From 2885b3f2ed634265551ee6e75c3cf4f8927be4c9 Mon Sep 17 00:00:00 2001 From: biondizzle Date: Thu, 28 May 2026 13:39:34 +0000 Subject: [PATCH] test: full FMHA HD=16 with PV GEMM via tcgen05.mma TS --- tests/unit/test_fmha_ts_hd16.cu | 214 ++++++++++++++++++++++++++++++++ 1 file changed, 214 insertions(+) create mode 100644 tests/unit/test_fmha_ts_hd16.cu diff --git a/tests/unit/test_fmha_ts_hd16.cu b/tests/unit/test_fmha_ts_hd16.cu new file mode 100644 index 00000000..889d06be --- /dev/null +++ b/tests/unit/test_fmha_ts_hd16.cu @@ -0,0 +1,214 @@ +/** + * Full UMMA FMHA — HD=16, SK=128, with PV GEMM via tcgen05.mma TS + * + * Pipeline: Q×K^T (SS) → softmax → P×V (TS) → epilogue + * TMEM: columns 0-127 = P, columns 128-159 = O + * + * PV GEMM: 8 K-tiles, each A=(128,16) from TMEM, B=(16,16) from SMEM + * Accumulate O in TMEM at columns 128-143 + */ + +#include +#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 = 16, SK = 128, BLOCK_MN = 128; +constexpr int VKT = SK / MMA_K_BF16; // 8 PV K-tiles +constexpr int V_TILE_SZ = MMA_K_BF16 * HD; // 256 BF16 per V K-tile +constexpr int TMEM_P = 128; // P: 128 columns +constexpr int TMEM_O = 32; // O: 16 cols, round to 32 (min, power of 2) +constexpr int TMEM_N = 256; // total: 128 + 32 = 160 → round to 256 + +__global__ void __launch_bounds__(128) +test_fmha_ts(const bf16_t* q, const bf16_t* k, const bf16_t* v, + bf16_t* o_out, float* o_scalar, float scale) +{ + const int tid = threadIdx.x, wid = tid / 32, lane = tid % 32; + + // SMEM: tmem_base + sQ(128,16)+pad + sK(128,16) + V tiles (8 × 16×16) + extern __shared__ char sbuf[]; + uint32_t* sTmemBase = (uint32_t*)sbuf; + bf16_t* sQ = (bf16_t*)(((uintptr_t)(sbuf + 4) + 15) & ~(uintptr_t)15); + bf16_t* sK = sQ + 128 * 16 + 4096; + bf16_t* sV_base = sK + 128 * 16; + float* sQ_row = (float*)(sV_base + VKT * V_TILE_SZ); + + for (int d = tid; d < HD; d += 128) sQ_row[d] = bf16_to_f32(q[d]); + + // TMEM alloc — 256 columns + if (wid == 1) tmem_alloc(__cvta_generic_to_shared(sTmemBase), TMEM_N); + __syncthreads(); + uint32_t tb = *sTmemBase; + uint32_t tb_o = tb + TMEM_P; // O at column 128 + + // Load Q, K + write_q_to_smem(sQ, q); + write_k_to_smem(sK, k); + bf16_t* sQ_pad = sQ + 128 * 16; + for (int i = tid; i < 4096; i += 128) sQ_pad[i] = 0; + + // Load V as 8 K-tiles of (16, 16) canonical + for (int i = tid; i < VKT * V_TILE_SZ; i += 128) sV_base[i] = 0; + for (int kt = 0; kt < VKT; kt++) { + bf16_t* sv = sV_base + kt * V_TILE_SZ; + for (int i = tid; i < MMA_K_BF16 * HD; i += 128) { + int r = i / HD, d = i % HD; + int ck = d / 8, lc = d % 8; + int tmn = r / 8, lr = r % 8; + sv[ck * 2 * 64 + tmn * 64 + lr * 8 + lc] = v[d * SK + kt * MMA_K_BF16 + r]; + } + } + __syncthreads(); + + // STEP 1: QK GEMM + uint64_t desc_q = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sQ), BLOCK_MN); + uint64_t desc_k = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sK), BLOCK_MN); + uint32_t idesc_qk = make_idesc(BLOCK_MN, BLOCK_MN); + if (lane == 0) umma_ss_f16(tb, desc_q, desc_k, idesc_qk, false); + asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory"); + __syncthreads(); + + // STEP 2: Softmax + write P to TMEM + 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(); + } + asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory"); + __syncthreads(); + + // STEP 4: Epilogue — read O from TMEM, apply MMA scale (0.5), write to GMEM + if (wid == 0) { + float o_vals[HD]; + for (int n = 0; n < HD / 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_o + n*8)); + asm volatile("tcgen05.wait::ld.sync.aligned;"); + if (lane == 0) for (int c=0;c<8;c++) o_vals[n*8+c] = tmp[c] * 2.0f; // Undo MMA 0.5 scale + } + if (lane == 0) for (int d=0;d>>(d_q, d_k, d_v, d_o, d_o_scalar, SCALE); + + cudaError_t err = cudaDeviceSynchronize(); + if (err != cudaSuccess) { printf("CUDA ERROR: %s\n", cudaGetErrorString(err)); return 1; } + + cudaMemcpy(h_o, d_o, HD*sizeof(bf16_t), cudaMemcpyDeviceToHost); + cudaMemcpy(h_o_scalar, d_o_scalar, HD*sizeof(float), cudaMemcpyDeviceToHost); + + printf("O[0..15] MMA: "); for(int d=0;d0 ? max_diff/max_val : max_diff; + float cos_sim=0,na=0,nb=0; + for (int d=0;d 0.999f ? "PASSED" : "FAILED"); + + cudaFree(d_q); cudaFree(d_k); cudaFree(d_v); cudaFree(d_o); cudaFree(d_o_scalar); + free(h_q); free(h_k); free(h_v); free(h_o); free(h_o_scalar); + return cos_sim > 0.999f ? 0 : 1; +}