/* hotpath kernel-lane demonstration (SPEC §13). * * A single-precision matrix multiply in two implementations that are * mathematically identical but numerically different because they sum the * inner products in a different ORDER: * * matmul_ref — naive i,j,k with a single sequential accumulator. The * reference oracle. * matmul_opt — eight independent accumulators over the k-reduction, * tree-combined at the end. This breaks the float-add * dependency chain (hiding ~4-cycle add latency behind * instruction-level parallelism, so it is faster) AND sums * the inner product in a different ORDER, so results differ * in the last few ULPs — bit-identical is impossible by * construction. * * This is the crux of the kernel lane: a real optimization here CANNOT be * gated by byte-identical golden replay (the low bits differ by design); * it needs a floating-point *tolerance* gate that accepts last-ULP * reordering while still catching a genuine wrong result. The reference * implementation is the oracle; the candidate is differential-tested * against it within a declared tolerance. On a GPU this same shape holds * (a Triton/CUDA kernel vs a reference kernel) — only the timer and the * hardware change. * * kernel emit ref|opt # print the result matrix * kernel check # in-process differential test * kernel run ref|opt # one matmul, no output (for A/B) * kernel bench ref|opt # time one implementation */ #include #include #include #include #include #define BS 64 /* block size */ /* Deterministic f32 fill — xorshift, identical on every machine. */ static void fill(float *m, long n, unsigned seed) { unsigned s = seed ? seed : 1; for (long i = 0; i < n * n; i++) { s ^= s << 13; s ^= s >> 17; s ^= s << 5; /* in [-1, 1) */ m[i] = (float)((double)s / 2147483648.0 - 1.0); } } static void matmul_ref(const float *A, const float *B, float *C, long n) { for (long i = 0; i < n; i++) for (long j = 0; j < n; j++) { float acc = 0.0f; for (long k = 0; k < n; k++) acc += A[i * n + k] * B[k * n + j]; C[i * n + j] = acc; } } static void matmul_opt(const float *A, const float *B, float *C, long n) { /* Transpose B so the inner reduction walks BT[j] contiguously instead * of striding B by n (the cache win), and use eight independent * accumulators (the ILP win, which also REORDERS the reduction). Both * levers together are a robust speedup AND make bit-identical output * impossible — the kernel lane in one function. */ float *BT = malloc((size_t)n * n * sizeof(float)); if (!BT) { matmul_ref(A, B, C, n); return; } for (long i = 0; i < n; i++) for (long j = 0; j < n; j++) BT[j * n + i] = B[i * n + j]; for (long i = 0; i < n; i++) { const float *a = &A[i * n]; for (long j = 0; j < n; j++) { const float *b = &BT[j * n]; float acc[8] = {0, 0, 0, 0, 0, 0, 0, 0}; long k = 0; for (; k + 8 <= n; k += 8) for (int r = 0; r < 8; r++) acc[r] += a[k + r] * b[k + r]; float s = ((acc[0] + acc[1]) + (acc[2] + acc[3])) + ((acc[4] + acc[5]) + (acc[6] + acc[7])); for (; k < n; k++) s += a[k] * b[k]; C[i * n + j] = s; } } free(BT); } static double now_s(void) { struct timespec t; clock_gettime(CLOCK_MONOTONIC, &t); return (double)t.tv_sec + (double)t.tv_nsec / 1e9; } int main(int argc, char **argv) { if (argc < 3) { fprintf(stderr, "usage: %s emit ref|opt | check | run ref|opt | bench ref|opt \n", argv[0]); return 2; } long n = atol(argv[1]); if (n < 1) n = 512; const char *mode = argv[2]; float *A = malloc((size_t)n * n * sizeof(float)); float *B = malloc((size_t)n * n * sizeof(float)); float *C = malloc((size_t)n * n * sizeof(float)); float *R = malloc((size_t)n * n * sizeof(float)); if (!A || !B || !C || !R) return 2; fill(A, n, 0x9E3779B1u); fill(B, n, 0x85EBCA77u); if (strcmp(mode, "emit") == 0) { int blocked = (argc > 3 && strcmp(argv[3], "opt") == 0); if (blocked) matmul_opt(A, B, C, n); else matmul_ref(A, B, C, n); for (long i = 0; i < n * n; i++) printf("%.9g\n", C[i]); return 0; } if (strcmp(mode, "check") == 0) { /* Combined abs+rel tolerance — the standard for FP comparison, and * what the diff-test policy uses. Rel-only is wrong here: result * elements near zero (catastrophic cancellation) have meaningless * relative error, so an abs floor is required. */ double abs_tol = argc > 3 ? atof(argv[3]) : 1e-4; double rel_tol = argc > 4 ? atof(argv[4]) : 1e-3; matmul_ref(A, B, R, n); matmul_opt(A, B, C, n); double max_abs = 0.0, max_rel = 0.0, worst_excess = -1e30; for (long i = 0; i < n * n; i++) { double d = fabs((double)C[i] - (double)R[i]); double r = d / (fabs((double)R[i]) + 1e-30); double tol = abs_tol + rel_tol * fabs((double)R[i]); if (d > max_abs) max_abs = d; if (r > max_rel) max_rel = r; if (d - tol > worst_excess) worst_excess = d - tol; } int pass = worst_excess <= 0.0; printf("kernel differential test (opt vs reference):\n"); printf(" max_abs_err = %.3e\n", max_abs); printf(" max_rel_err = %.3e (dominated by near-zero elements; see abs floor)\n", max_rel); printf(" tolerance = abs %.3e + rel %.3e * |ref|\n", abs_tol, rel_tol); printf(" byte_identical = NO (accumulation reordered by design)\n"); printf(" within_tolerance = %s\n", pass ? "YES" : "NO"); printf(" verdict = %s\n", pass ? "EQUIVALENT" : "DIVERGENT"); return pass ? 0 : 1; } /* One matmul, no output — for bench-runner's interleaved A/B (external * wall-clock timing with a bootstrap CI, like every other target). */ if (strcmp(mode, "run") == 0) { if (strcmp(argv[3], "opt") == 0) matmul_opt(A, B, C, n); else matmul_ref(A, B, C, n); /* touch C so the compiler cannot elide the work */ volatile float sink = C[n * n - 1]; (void)sink; return 0; } if (strcmp(mode, "bench") == 0) { int use_opt = strcmp(argv[3], "opt") == 0; long reps = argc > 4 ? atol(argv[4]) : 5; if (use_opt) matmul_opt(A, B, C, n); else matmul_ref(A, B, C, n); double best = 1e30; for (long r = 0; r < reps; r++) { double t0 = now_s(); if (use_opt) matmul_opt(A, B, C, n); else matmul_ref(A, B, C, n); double dt = now_s() - t0; if (dt < best) best = dt; } printf("%.6f\n", best); return 0; } fprintf(stderr, "unknown mode: %s\n", mode); return 2; }