/** * TMEM Layout D for PV MMA N=64: zero TMEM before PV, then dump. * This tells us exactly which columns the PV MMA writes to. */ #include #include #include #include #include "dsv4/kernels/attention/fmha_common.cuh" #include "dsv4/kernels/attention/fmha_umma_desc.cuh" using namespace dsv4::kernels::attention; static bf16_t f32_to_bf16_host(float f) { uint32_t u; memcpy(&u,&f,4); return (uint16_t)(u>>16); } static float bf16_to_f32_host(bf16_t h) { uint32_t u=(uint32_t)h<<16; float f; memcpy(&f,&u,4); return f; } constexpr int HD = 64, SK = 128, BLOCK_MN = 128; constexpr int LOCAL_MMA_K = 16; constexpr int TILE_SZ = BLOCK_MN * LOCAL_MMA_K; constexpr int V_TILE_SZ = (HD / 8) * 2 * 64; __global__ void __launch_bounds__(128) test_tmem_zero_before_pv(const bf16_t* q, const bf16_t* k, const bf16_t* v, float* tmem_dump, float scale) { const int tid = threadIdx.x, wid = tid / 32, lane = tid % 32; extern __shared__ char sbuf[]; uint32_t* sTmemBase = (uint32_t*)sbuf; bf16_t* sQ0 = (bf16_t*)(((uintptr_t)(sbuf + 4) + 15) & ~(uintptr_t)15); bf16_t* sK0 = sQ0 + 4 * TILE_SZ; bf16_t* sPk = (bf16_t*)(((uintptr_t)(sK0 + 4 * TILE_SZ) + 127) & ~(uintptr_t)127); bf16_t* sV = (bf16_t*)(((uintptr_t)(sPk + TILE_SZ) + 127) & ~(uintptr_t)127); float* s_p_vals = (float*)(sV + 8 * V_TILE_SZ); for (int kt = 0; kt < 4; kt++) { bf16_t* sq = sQ0 + kt * TILE_SZ; for (int i = tid; i < TILE_SZ; i += 128) sq[i] = 0; for (int d = tid; d < LOCAL_MMA_K; d += 128) { int ck = d / 8, lc = d % 8; sq[ck * 16 * 64 + lc] = q[kt * LOCAL_MMA_K + d]; } } for (int kt = 0; kt < 4; kt++) { bf16_t* sk = sK0 + kt * TILE_SZ; for (int i = tid; i < TILE_SZ; i += 128) sk[i] = 0; for (int r = 0; r < SK; r++) { for (int d = tid; d < LOCAL_MMA_K; d += 128) { int ck = d / 8, lc = d % 8; int tmn = r / 8, lr = r % 8; sk[ck * 16 * 64 + tmn * 64 + lr * 8 + lc] = k[r * HD + kt * LOCAL_MMA_K + d]; } } } for (int kt = 0; kt < 8; kt++) { bf16_t* sv = sV + kt * V_TILE_SZ; for (int i = tid; i < V_TILE_SZ; i += 128) sv[i] = 0; for (int d = tid; d < HD; d += 128) { for (int lr = 0; lr < LOCAL_MMA_K; lr++) { int r = kt * LOCAL_MMA_K + lr; int g_mn = d / 8, g_k = lr / 8; int llr = d % 8, lc = lr % 8; sv[g_k * 8 * 64 + g_mn * 64 + llr * 8 + lc] = v[d * SK + r]; } } } __syncthreads(); if (wid == 1) tmem_alloc(__cvta_generic_to_shared(sTmemBase), 128); __syncthreads(); uint32_t tb = *sTmemBase; // QK GEMM { uint32_t idesc = make_idesc(BLOCK_MN, BLOCK_MN); for (int kt = 0; kt < 4; kt++) { bf16_t* sq = sQ0 + kt * TILE_SZ; bf16_t* sk = sK0 + kt * TILE_SZ; uint64_t dq = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sq), BLOCK_MN); uint64_t dk = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sk), BLOCK_MN); if (tid == 0) umma_ss_f16(tb, dq, dk, idesc, kt > 0); asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory"); __syncthreads(); } } // Softmax if (wid == 0) { float s_vals[SK], row_max = -INFINITY; for (int n = 0; n < SK / 8; n++) { float tmp[8]; asm volatile("tcgen05.ld.sync.aligned.32x32b.x8.b32 {%0,%1,%2,%3,%4,%5,%6,%7},[%8];" : "=f"(tmp[0]),"=f"(tmp[1]),"=f"(tmp[2]),"=f"(tmp[3]), "=f"(tmp[4]),"=f"(tmp[5]),"=f"(tmp[6]),"=f"(tmp[7]) : "r"(tb + n*8)); asm volatile("tcgen05.wait::ld.sync.aligned;"); if (lane == 0) for (int c=0;c<8;c++) { s_vals[n*8+c] = tmp[c] * scale; row_max = fmaxf(row_max, tmp[c] * scale); } } row_max = wmax(row_max); float row_sum = 0.0f; if (lane == 0) for (int j=0;j 0); asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory"); __syncthreads(); } } // ===== Dump ALL 128 TMEM columns (lane 0 only) ===== if (wid == 0) { for (int n = 0; n < 16; n++) { float tmp[8]; asm volatile("tcgen05.ld.sync.aligned.32x32b.x8.b32 {%0,%1,%2,%3,%4,%5,%6,%7},[%8];" : "=f"(tmp[0]),"=f"(tmp[1]),"=f"(tmp[2]),"=f"(tmp[3]), "=f"(tmp[4]),"=f"(tmp[5]),"=f"(tmp[6]),"=f"(tmp[7]) : "r"(tb + n*8)); asm volatile("tcgen05.wait::ld.sync.aligned;"); for (int c = 0; c < 8; c++) { int col = n * 8 + c; tmem_dump[col] = tmp[c]; // lane 0's value for this column } } } __syncthreads(); if (wid == 0) tmem_dealloc(tb, 128); } int main() { printf("=== TMEM dump after zeroing + PV MMA N=64 ===\n"); const float SCALE = 1.0f / sqrtf((float)HD); bf16_t* h_q = (bf16_t*)malloc(HD*sizeof(bf16_t)); bf16_t* h_k = (bf16_t*)malloc(SK*HD*sizeof(bf16_t)); bf16_t* h_v = (bf16_t*)malloc(HD*SK*sizeof(bf16_t)); srand(42); for (int d=0;d>>(d_q, d_k, d_v, d_tmem_dump, SCALE); cudaError_t err = cudaDeviceSynchronize(); if (err != cudaSuccess) { printf("CUDA ERROR: %s\n", cudaGetErrorString(err)); return 1; } float* h_dump = (float*)malloc(128 * sizeof(float)); cudaMemcpy(h_dump, d_tmem_dump, 128 * sizeof(float), cudaMemcpyDeviceToHost); // Reference float s[SK]; for (int j=0;j 1e-6f) { // Try to find matching reference output int best_d = -1; float best_diff = 1e10f; for (int d = 0; d < HD; d++) { float diff = fabsf(h_dump[col] - o_ref[d]); if (diff < best_diff) { best_diff = diff; best_d = d; } } printf(" col %3d: %10.6f", col, h_dump[col]); if (best_diff < 1e-3f) printf(" ≈ ref[%d]=%.6f (diff=%.2e)", best_d, o_ref[best_d], best_diff); printf("\n"); } } // Count non-zero columns in 0-63 range int nz = 0; for (int col = 0; col < 64; col++) if (fabsf(h_dump[col]) > 1e-6f) nz++; printf("\nNon-zero columns 0-63: %d (expected 64)\n", nz); nz = 0; for (int col = 64; col < 128; col++) if (fabsf(h_dump[col]) > 1e-6f) nz++; printf("Non-zero columns 64-127: %d (expected 0)\n", nz); // Which columns 0-63 are ZERO? printf("\nMissing columns (0 in 0-63): "); for (int col = 0; col < 64; col++) if (fabsf(h_dump[col]) < 1e-6f) printf("%d ", col); printf("\n"); cudaFree(d_q); cudaFree(d_k); cudaFree(d_v); cudaFree(d_tmem_dump); free(h_q); free(h_k); free(h_v); free(h_dump); return 0; }