/**
 * Generalized FMHA for HD=16/64/128/256 using N=16 PV sub-tiles.
 * Compile with -DHD_VAL=64 etc.
 * Default HD_VAL=64.
 */

#include <cuda_runtime.h>
#include <cstdio>
#include <cmath>
#include <cstdlib>
#include <cstring>

#ifndef HD_VAL
#define HD_VAL 64
#endif

#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 = HD_VAL;
constexpr int SK = 128, BLOCK_MN = 128;
constexpr int NKT_QK = HD / MMA_K_BF16;
constexpr int NKT_PV = SK / MMA_K_BF16;  // 8
constexpr int TILE_SZ = BLOCK_MN * MMA_K_BF16;  // 2048 BF16
constexpr int N_NSUB = HD / 16;
constexpr int V_SUB_SZ = 256;  // (16,16) canonical BF16
constexpr int TMEM_N = (HD <= 128) ? 128 : 256;

__global__ void __launch_bounds__(128)
fmha_kernel(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;

    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 + TILE_SZ;
    bf16_t* sPk = (bf16_t*)(((uintptr_t)(sK0 + 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 + V_SUB_SZ);

    // TMEM alloc
    if (wid == 1) tmem_alloc(__cvta_generic_to_shared(sTmemBase), TMEM_N);
    __syncthreads();
    uint32_t tb = *sTmemBase;

    // ===== QK GEMM (one K-tile at a time) =====
    {
        uint32_t idesc = make_idesc(BLOCK_MN, BLOCK_MN);
        for (int kt = 0; kt < NKT_QK; kt++) {
            for (int i = tid; i < TILE_SZ; i += 128) sQ0[i] = 0;
            for (int d = tid; d < MMA_K_BF16; d += 128) {
                int ck = d / 8, lc = d % 8;
                sQ0[ck * 16 * 64 + lc] = q[kt * MMA_K_BF16 + d];
            }
            for (int i = tid; i < TILE_SZ; i += 128) sK0[i] = 0;
            for (int r = 0; r < SK; r++) {
                for (int d = tid; d < MMA_K_BF16; d += 128) {
                    int ck = d / 8, lc = d % 8;
                    int tmn = r / 8, lr = r % 8;
                    sK0[ck * 16 * 64 + tmn * 64 + lr * 8 + lc] = k[r * HD + kt * MMA_K_BF16 + d];
                }
            }
            __syncthreads();

            uint64_t dq = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sQ0), BLOCK_MN);
            uint64_t dk = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sK0), BLOCK_MN);
            if (tid == 0) umma_ss_f16(tb, dq, dk, idesc, kt > 0);
            asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory");
            __syncthreads();
        }
    }

    // ===== Softmax (row 0 only) =====
    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<SK;j++) {
            s_vals[j] = expf(s_vals[j] - row_max);
            row_sum += s_vals[j];
        }
        row_sum = wsum(row_sum);
        if (lane == 0) for (int j=0;j<SK;j++) s_vals[j] /= row_sum;
        if (lane == 0) for (int j=0;j<SK;j++) s_p_vals[j] = s_vals[j];
    }
    __syncthreads();

    // ===== PV GEMM: N=16 sub-tiles =====
    {
        uint32_t idesc_pv16 = make_idesc(BLOCK_MN, 16);
        uint64_t dp = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sPk), BLOCK_MN);

        for (int n = 0; n < N_NSUB; n++) {
            int d_base = n * 16;
            for (int kt = 0; kt < NKT_PV; kt++) {
                for (int i = tid; i < TILE_SZ; i += 128) sPk[i] = 0;
                if (tid < 16) {
                    int c = tid;
                    int ck = c / 8, lc = c % 8;
                    sPk[ck * 16 * 64 + 0 * 64 + 0 * 8 + lc] = f32_to_bf16(s_p_vals[kt * MMA_K_BF16 + c]);
                }
                for (int i = tid; i < V_SUB_SZ; i += 128) sV[i] = 0;
                for (int dd = tid; dd < 16; dd += 128) {
                    for (int lr = 0; lr < MMA_K_BF16; lr++) {
                        int r = kt * MMA_K_BF16 + lr;
                        int g_mn = dd / 8, g_k = lr / 8;
                        int llr = dd % 8, lc = lr % 8;
                        sV[g_k * 2 * 64 + g_mn * 64 + llr * 8 + lc] = v[(d_base + dd) * SK + r];
                    }
                }
                __syncthreads();

                uint64_t dv = make_umma_desc_kmajor_none(__cvta_generic_to_shared(sV), 16);
                if (tid == 0) umma_ss_f16(tb + n * 16, dp, dv, idesc_pv16, kt > 0);
                asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory");
                __syncthreads();
            }
        }
    }

    // ===== Epilogue =====
    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 + 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];
        }
        if (lane == 0) for (int d=0;d<HD;d++) o_out[d] = f32_to_bf16(o_vals[d]);
    }
    __syncthreads();

    // Scalar reference
    if (tid == 0) {
        float s[SK];
        for (int j=0;j<SK;j++) {
            float dot = 0.0f;
            for (int d=0;d<HD;d++) dot += bf16_to_f32(q[d]) * bf16_to_f32(k[j*HD+d]);
            s[j] = dot * scale;
        }
        float mx = -INFINITY;
        for (int j=0;j<SK;j++) mx = fmaxf(mx, s[j]);
        float sm = 0.0f;
        for (int j=0;j<SK;j++) { s[j] = expf(s[j]-mx); sm += s[j]; }
        for (int j=0;j<SK;j++) s[j] /= sm;
        for (int d=0;d<HD;d++) {
            float ov = 0.0f;
            for (int j=0;j<SK;j++) ov += s[j] * bf16_to_f32(v[d*SK+j]);
            o_scalar[d] = ov;
        }
    }

    if (wid == 0) tmem_dealloc(tb, TMEM_N);
}

int main() {
    printf("=== Generalized FMHA HD=%d (N=16 PV sub-tiles) ===\n", HD);
    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));
    bf16_t* h_o = (bf16_t*)calloc(HD, sizeof(bf16_t));
    float* h_o_scalar = (float*)calloc(HD, sizeof(float));

    srand(42);
    for (int d=0;d<HD;d++) h_q[d] = f32_to_bf16_host((float)(rand()%100)/100.0f-0.5f);
    for (int i=0;i<SK*HD;i++) h_k[i] = f32_to_bf16_host((float)(rand()%100)/100.0f-0.5f);
    for (int i=0;i<HD*SK;i++) h_v[i] = f32_to_bf16_host((float)(rand()%100)/100.0f-0.5f);

    bf16_t *d_q,*d_k,*d_v,*d_o; float *d_o_scalar;
    cudaMalloc(&d_q, HD*sizeof(bf16_t));
    cudaMalloc(&d_k, SK*HD*sizeof(bf16_t));
    cudaMalloc(&d_v, HD*SK*sizeof(bf16_t));
    cudaMalloc(&d_o, HD*sizeof(bf16_t));
    cudaMalloc(&d_o_scalar, HD*sizeof(float));
    cudaMemcpy(d_q, h_q, HD*sizeof(bf16_t), cudaMemcpyHostToDevice);
    cudaMemcpy(d_k, h_k, SK*HD*sizeof(bf16_t), cudaMemcpyHostToDevice);
    cudaMemcpy(d_v, h_v, HD*SK*sizeof(bf16_t), cudaMemcpyHostToDevice);

    int smem = (4+16 + TILE_SZ*2 + TILE_SZ*2 + TILE_SZ*2 + V_SUB_SZ*2 + SK*4 + 256 + 127) & ~127;
    printf("SMEM: %d bytes (%.1f KB), TMEM: %d cols, N_NSUB: %d, NKT_QK: %d\n",
           smem, smem/1024.0f, TMEM_N, N_NSUB, NKT_QK);

    if (smem > 48 * 1024) {
        cudaFuncSetAttribute(fmha_kernel, cudaFuncAttributeMaxDynamicSharedMemorySize, smem);
    }
    fmha_kernel<<<1, 128, smem>>>(d_q, d_k, d_v, d_o, d_o_scalar, SCALE);

    cudaError_t launch_err = cudaGetLastError();
    if (launch_err != cudaSuccess) { printf("LAUNCH ERROR: %s\n", cudaGetErrorString(launch_err)); return 1; }

    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..7] MMA:  "); for(int d=0;d<min(8,HD);d++) printf("%.6f ",bf16_to_f32_host(h_o[d])); printf("\n");
    printf("O[0..7] ref:  "); for(int d=0;d<min(8,HD);d++) printf("%.6f ",h_o_scalar[d]); printf("\n");

    float cs=0,na=0,nb=0;
    for (int d=0;d<HD;d++) {
        float a=bf16_to_f32_host(h_o[d]),b=h_o_scalar[d];
        if(fabsf(b)>1e-4f) { cs+=a*b; na+=a*a; nb+=b*b; }
    }
    cs /= (sqrtf(na)*sqrtf(nb)+1e-10f);
    printf("Filtered cosine: %.8f\n", cs);
    printf("Test %s\n", cs > 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 cs > 0.999f ? 0 : 1;
}
