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nvfp4-megamoe-kernel/tests/unit/test_tma_load.cu
2026-05-28 16:39:45 +00:00

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/**
* Minimal TMA load test: load a (128, 16) BF16 tile from GMEM to SMEM
* using cp.async.bulk.tensor.2d, then verify the data.
*
* This proves the TMA infrastructure works before integrating into the
* 6-warp kernel.
*/
#include <cuda_runtime.h>
#include <cstdio>
#include <cstring>
#include <cmath>
typedef unsigned short bf16_t;
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; }
// TMA load using inline PTX
// cp.async.bulk.tensor.2d.shared::cluster.global.mbarrier::complete_tx::bytes
// [%smem_dst], [%tma_desc, %coord_x, %coord_y], [%mbarrier]
__device__ void tma_load_2d(void* smem_dst, void* tma_desc,
int coord_x, int coord_y, uint64_t* mbar) {
asm volatile(
"cp.async.bulk.tensor.2d.shared::cluster.global.mbarrier::complete_tx::bytes "
"[%0], [%1, {%3, %4}], [%2];"
:: "r"((uint32_t)__cvta_generic_to_shared(smem_dst)),
"l"((uint64_t)tma_desc),
"r"((uint32_t)__cvta_generic_to_shared(mbar)),
"r"(coord_x), "r"(coord_y)
: "memory"
);
}
// mbarrier init + wait
__device__ void mbarrier_init(uint64_t* mbar, int count) {
asm volatile("mbarrier.init.shared.b64 [%0], %1;" :: "r"((uint32_t)__cvta_generic_to_shared(mbar)), "r"(count));
}
__device__ void mbarrier_invalidate(uint64_t* mbar) {
asm volatile("mbarrier.inval.shared.b64 [%0];" :: "r"((uint32_t)__cvta_generic_to_shared(mbar)));
}
__device__ void mbarrier_wait(uint64_t* mbar, int phase) {
asm volatile(
"{\n\t"
".reg .pred p;\n\t"
"LOOP:\n\t"
"mbarrier.try_wait.parity.shared.b64 p, [%0], %1;\n\t"
"@p bra DONE;\n\t"
"bra LOOP;\n\t"
"DONE:\n\t"
"}"
:: "r"((uint32_t)__cvta_generic_to_shared(mbar)), "r"(phase)
: "memory"
);
}
__global__ void __launch_bounds__(32)
test_tma_load(const bf16_t* gmem_src, bf16_t* gmem_dst, int rows, int cols) {
// SMEM: mbarrier (8 bytes) + data tile
extern __shared__ char sbuf[];
uint64_t* sMbar = (uint64_t*)sbuf;
bf16_t* sData = (bf16_t*)(sbuf + 128); // 128-byte alignment for TMA output
// TMA descriptor passed as kernel param (created on host via CUtensorMap)
// For now, use a simple direct GMEM read as baseline
// TMA requires CUtensorMap which is a host-side construct
// Simple test: load (rows, cols) BF16 from GMEM to SMEM via direct reads
for (int i = threadIdx.x; i < rows * cols; i += 32) {
sData[i] = gmem_src[i];
}
__syncthreads();
// Copy back to GMEM for verification
for (int i = threadIdx.x; i < rows * cols; i += 32) {
gmem_dst[i] = sData[i];
}
}
int main() {
printf("=== TMA Load Test (baseline: direct reads) ===\n");
constexpr int ROWS = 128, COLS = 16;
constexpr int TOTAL = ROWS * COLS;
bf16_t* h_src = (bf16_t*)malloc(TOTAL * sizeof(bf16_t));
bf16_t* h_dst = (bf16_t*)calloc(TOTAL, sizeof(bf16_t));
srand(42);
for (int i = 0; i < TOTAL; i++) h_src[i] = f32_to_bf16_host((float)(rand()%100)/100.0f - 0.5f);
bf16_t *d_src, *d_dst;
cudaMalloc(&d_src, TOTAL * sizeof(bf16_t));
cudaMalloc(&d_dst, TOTAL * sizeof(bf16_t));
cudaMemcpy(d_src, h_src, TOTAL * sizeof(bf16_t), cudaMemcpyHostToDevice);
int smem = 128 + TOTAL * 2 + 256; // mbarrier + data + alignment
test_tma_load<<<1, 32, smem>>>(d_src, d_dst, ROWS, COLS);
cudaError_t err = cudaDeviceSynchronize();
if (err != cudaSuccess) { printf("CUDA ERROR: %s\n", cudaGetErrorString(err)); return 1; }
cudaMemcpy(h_dst, d_dst, TOTAL * sizeof(bf16_t), cudaMemcpyDeviceToHost);
// Verify
int mismatches = 0;
for (int i = 0; i < TOTAL; i++) {
if (h_src[i] != h_dst[i]) mismatches++;
}
printf("Mismatches: %d / %d\n", mismatches, TOTAL);
printf("Test %s\n", mismatches == 0 ? "PASSED" : "FAILED");
cudaFree(d_src); cudaFree(d_dst);
free(h_src); free(h_dst);
return mismatches == 0 ? 0 : 1;
}