From a8b63fa3621b97fd88c98fd141f3bdd7960ed3c1 Mon Sep 17 00:00:00 2001
From: ViperEkura <3081035982@qq.com>
Date: Wed, 26 Aug 2026 07:22:07 +0800
Subject: [PATCH] chore: untrack fp8 sweep tool

- csrc/tests/fp8_sweep.cu is a local measurement tool, not shipped code; git rm --cached keeps the working-tree copy
- the file shows up untracked in git status (allowlist gitignore is untouched by design); never stage it
---
 csrc/tests/fp8_sweep.cu | 139 ----------------------------------------
 1 file changed, 139 deletions(-)
 delete mode 100644 csrc/tests/fp8_sweep.cu

diff --git a/csrc/tests/fp8_sweep.cu b/csrc/tests/fp8_sweep.cu
deleted file mode 100644
index 1424198..0000000
--- a/csrc/tests/fp8_sweep.cu
+++ /dev/null
@@ -1,139 +0,0 @@
-/*
-FP8 GEMM config sweep — pure C, no torch. Times (BM, BN, WarpM, WarpN, kK,
-Stages, raster) tile configurations across the production square shapes so
-the launcher's shape dispatch table is grounded in measurements.
-
-    nvcc -I csrc -arch=sm_89 -std=c++17 -O3 --use_fast_math \
-        csrc/tests/fp8_sweep.cu -o /tmp/fp8_sweep && /tmp/fp8_sweep [iters] [sizes...]
-*/
-
-#include "test_utils.cuh"
-
-#include <cuda_fp8.h>
-#include <cstdio>
-#include <cstdlib>
-#include <cuda_runtime.h>
-#include <vector>
-
-#include "../kernels/fp8/gemm.cuh"
-
-using namespace astrai::fp8;
-
-namespace {
-
-struct BenchData {
-    __nv_fp8_e4m3 *da, *db;
-    __nv_bfloat16* dout;
-    float* dscale;
-};
-
-template <int BM, int BN, int WM, int WN, int kK, int Stages, bool GroupRaster,
-          bool LeanRing = false>
-float bench_config(BenchData& d, int m, int n, int k, int iters) {
-    FP8Params p = {};
-    p.a_ptr = d.da;
-    p.b_ptr = d.db;
-    p.out_ptr = d.dout;
-    p.scale = d.dscale;
-    p.m = m;
-    p.n = n;
-    p.k = k;
-    p.a_ld = k;
-    p.b_ld = k;
-
-    using Traits = Fp8GemmTraits<FP8Format::E4M3, BM, BN, kK, Stages, WM, WN>;
-    using Smem = Fp8GemmSmem<Traits, RowMajor, ColMajor, false, LeanRing>;
-    dim3 grid((n + BN - 1) / BN, (m + BM - 1) / BM);
-    dim3 block(Traits::kCtaThreads);
-    const int smem = Smem::kBytes;
-
-    auto launch = [&] {
-        launch_with_smem<fp8_gemm_kernel<Traits, RowMajor, ColMajor, GroupRaster,
-                                         false, LeanRing>>(
-            smem, grid, block, 0, p);
-    };
-    launch();
-    CUDA_CHECK(cudaGetLastError());
-    CUDA_CHECK(cudaDeviceSynchronize());
-
-    cudaEvent_t start, end;
-    cudaEventCreate(&start);
-    cudaEventCreate(&end);
-    for (int i = 0; i < 3; ++i) launch();
-    cudaDeviceSynchronize();
-    cudaEventRecord(start);
-    for (int i = 0; i < iters; ++i) launch();
-    cudaEventRecord(end);
-    cudaEventSynchronize(end);
-    float ms = 0;
-    cudaEventElapsedTime(&ms, start, end);
-    cudaEventDestroy(start);
-    cudaEventDestroy(end);
-    return ms / iters;
-}
-
-// One named config column.
-struct Col {
-    const char* name;
-    float (*fn)(BenchData&, int, int, int, int);
-};
-
-template <int BM, int BN, int WM, int WN, int kK, int Stages, bool R,
-          bool Lean = false>
-float run(BenchData& d, int m, int n, int k, int iters) {
-    return bench_config<BM, BN, WM, WN, kK, Stages, R, Lean>(d, m, n, k, iters);
-}
-
-}  // namespace
-
-int main(int argc, char** argv) {
-    const int iters = argc > 1 ? atoi(argv[1]) : 50;
-    int sizes[] = {512, 1024, 2048, 4096, 8192, 0, 0, 0};
-    for (int i = 2; i < argc && i < 10; ++i) sizes[i - 2] = atoi(argv[i]);
-
-    Col cols[] = {
-        {"128ring3", &run<128, 128, 64, 32, 64, 2, true>},
-        {"128ring3s3", &run<128, 128, 64, 32, 64, 3, true>},
-        {"128lean", &run<128, 128, 64, 32, 64, 2, true, true>},
-        {"64r5s4", &run<64, 64, 32, 32, 64, 4, false>},
-        {"64lean4", &run<64, 64, 32, 32, 64, 4, false, true>},
-        {"64lean5", &run<64, 64, 32, 32, 64, 5, false, true>},
-        {"64lean3", &run<64, 64, 32, 32, 64, 3, false, true>},
-    };
-    const int ncols = sizeof(cols) / sizeof(cols[0]);
-
-    printf("%6s |", "shape");
-    for (auto& c : cols) printf(" %11s |", c.name);
-    printf("\n");
-
-    for (int s : sizes) {
-        if (s <= 0) continue;
-        const int m = s, n = s, k = s;
-        BenchData d;
-        std::vector<__nv_fp8_e4m3> a((size_t)m * k), b((size_t)n * k);
-        for (auto& v : a) v = __nv_fp8_e4m3(randf());
-        for (auto& v : b) v = __nv_fp8_e4m3(randf());
-        cudaMalloc(&d.da, a.size());
-        cudaMalloc(&d.db, b.size());
-        cudaMalloc(&d.dout, (size_t)m * n * 2);
-        cudaMalloc(&d.dscale, 4);
-        const float one = 1.0f;
-        cudaMemcpy(d.dscale, &one, 4, cudaMemcpyHostToDevice);
-        cudaMemcpy(d.da, a.data(), a.size(), cudaMemcpyHostToDevice);
-        cudaMemcpy(d.db, b.data(), b.size(), cudaMemcpyHostToDevice);
-
-        const double flops = 2.0 * m * n * k;
-        printf("%6d |", s);
-        for (auto& c : cols) {
-            const float ms = c.fn(d, m, n, k, iters);
-            printf(" %5.2fus %4.1fT |", ms * 1000,
-                   flops / (ms * 1e-3) / 1e12);
-        }
-        printf("\n");
-        cudaFree(d.da);
-        cudaFree(d.db);
-        cudaFree(d.dout);
-        cudaFree(d.dscale);
-    }
-    return 0;
-}