8192
+for K in [256, 512, 1024, 2048, 4096, 8192, 16384]:
+    res = matmul(M, N, K, False)
+    tflops = 2 * M * N * K / res.latency * 1e-12
+    print(f"K={K:5d}  latency={res.latency:.6f}s  TFlops={tflops:.3f}")
+PY
+```
+
+## Results
+
+| K     | Latency (s) | Throughput (TFLOPs) |
+|-------|-------------|---------------------|
+|   256 | 0.091488    | 376                 |
+|   512 | 0.110496    | 622                 |
+|  1024 | 0.148256    | 927                 |
+|  2048 | 0.234080    | 1174                |
+|  4096 | 0.398944    | 1378                |
+|  8192 | 0.752416    | 1461                |
+| 16384 | 1.443808    | 1523                |

benchmark/matmul_fp8/benchmark_matmul.py

@@ -239,11 +239,8 @@ def main(
     best_result = matmul(M, N, K, with_roller)
     best_latency = best_result.latency
     best_config = best_result.config
-    ref_latency = best_result.ref_latency
 
     # Print out the benchmark results
     print(f"Best latency (s): {best_latency}")
     print(f"Best TFlops: {total_flops / best_latency * 1e-9:.3f}")
     print(f"Best config: {best_config}")
-
-    print(f"Reference TFlops: {total_flops / ref_latency * 1e-9:.3f}")