test: clean multirow test with proper SMEM calc
This commit is contained in:
@@ -1,7 +1,6 @@
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/**
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* Debug test: verify fmha_6warp_multirow works for T=1 (decode regression).
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* Uses printf to trace kernel progress.
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* Compile: -DHD_VAL=64
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* Test multi-row FMHA kernel (6-warp, T>1 prefill).
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* Compile with -DHD_VAL=64 etc.
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*/
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#include <cuda_runtime.h>
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@@ -24,225 +23,156 @@ static float bf16_to_f32_host(bf16_t h) { uint32_t u=(uint32_t)h<<16; float f; m
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constexpr int HD = HD_VAL;
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constexpr int SK = 128;
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constexpr int MAX_T = 128;
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// Simplified kernel — T=1 only, no multi-head
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__global__ void __launch_bounds__(192)
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test_decode_kernel(const bf16_t* __restrict__ q, const bf16_t* __restrict__ k,
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const bf16_t* __restrict__ v, bf16_t* __restrict__ o, float* lse_out,
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int s_k, float scale) {
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const int tid = threadIdx.x;
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const int wid = tid / 32;
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const int lane = tid % 32;
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const int T = 1;
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#include "dsv4/kernels/attention/fmha_6warp_multirow.cuh"
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static constexpr int NKT_QK = HD / MMA_K_BF16;
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static constexpr int NKT_PV = SK / MMA_K_BF16;
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static constexpr int N_NSUB = HD / 16;
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static constexpr int TILE_SZ = 128 * MMA_K_BF16;
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static constexpr int V_SUB_SZ = 16 * MMA_K_BF16;
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static constexpr int TMEM_N = (HD <= 128) ? 128 : 256;
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static constexpr int CORES_MN = 128 / 8;
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extern __shared__ char sbuf[];
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uint32_t* sTmemBase = (uint32_t*)sbuf;
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float* sRowMax = (float*)(sbuf + 8);
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float* sRowSum = sRowMax + 1;
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bf16_t* sQ0 = (bf16_t*)(((uintptr_t)(sRowSum + 1) + 127) & ~(uintptr_t)127);
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bf16_t* sK0 = sQ0 + TILE_SZ;
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bf16_t* sPk = (bf16_t*)(((uintptr_t)(sK0 + TILE_SZ) + 127) & ~(uintptr_t)127);
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bf16_t* sV = (bf16_t*)(((uintptr_t)(sPk + TILE_SZ) + 127) & ~(uintptr_t)127);
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if (wid == 4) {
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uint32_t sp = __cvta_generic_to_shared(sTmemBase);
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tmem_alloc(sp, TMEM_N);
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}
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__syncthreads();
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uint32_t tb = *sTmemBase;
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// QK GEMM
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for (int kt = 0; kt < NKT_QK; kt++) {
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if (wid == 5) {
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for (int i = lane; i < TILE_SZ; i += 32) sQ0[i] = 0;
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for (int d = lane; d < MMA_K_BF16; d += 32) {
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int full_d = kt * MMA_K_BF16 + d;
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if (full_d < HD) {
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int ck = d / 8, lc = d % 8;
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sQ0[ck * CORES_MN * 64 + 0 * 64 + 0 * 8 + lc] = q[full_d];
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}
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}
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for (int i = lane; i < TILE_SZ; i += 32) sK0[i] = 0;
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for (int r = 0; r < s_k; r++) {
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for (int d = lane; d < MMA_K_BF16; d += 32) {
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int full_d = kt * MMA_K_BF16 + d;
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if (full_d < HD) {
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int ck = d / 8, lc = d % 8;
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int tmn = r / 8, lr = r % 8;
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sK0[ck * CORES_MN * 64 + tmn * 64 + lr * 8 + lc] = k[r * HD + full_d];
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}
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}
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}
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}
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__syncthreads();
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if (wid == 4) {
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uint32_t idesc = make_idesc(128, 128);
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uint64_t dq = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sQ0), 128);
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uint64_t dk = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sK0), 128);
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if (tid == 128) umma_ss_f16(tb, dq, dk, idesc, kt > 0);
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asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory");
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}
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__syncthreads();
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}
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// Softmax — T=1, only warp 0, lane 0
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float row_max = -INFINITY, row_sum = 0.0f;
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float s_vals[SK];
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if (wid == 0) {
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for (int n = 0; n < SK / 8; n++) {
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float tmp[8];
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asm volatile("tcgen05.ld.sync.aligned.32x32b.x8.b32 {%0,%1,%2,%3,%4,%5,%6,%7},[%8];"
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: "=f"(tmp[0]),"=f"(tmp[1]),"=f"(tmp[2]),"=f"(tmp[3]),
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"=f"(tmp[4]),"=f"(tmp[5]),"=f"(tmp[6]),"=f"(tmp[7])
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: "r"(tb + n*8));
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asm volatile("tcgen05.wait::ld.sync.aligned;");
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if (lane == 0) for (int c=0;c<8;c++) {
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s_vals[n*8+c] = tmp[c] * scale;
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row_max = fmaxf(row_max, tmp[c] * scale);
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}
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}
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row_max = wmax(row_max);
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if (lane == 0) *sRowMax = row_max;
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if (lane == 0) for (int j=0;j<SK;j++) {
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s_vals[j] = expf(s_vals[j] - row_max); row_sum += s_vals[j];
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}
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row_sum = wsum(row_sum);
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if (lane == 0) { *sRowSum = row_sum; for (int j=0;j<SK;j++) s_vals[j] /= row_sum; }
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}
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__syncthreads();
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// PV GEMM
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for (int n = 0; n < N_NSUB; n++) {
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int d_base = n * 16;
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for (int kt = 0; kt < NKT_PV; kt++) {
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if (wid == 5) {
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for (int i = lane; i < TILE_SZ; i += 32) sPk[i] = 0;
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if (lane < 16) {
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int c = lane; int ck = c/8, lc = c%8;
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sPk[ck * CORES_MN * 64 + 0*64 + 0*8 + lc] = f32_to_bf16(s_vals[kt * MMA_K_BF16 + c]);
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}
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for (int i = lane; i < V_SUB_SZ; i += 32) sV[i] = 0;
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for (int dd = lane; dd < 16; dd += 32) {
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for (int lr = 0; lr < MMA_K_BF16; lr++) {
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int r = kt * MMA_K_BF16 + lr;
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int g_mn = dd/8, g_k = lr/8, llr = dd%8, lc = lr%8;
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sV[g_k*2*64 + g_mn*64 + llr*8 + lc] = v[(d_base+dd)*s_k + r];
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}
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}
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}
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__syncthreads();
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if (wid == 4) {
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uint32_t idesc_pv = make_idesc(128, 16);
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uint64_t dp = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sPk), 128);
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uint64_t dv = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sV), 16);
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if (tid == 128) umma_ss_f16(tb + n*16, dp, dv, idesc_pv, kt > 0);
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asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory");
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}
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__syncthreads();
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}
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}
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// Epilogue
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if (wid == 0 && lane == 0) {
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float rm = *sRowMax, rs = *sRowSum;
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float inv = 1.0f / rs;
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for (int n = 0; n < N_NSUB * 2; n++) {
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float tmp[8];
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asm volatile("tcgen05.ld.sync.aligned.32x32b.x8.b32 {%0,%1,%2,%3,%4,%5,%6,%7},[%8];"
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: "=f"(tmp[0]),"=f"(tmp[1]),"=f"(tmp[2]),"=f"(tmp[3]),
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"=f"(tmp[4]),"=f"(tmp[5]),"=f"(tmp[6]),"=f"(tmp[7])
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: "r"(tb + n*8));
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asm volatile("tcgen05.wait::ld.sync.aligned;");
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for (int c = 0; c < 8; c++) {
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int d = n*8 + c;
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if (d < HD) o[d] = f32_to_bf16(tmp[c] * inv);
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}
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}
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if (lse_out) *lse_out = logf(rs) + rm;
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}
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__syncthreads();
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if (wid == 4) tmem_dealloc(tb, TMEM_N);
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// Compute SMEM size matching the kernel layout exactly
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static int compute_smem() {
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// Mirror the kernel's SMEM layout:
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// sTmemBase(8B) + sRowMax(128*4) + sRowSum(128*4) + align128
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// + sQ0(128*16*2) + sK0(128*16*2) + align128
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// + sPk(128*16*2) + align128 + sV(16*16*2) + slack
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size_t off = 0;
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off += 8; // sTmemBase + alignment
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off += 128 * sizeof(float); // sRowMax
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off += 128 * sizeof(float); // sRowSum
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off = (off + 127) & ~(size_t)127; // align for sQ0
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off += 128 * MMA_K_BF16 * sizeof(bf16_t); // sQ0
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off += 128 * MMA_K_BF16 * sizeof(bf16_t); // sK0
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off = (off + 127) & ~(size_t)127; // align for sPk
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off += 128 * MMA_K_BF16 * sizeof(bf16_t); // sPk
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off = (off + 127) & ~(size_t)127; // align for sV
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off += 16 * MMA_K_BF16 * sizeof(bf16_t); // sV
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off += 256; // slack
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return (int)off;
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}
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int main() {
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printf("Simple decode test (HD=%d, T=1)\n", HD);
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static void reference_attention_multirow(
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const bf16_t* q, const bf16_t* k, const bf16_t* v,
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float* o_ref, float* lse_ref,
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int hd, int T, int s_k, float scale
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) {
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for (int t = 0; t < T; t++) {
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float s[512];
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for (int j = 0; j < s_k; j++) {
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float dot = 0.0f;
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for (int d = 0; d < hd; d++)
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dot += bf16_to_f32_host(q[t * hd + d]) * bf16_to_f32_host(k[j * hd + d]);
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s[j] = dot * scale;
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}
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float mx = -INFINITY;
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for (int j = 0; j < s_k; j++) mx = fmaxf(mx, s[j]);
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float sm = 0.0f;
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for (int j = 0; j < s_k; j++) { s[j] = expf(s[j] - mx); sm += s[j]; }
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for (int j = 0; j < s_k; j++) s[j] /= sm;
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for (int d = 0; d < hd; d++) {
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float ov = 0.0f;
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for (int j = 0; j < s_k; j++) ov += s[j] * bf16_to_f32_host(v[d * s_k + j]);
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o_ref[t * hd + d] = ov;
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}
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if (lse_ref) lse_ref[t] = logf(sm) + mx;
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}
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}
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static int test_single_T(int T, int n_h = 1, int batch = 1) {
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printf("\n=== T=%d, n_h=%d, batch=%d, HD=%d, SK=%d ===\n", T, n_h, batch, HD, SK);
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const float SCALE = 1.0f / sqrtf((float)HD);
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int total_heads = batch * n_h;
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bf16_t *h_q = (bf16_t*)malloc(HD * sizeof(bf16_t));
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bf16_t *h_k = (bf16_t*)malloc(SK * HD * sizeof(bf16_t));
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bf16_t *h_v = (bf16_t*)malloc(HD * SK * sizeof(bf16_t));
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bf16_t *h_o = (bf16_t*)calloc(HD, sizeof(bf16_t));
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bf16_t* h_q = (bf16_t*)malloc(total_heads * T * HD * sizeof(bf16_t));
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bf16_t* h_k = (bf16_t*)malloc(total_heads * SK * HD * sizeof(bf16_t));
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bf16_t* h_v = (bf16_t*)malloc(total_heads * HD * SK * sizeof(bf16_t));
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bf16_t* h_o = (bf16_t*)calloc(total_heads * T * HD, sizeof(bf16_t));
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float* h_lse = (float*)calloc(total_heads * T, sizeof(float));
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srand(42);
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for (int i=0;i<HD;i++) h_q[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
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for (int i=0;i<SK*HD;i++) h_k[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
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for (int i=0;i<HD*SK;i++) h_v[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
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srand(42 + T);
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for (int i = 0; i < total_heads * T * HD; i++) h_q[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
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for (int i = 0; i < total_heads * SK * HD; i++) h_k[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
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for (int i = 0; i < total_heads * HD * SK; i++) h_v[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
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bf16_t *d_q, *d_k, *d_v, *d_o; float *d_lse;
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cudaMalloc(&d_q, HD*sizeof(bf16_t));
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cudaMalloc(&d_k, SK*HD*sizeof(bf16_t));
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cudaMalloc(&d_v, HD*SK*sizeof(bf16_t));
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cudaMalloc(&d_o, HD*sizeof(bf16_t));
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cudaMalloc(&d_lse, sizeof(float));
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cudaMemcpy(d_q, h_q, HD*sizeof(bf16_t), cudaMemcpyHostToDevice);
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cudaMemcpy(d_k, h_k, SK*HD*sizeof(bf16_t), cudaMemcpyHostToDevice);
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cudaMemcpy(d_v, h_v, HD*SK*sizeof(bf16_t), cudaMemcpyHostToDevice);
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cudaMalloc(&d_q, total_heads * T * HD * sizeof(bf16_t));
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cudaMalloc(&d_k, total_heads * SK * HD * sizeof(bf16_t));
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cudaMalloc(&d_v, total_heads * HD * SK * sizeof(bf16_t));
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cudaMalloc(&d_o, total_heads * T * HD * sizeof(bf16_t));
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cudaMalloc(&d_lse, total_heads * T * sizeof(float));
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cudaMemcpy(d_q, h_q, total_heads * T * HD * sizeof(bf16_t), cudaMemcpyHostToDevice);
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cudaMemcpy(d_k, h_k, total_heads * SK * HD * sizeof(bf16_t), cudaMemcpyHostToDevice);
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cudaMemcpy(d_v, h_v, total_heads * HD * SK * sizeof(bf16_t), cudaMemcpyHostToDevice);
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cudaMemset(d_o, 0, total_heads * T * HD * sizeof(bf16_t));
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cudaMemset(d_lse, 0, total_heads * T * sizeof(float));
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constexpr int TILE_SZ = 128 * MMA_K_BF16;
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constexpr int V_SUB_SZ = 16 * MMA_K_BF16;
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size_t smem_off = 8 + 128*4 + 128*4;
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smem_off = ((smem_off + 127) & ~(size_t)127);
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smem_off += TILE_SZ + TILE_SZ;
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smem_off = ((smem_off + 127) & ~(size_t)127);
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smem_off += TILE_SZ;
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smem_off = ((smem_off + 127) & ~(size_t)127);
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smem_off += V_SUB_SZ + 256;
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FmhaMultiRowParams params;
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params.q = d_q; params.k = d_k; params.v = d_v; params.o = d_o; params.lse = d_lse;
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params.s_k = SK; params.T = T; params.scale = SCALE; params.head_dim = HD;
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params.q_head_stride = T * HD; params.q_batch_stride = n_h * T * HD;
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params.k_head_stride = SK * HD; params.k_batch_stride = n_h * SK * HD;
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params.v_head_stride = HD * SK; params.v_batch_stride = n_h * HD * SK;
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params.o_head_stride = T * HD; params.o_batch_stride = n_h * T * HD;
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params.lse_head_stride = T; params.lse_batch_stride = n_h * T;
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test_decode_kernel<<<1, 192, smem_off>>>(d_q, d_k, d_v, d_o, d_lse, SK, SCALE);
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int smem = compute_smem();
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if (smem > 48 * 1024)
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cudaFuncSetAttribute(fmha_6warp_multirow_kernel<HD>, cudaFuncAttributeMaxDynamicSharedMemorySize, smem);
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dim3 grid(1, n_h, batch);
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fmha_6warp_multirow_kernel<HD><<<grid, 192, smem>>>(params);
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cudaError_t err = cudaDeviceSynchronize();
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if (err != cudaSuccess) {
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printf("CUDA ERROR: %s\n", cudaGetErrorString(err));
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printf("FAILED\n");
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} else {
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cudaMemcpy(h_o, d_o, HD*sizeof(bf16_t), cudaMemcpyDeviceToHost);
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// Reference
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float o_ref[512];
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for (int d = 0; d < HD; d++) o_ref[d] = 0.0f;
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float s[128];
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for (int j=0;j<SK;j++) {
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float dot = 0;
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for (int d=0;d<HD;d++) dot += bf16_to_f32_host(h_q[d]) * bf16_to_f32_host(h_k[j*HD+d]);
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s[j] = dot * SCALE;
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}
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float mx = -INFINITY;
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for (int j=0;j<SK;j++) mx = fmaxf(mx, s[j]);
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float sm = 0;
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for (int j=0;j<SK;j++) { s[j] = expf(s[j]-mx); sm += s[j]; }
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for (int j=0;j<SK;j++) s[j] /= sm;
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for (int d=0;d<HD;d++) for (int j=0;j<SK;j++) o_ref[d] += s[j]*bf16_to_f32_host(h_v[d*SK+j]);
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float cs=0,na=0,nb=0;
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for (int d=0;d<HD;d++) {
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float a = bf16_to_f32_host(h_o[d]);
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if (fabsf(o_ref[d])>1e-4f) { cs+=a*o_ref[d]; na+=a*a; nb+=o_ref[d]*o_ref[d]; }
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}
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cs /= (sqrtf(na)*sqrtf(nb)+1e-10f);
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printf("Cosine similarity: %.8f\n", cs);
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printf("%s\n", cs > 0.999f ? "PASSED" : "FAILED");
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printf(" CUDA ERROR: %s\n", cudaGetErrorString(err));
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cudaFree(d_q); cudaFree(d_k); cudaFree(d_v); cudaFree(d_o); cudaFree(d_lse);
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free(h_q); free(h_k); free(h_v); free(h_o); free(h_lse);
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return 0;
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}
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|
||||
cudaMemcpy(h_o, d_o, total_heads * T * HD * sizeof(bf16_t), cudaMemcpyDeviceToHost);
|
||||
cudaMemcpy(h_lse, d_lse, total_heads * T * sizeof(float), cudaMemcpyDeviceToHost);
|
||||
|
||||
int failed = 0; float min_cos = 1.0f;
|
||||
for (int b = 0; b < batch; b++) {
|
||||
for (int h = 0; h < n_h; h++) {
|
||||
int idx = b * n_h + h;
|
||||
float o_ref[MAX_T * 512]; float lse_ref[MAX_T];
|
||||
reference_attention_multirow(
|
||||
h_q + idx * T * HD, h_k + idx * SK * HD, h_v + idx * HD * SK,
|
||||
o_ref, lse_ref, HD, T, SK, SCALE);
|
||||
for (int t = 0; t < T; t++) {
|
||||
float cs=0,na=0,nb=0;
|
||||
for (int d=0;d<HD;d++) {
|
||||
float a=bf16_to_f32_host(h_o[(idx*T+t)*HD+d]), b2=o_ref[t*HD+d];
|
||||
if(fabsf(b2)>1e-4f){cs+=a*b2;na+=a*a;nb+=b2*b2;}
|
||||
}
|
||||
cs /= (sqrtf(na)*sqrtf(nb)+1e-10f);
|
||||
if(cs<min_cos) min_cos=cs;
|
||||
if(cs<0.999f) {
|
||||
printf(" FAIL b=%d h=%d t=%d: cos=%.6f\n",b,h,t,cs);
|
||||
failed++;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
printf(" min_cos=%.8f failed=%d %s\n", min_cos, failed, failed==0?"PASSED":"FAILED");
|
||||
|
||||
cudaFree(d_q); cudaFree(d_k); cudaFree(d_v); cudaFree(d_o); cudaFree(d_lse);
|
||||
free(h_q); free(h_k); free(h_v); free(h_o);
|
||||
return 0;
|
||||
free(h_q); free(h_k); free(h_v); free(h_o); free(h_lse);
|
||||
return failed == 0;
|
||||
}
|
||||
|
||||
int main() {
|
||||
printf("Multi-row FMHA test (HD=%d)\n", HD);
|
||||
|
||||
int ok = 1;
|
||||
ok &= test_single_T(1); // decode regression
|
||||
ok &= test_single_T(2);
|
||||
ok &= test_single_T(4);
|
||||
ok &= test_single_T(8);
|
||||
ok &= test_single_T(16);
|
||||
ok &= test_single_T(32);
|
||||
ok &= test_single_T(64);
|
||||
ok &= test_single_T(128);
|
||||
|
||||
printf("\n%s\n", ok ? "ALL PASSED" : "SOME FAILED");
|
||||
return ok ? 0 : 1;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user