/**
 * Full UMMA FMHA — HD=16, SK=128, T=1 (decode)
 * 
 * Pipeline:
 *   Q×K^T (UMMA SS) → softmax (TMEM read/write) → PV (register math)
 * 
 * For decode (T=1), P is (1, SK) — only row 0 is non-zero.
 * PV = P[0,:] × V is just a weighted sum: O[d] = Σ P[0,j] × V[d,j].
 * No UMMA needed for PV — compute directly in registers.
 * 
 * TMEM: 128 columns for S/P. O computed in registers.
 */

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

#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;

__global__ void __launch_bounds__(128)
test_fmha_hd16(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* sQ = (bf16_t*)(((uintptr_t)(sbuf + 4) + 15) & ~(uintptr_t)15);
    bf16_t* sK = sQ + 128 * 16 + 4096;
    float* sQ_row = (float*)(sK + 128 * 16);

    for (int d = tid; d < HD; d += 128) sQ_row[d] = bf16_to_f32(q[d]);

    if (wid == 1) tmem_alloc(__cvta_generic_to_shared(sTmemBase), 128);
    __syncthreads();
    uint32_t tb = *sTmemBase;

    write_q_to_smem<HD>(sQ, q);
    write_k_to_smem<SK, HD>(sK, k);
    bf16_t* sQ_pad = sQ + 128 * 16;
    for (int i = tid; i < 4096; i += 128) sQ_pad[i] = 0;
    __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 = make_idesc(BLOCK_MN, BLOCK_MN);
    if (lane == 0) umma_ss_f16(tb, desc_q, desc_k, idesc, false);
    asm volatile("tcgen05.fence::after_thread_sync;" ::: "memory");
    __syncthreads();

    // STEP 2: Softmax — read S, compute P, 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<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;

        // Write P back to TMEM
        for (int n = 0; n < SK / 8; n++) {
            float p0=(lane==0)?s_vals[n*8+0]:0, p1=(lane==0)?s_vals[n*8+1]:0;
            float p2=(lane==0)?s_vals[n*8+2]:0, p3=(lane==0)?s_vals[n*8+3]:0;
            float p4=(lane==0)?s_vals[n*8+4]:0, p5=(lane==0)?s_vals[n*8+5]:0;
            float p6=(lane==0)?s_vals[n*8+6]:0, p7=(lane==0)?s_vals[n*8+7]:0;
            asm volatile("tcgen05.st.sync.aligned.32x32b.x8.b32 [%0],{%1,%2,%3,%4,%5,%6,%7,%8};" :: "r"(tb+n*8),"f"(p0),"f"(p1),"f"(p2),"f"(p3),"f"(p4),"f"(p5),"f"(p6),"f"(p7));
        }
        tmem_fence_store();
    }
    __syncthreads();

    // STEP 3: Just read P from TMEM and write to output (debug)
    if (wid == 0) {
        float p_vals[SK];
        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++) p_vals[n*8+c] = tmp[c];
        }
        if (lane == 0) for (int j=0;j<SK;j++) o_out[j] = f32_to_bf16(p_vals[j]);
    }
    __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 += sQ_row[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, 128);
}

int main() {
    printf("=== Full UMMA FMHA HD=16 (decode) ===\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));
    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 + 128*16*2+4096 + 128*16*2 + 16*4 + 256 + 127) & ~127;
    test_fmha_hd16<<<1, 128, smem>>>(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;d<HD;d++) printf("%.6f ",bf16_to_f32_host(h_o[d])); printf("\n");
    printf("O[0..15] ref:  "); for(int d=0;d<HD;d++) printf("%.6f ",h_o_scalar[d]); printf("\n");

    float max_diff=0, max_val=0;
    for (int d=0;d<HD;d++) {
        max_diff = fmaxf(max_diff, fabsf(bf16_to_f32_host(h_o[d]) - h_o_scalar[d]));
        max_val = fmaxf(max_val, fabsf(h_o_scalar[d]));
    }
    float rel_err = max_val>0 ? max_diff/max_val : max_diff;
    float cos_sim = 0, norm_a=0, norm_b=0;
    for (int d=0;d<HD;d++) {
        float a=bf16_to_f32_host(h_o[d]), b=h_o_scalar[d];
        cos_sim += a*b; norm_a += a*a; norm_b += b*b;
    }
    cos_sim /= (sqrtf(norm_a)*sqrtf(norm_b)+1e-10f);
    printf("Max rel err: %.8f | cosine: %.8f\n", rel_err, cos_sim);
    printf("Test %s\n", cos_sim > 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;
}