#define _POSIX_C_SOURCE 200809L

#include <dlfcn.h>
#include <math.h>
#include <stdarg.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>

#if defined(__has_include)
#if __has_include(<cublasLt.h>)
#include <cublasLt.h>
#define HAVE_CUBLASLT_HEADERS 1
#else
#define HAVE_CUBLASLT_HEADERS 0
#endif
#else
#define HAVE_CUBLASLT_HEADERS 0
#endif

typedef int CUdevice;
typedef uint64_t CUdeviceptr;
typedef int CUresult;
typedef void *CUcontext;
typedef void *CUmodule;
typedef void *CUfunction;
typedef void *CUstream;

#define CU_SUCCESS 0
#define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR 75
#define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR 76

static const char *ptx_source =
    ".version 6.0\n"
    ".target sm_30\n"
    ".address_size 64\n"
    "\n"
    ".visible .entry burn(\n"
    "    .param .u64 data,\n"
    "    .param .u32 words,\n"
    "    .param .u32 rounds\n"
    ")\n"
    "{\n"
    "    .reg .pred %p<2>;\n"
    "    .reg .b32 %r<8>;\n"
    "    .reg .b64 %rd<5>;\n"
    "\n"
    "    ld.param.u64 %rd1, [data];\n"
    "    ld.param.u32 %r1, [words];\n"
    "    ld.param.u32 %r2, [rounds];\n"
    "    mov.u32 %r3, %ctaid.x;\n"
    "    mov.u32 %r4, %ntid.x;\n"
    "    mov.u32 %r5, %tid.x;\n"
    "    mad.lo.s32 %r0, %r3, %r4, %r5;\n"
    "    setp.ge.u32 %p0, %r0, %r1;\n"
    "    @%p0 bra DONE;\n"
    "    mul.wide.u32 %rd2, %r0, 4;\n"
    "    add.s64 %rd3, %rd1, %rd2;\n"
    "    ld.global.u32 %r6, [%rd3];\n"
    "LOOP:\n"
    "    setp.eq.u32 %p1, %r2, 0;\n"
    "    @%p1 bra STORE;\n"
    "    mad.lo.u32 %r6, %r6, 1664525, 1013904223;\n"
    "    sub.u32 %r2, %r2, 1;\n"
    "    bra LOOP;\n"
    "STORE:\n"
    "    st.global.u32 [%rd3], %r6;\n"
    "DONE:\n"
    "    ret;\n"
    "}\n";

typedef CUresult (*cuInit_fn)(unsigned int);
typedef CUresult (*cuDeviceGetCount_fn)(int *);
typedef CUresult (*cuDeviceGet_fn)(CUdevice *, int);
typedef CUresult (*cuDeviceGetName_fn)(char *, int, CUdevice);
typedef CUresult (*cuDeviceGetAttribute_fn)(int *, int, CUdevice);
typedef CUresult (*cuCtxCreate_fn)(CUcontext *, unsigned int, CUdevice);
typedef CUresult (*cuCtxDestroy_fn)(CUcontext);
typedef CUresult (*cuCtxSynchronize_fn)(void);
typedef CUresult (*cuMemAlloc_fn)(CUdeviceptr *, size_t);
typedef CUresult (*cuMemFree_fn)(CUdeviceptr);
typedef CUresult (*cuMemsetD8_fn)(CUdeviceptr, unsigned char, size_t);
typedef CUresult (*cuMemcpyHtoD_fn)(CUdeviceptr, const void *, size_t);
typedef CUresult (*cuMemcpyDtoH_fn)(void *, CUdeviceptr, size_t);
typedef CUresult (*cuModuleLoadDataEx_fn)(CUmodule *, const void *, unsigned int, void *, void *);
typedef CUresult (*cuModuleGetFunction_fn)(CUfunction *, CUmodule, const char *);
typedef CUresult (*cuLaunchKernel_fn)(CUfunction,
                                      unsigned int,
                                      unsigned int,
                                      unsigned int,
                                      unsigned int,
                                      unsigned int,
                                      unsigned int,
                                      unsigned int,
                                      CUstream,
                                      void **,
                                      void **);
typedef CUresult (*cuGetErrorName_fn)(CUresult, const char **);
typedef CUresult (*cuGetErrorString_fn)(CUresult, const char **);

struct cuda_api {
    void *lib;
    cuInit_fn cuInit;
    cuDeviceGetCount_fn cuDeviceGetCount;
    cuDeviceGet_fn cuDeviceGet;
    cuDeviceGetName_fn cuDeviceGetName;
    cuDeviceGetAttribute_fn cuDeviceGetAttribute;
    cuCtxCreate_fn cuCtxCreate;
    cuCtxDestroy_fn cuCtxDestroy;
    cuCtxSynchronize_fn cuCtxSynchronize;
    cuMemAlloc_fn cuMemAlloc;
    cuMemFree_fn cuMemFree;
    cuMemsetD8_fn cuMemsetD8;
    cuMemcpyHtoD_fn cuMemcpyHtoD;
    cuMemcpyDtoH_fn cuMemcpyDtoH;
    cuModuleLoadDataEx_fn cuModuleLoadDataEx;
    cuModuleGetFunction_fn cuModuleGetFunction;
    cuLaunchKernel_fn cuLaunchKernel;
    cuGetErrorName_fn cuGetErrorName;
    cuGetErrorString_fn cuGetErrorString;
};

struct stress_report {
    char backend[32];
    char device[128];
    int cc_major;
    int cc_minor;
    int buffer_mb;
    unsigned long iterations;
    uint64_t checksum;
    char details[1024];
};

static int load_symbol(void *lib, const char *name, void **out) {
    *out = dlsym(lib, name);
    return *out != NULL;
}

static int load_cuda(struct cuda_api *api) {
    memset(api, 0, sizeof(*api));
    api->lib = dlopen("libcuda.so.1", RTLD_NOW | RTLD_LOCAL);
    if (!api->lib) {
        return 0;
    }
    return
        load_symbol(api->lib, "cuInit", (void **)&api->cuInit) &&
        load_symbol(api->lib, "cuDeviceGetCount", (void **)&api->cuDeviceGetCount) &&
        load_symbol(api->lib, "cuDeviceGet", (void **)&api->cuDeviceGet) &&
        load_symbol(api->lib, "cuDeviceGetName", (void **)&api->cuDeviceGetName) &&
        load_symbol(api->lib, "cuDeviceGetAttribute", (void **)&api->cuDeviceGetAttribute) &&
        load_symbol(api->lib, "cuCtxCreate_v2", (void **)&api->cuCtxCreate) &&
        load_symbol(api->lib, "cuCtxDestroy_v2", (void **)&api->cuCtxDestroy) &&
        load_symbol(api->lib, "cuCtxSynchronize", (void **)&api->cuCtxSynchronize) &&
        load_symbol(api->lib, "cuMemAlloc_v2", (void **)&api->cuMemAlloc) &&
        load_symbol(api->lib, "cuMemFree_v2", (void **)&api->cuMemFree) &&
        load_symbol(api->lib, "cuMemsetD8_v2", (void **)&api->cuMemsetD8) &&
        load_symbol(api->lib, "cuMemcpyHtoD_v2", (void **)&api->cuMemcpyHtoD) &&
        load_symbol(api->lib, "cuMemcpyDtoH_v2", (void **)&api->cuMemcpyDtoH) &&
        load_symbol(api->lib, "cuModuleLoadDataEx", (void **)&api->cuModuleLoadDataEx) &&
        load_symbol(api->lib, "cuModuleGetFunction", (void **)&api->cuModuleGetFunction) &&
        load_symbol(api->lib, "cuLaunchKernel", (void **)&api->cuLaunchKernel);
}

static const char *cu_error_name(struct cuda_api *api, CUresult rc) {
    const char *value = NULL;
    if (api->cuGetErrorName && api->cuGetErrorName(rc, &value) == CU_SUCCESS && value) {
        return value;
    }
    return "CUDA_ERROR";
}

static const char *cu_error_string(struct cuda_api *api, CUresult rc) {
    const char *value = NULL;
    if (api->cuGetErrorString && api->cuGetErrorString(rc, &value) == CU_SUCCESS && value) {
        return value;
    }
    return "unknown";
}

static int check_rc(struct cuda_api *api, const char *step, CUresult rc) {
    if (rc == CU_SUCCESS) {
        return 1;
    }
    fprintf(stderr, "%s failed: %s (%s)\n", step, cu_error_name(api, rc), cu_error_string(api, rc));
    return 0;
}

static double now_seconds(void) {
    struct timespec ts;
    clock_gettime(CLOCK_MONOTONIC, &ts);
    return (double)ts.tv_sec + ((double)ts.tv_nsec / 1000000000.0);
}

#if HAVE_CUBLASLT_HEADERS
static size_t round_down_size(size_t value, size_t multiple) {
    if (multiple == 0 || value < multiple) {
        return value;
    }
    return value - (value % multiple);
}
#endif

static int query_compute_capability(struct cuda_api *api, CUdevice dev, int *major, int *minor) {
    int cc_major = 0;
    int cc_minor = 0;
    if (!check_rc(api,
                  "cuDeviceGetAttribute(major)",
                  api->cuDeviceGetAttribute(&cc_major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, dev))) {
        return 0;
    }
    if (!check_rc(api,
                  "cuDeviceGetAttribute(minor)",
                  api->cuDeviceGetAttribute(&cc_minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, dev))) {
        return 0;
    }
    *major = cc_major;
    *minor = cc_minor;
    return 1;
}

#if HAVE_CUBLASLT_HEADERS
static void append_detail(char *buf, size_t cap, const char *fmt, ...) {
    size_t len = strlen(buf);
    if (len >= cap) {
        return;
    }
    va_list ap;
    va_start(ap, fmt);
    vsnprintf(buf + len, cap - len, fmt, ap);
    va_end(ap);
}
#endif

static int run_ptx_fallback(struct cuda_api *api,
                            CUdevice dev,
                            const char *device_name,
                            int cc_major,
                            int cc_minor,
                            int seconds,
                            int size_mb,
                            struct stress_report *report) {
    CUcontext ctx = NULL;
    CUdeviceptr device_mem = 0;
    CUmodule module = NULL;
    CUfunction kernel = NULL;
    uint32_t sample[256];
    uint32_t words = 0;
    unsigned long iterations = 0;

    memset(report, 0, sizeof(*report));
    snprintf(report->backend, sizeof(report->backend), "driver-ptx");
    snprintf(report->device, sizeof(report->device), "%s", device_name);
    report->cc_major = cc_major;
    report->cc_minor = cc_minor;
    report->buffer_mb = size_mb;

    if (!check_rc(api, "cuCtxCreate", api->cuCtxCreate(&ctx, 0, dev))) {
        return 0;
    }

    size_t bytes = (size_t)size_mb * 1024u * 1024u;
    if (bytes < 4u * 1024u * 1024u) {
        bytes = 4u * 1024u * 1024u;
    }
    if (bytes > (size_t)1024u * 1024u * 1024u) {
        bytes = (size_t)1024u * 1024u * 1024u;
    }
    words = (uint32_t)(bytes / sizeof(uint32_t));

    if (!check_rc(api, "cuMemAlloc", api->cuMemAlloc(&device_mem, bytes))) {
        api->cuCtxDestroy(ctx);
        return 0;
    }
    if (!check_rc(api, "cuMemsetD8", api->cuMemsetD8(device_mem, 0, bytes))) {
        api->cuMemFree(device_mem);
        api->cuCtxDestroy(ctx);
        return 0;
    }
    if (!check_rc(api,
                  "cuModuleLoadDataEx",
                  api->cuModuleLoadDataEx(&module, ptx_source, 0, NULL, NULL))) {
        api->cuMemFree(device_mem);
        api->cuCtxDestroy(ctx);
        return 0;
    }
    if (!check_rc(api, "cuModuleGetFunction", api->cuModuleGetFunction(&kernel, module, "burn"))) {
        api->cuMemFree(device_mem);
        api->cuCtxDestroy(ctx);
        return 0;
    }

    unsigned int threads = 256;
    unsigned int blocks = (unsigned int)((words + threads - 1) / threads);
    uint32_t rounds = 1024;
    void *params[] = {&device_mem, &words, &rounds};

    double start = now_seconds();
    double deadline = start + (double)seconds;
    while (now_seconds() < deadline) {
        if (!check_rc(api,
                      "cuLaunchKernel",
                      api->cuLaunchKernel(kernel, blocks, 1, 1, threads, 1, 1, 0, NULL, params, NULL))) {
            api->cuMemFree(device_mem);
            api->cuCtxDestroy(ctx);
            return 0;
        }
        iterations++;
    }

    if (!check_rc(api, "cuCtxSynchronize", api->cuCtxSynchronize())) {
        api->cuMemFree(device_mem);
        api->cuCtxDestroy(ctx);
        return 0;
    }
    if (!check_rc(api, "cuMemcpyDtoH", api->cuMemcpyDtoH(sample, device_mem, sizeof(sample)))) {
        api->cuMemFree(device_mem);
        api->cuCtxDestroy(ctx);
        return 0;
    }

    for (size_t i = 0; i < sizeof(sample) / sizeof(sample[0]); i++) {
        report->checksum += sample[i];
    }
    report->iterations = iterations;
    snprintf(report->details,
             sizeof(report->details),
             "profile_int32_fallback=OK iterations=%lu\n",
             iterations);

    api->cuMemFree(device_mem);
    api->cuCtxDestroy(ctx);
    return 1;
}

#if HAVE_CUBLASLT_HEADERS
typedef cublasStatus_t (*cublasLtCreate_fn)(cublasLtHandle_t *);
typedef cublasStatus_t (*cublasLtDestroy_fn)(cublasLtHandle_t);
typedef cublasStatus_t (*cublasLtMatmulDescCreate_fn)(cublasLtMatmulDesc_t *,
                                                      cublasComputeType_t,
                                                      cudaDataType_t);
typedef cublasStatus_t (*cublasLtMatmulDescDestroy_fn)(cublasLtMatmulDesc_t);
typedef cublasStatus_t (*cublasLtMatmulDescSetAttribute_fn)(cublasLtMatmulDesc_t,
                                                            cublasLtMatmulDescAttributes_t,
                                                            const void *,
                                                            size_t);
typedef cublasStatus_t (*cublasLtMatrixLayoutCreate_fn)(cublasLtMatrixLayout_t *,
                                                        cudaDataType_t,
                                                        uint64_t,
                                                        uint64_t,
                                                        int64_t);
typedef cublasStatus_t (*cublasLtMatrixLayoutDestroy_fn)(cublasLtMatrixLayout_t);
typedef cublasStatus_t (*cublasLtMatmulPreferenceCreate_fn)(cublasLtMatmulPreference_t *);
typedef cublasStatus_t (*cublasLtMatmulPreferenceDestroy_fn)(cublasLtMatmulPreference_t);
typedef cublasStatus_t (*cublasLtMatmulPreferenceSetAttribute_fn)(cublasLtMatmulPreference_t,
                                                                  cublasLtMatmulPreferenceAttributes_t,
                                                                  const void *,
                                                                  size_t);
typedef cublasStatus_t (*cublasLtMatmulAlgoGetHeuristic_fn)(
    cublasLtHandle_t,
    cublasLtMatmulDesc_t,
    cublasLtMatrixLayout_t,
    cublasLtMatrixLayout_t,
    cublasLtMatrixLayout_t,
    cublasLtMatrixLayout_t,
    cublasLtMatmulPreference_t,
    int,
    cublasLtMatmulHeuristicResult_t *,
    int *);
typedef cublasStatus_t (*cublasLtMatmul_fn)(cublasLtHandle_t,
                                            cublasLtMatmulDesc_t,
                                            const void *,
                                            const void *,
                                            cublasLtMatrixLayout_t,
                                            const void *,
                                            cublasLtMatrixLayout_t,
                                            const void *,
                                            const void *,
                                            cublasLtMatrixLayout_t,
                                            void *,
                                            cublasLtMatrixLayout_t,
                                            const cublasLtMatmulAlgo_t *,
                                            void *,
                                            size_t,
                                            cudaStream_t);

struct cublaslt_api {
    void *lib;
    cublasLtCreate_fn cublasLtCreate;
    cublasLtDestroy_fn cublasLtDestroy;
    cublasLtMatmulDescCreate_fn cublasLtMatmulDescCreate;
    cublasLtMatmulDescDestroy_fn cublasLtMatmulDescDestroy;
    cublasLtMatmulDescSetAttribute_fn cublasLtMatmulDescSetAttribute;
    cublasLtMatrixLayoutCreate_fn cublasLtMatrixLayoutCreate;
    cublasLtMatrixLayoutDestroy_fn cublasLtMatrixLayoutDestroy;
    cublasLtMatmulPreferenceCreate_fn cublasLtMatmulPreferenceCreate;
    cublasLtMatmulPreferenceDestroy_fn cublasLtMatmulPreferenceDestroy;
    cublasLtMatmulPreferenceSetAttribute_fn cublasLtMatmulPreferenceSetAttribute;
    cublasLtMatmulAlgoGetHeuristic_fn cublasLtMatmulAlgoGetHeuristic;
    cublasLtMatmul_fn cublasLtMatmul;
};

struct profile_desc {
    const char *name;
    const char *block_label;
    int min_cc;
    int enabled;
    int needs_scalar_scale;
    int needs_block_scale;
    int min_multiple;
    cudaDataType_t a_type;
    cudaDataType_t b_type;
    cudaDataType_t c_type;
    cudaDataType_t d_type;
    cublasComputeType_t compute_type;
};

struct prepared_profile {
    struct profile_desc desc;
    cublasLtMatmulDesc_t op_desc;
    cublasLtMatrixLayout_t a_layout;
    cublasLtMatrixLayout_t b_layout;
    cublasLtMatrixLayout_t c_layout;
    cublasLtMatrixLayout_t d_layout;
    cublasLtMatmulPreference_t preference;
    cublasLtMatmulHeuristicResult_t heuristic;
    CUdeviceptr a_dev;
    CUdeviceptr b_dev;
    CUdeviceptr c_dev;
    CUdeviceptr d_dev;
    CUdeviceptr a_scale_dev;
    CUdeviceptr b_scale_dev;
    CUdeviceptr workspace_dev;
    size_t workspace_size;
    uint64_t m;
    uint64_t n;
    uint64_t k;
    unsigned long iterations;
    int ready;
};

static const struct profile_desc k_profiles[] = {
    {
        "fp32_tf32",
        "fp32",
        80,
        1,
        0,
        0,
        128,
        CUDA_R_32F,
        CUDA_R_32F,
        CUDA_R_32F,
        CUDA_R_32F,
        CUBLAS_COMPUTE_32F_FAST_TF32,
    },
    {
        "fp16_tensor",
        "fp16",
        80,
        1,
        0,
        0,
        128,
        CUDA_R_16F,
        CUDA_R_16F,
        CUDA_R_16F,
        CUDA_R_16F,
        CUBLAS_COMPUTE_32F_FAST_16F,
    },
    {
        "fp8_e4m3",
        "fp8",
        89,
        1,
        1,
        0,
        128,
        CUDA_R_8F_E4M3,
        CUDA_R_8F_E4M3,
        CUDA_R_16BF,
        CUDA_R_16BF,
        CUBLAS_COMPUTE_32F,
    },
    {
        "fp8_e5m2",
        "fp8",
        89,
        1,
        1,
        0,
        128,
        CUDA_R_8F_E5M2,
        CUDA_R_8F_E5M2,
        CUDA_R_16BF,
        CUDA_R_16BF,
        CUBLAS_COMPUTE_32F,
    },
#if defined(CUDA_R_4F_E2M1) && defined(CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3)
    {
        "fp4_e2m1",
        "fp4",
        100,
        1,
        0,
        1,
        128,
        CUDA_R_4F_E2M1,
        CUDA_R_4F_E2M1,
        CUDA_R_16BF,
        CUDA_R_16BF,
        CUBLAS_COMPUTE_32F,
    },
#endif
};

static int load_cublaslt(struct cublaslt_api *api) {
    memset(api, 0, sizeof(*api));
    api->lib = dlopen("libcublasLt.so.13", RTLD_NOW | RTLD_LOCAL);
    if (!api->lib) {
        api->lib = dlopen("libcublasLt.so", RTLD_NOW | RTLD_LOCAL);
    }
    if (!api->lib) {
        return 0;
    }
    return
        load_symbol(api->lib, "cublasLtCreate", (void **)&api->cublasLtCreate) &&
        load_symbol(api->lib, "cublasLtDestroy", (void **)&api->cublasLtDestroy) &&
        load_symbol(api->lib, "cublasLtMatmulDescCreate", (void **)&api->cublasLtMatmulDescCreate) &&
        load_symbol(api->lib, "cublasLtMatmulDescDestroy", (void **)&api->cublasLtMatmulDescDestroy) &&
        load_symbol(api->lib,
                    "cublasLtMatmulDescSetAttribute",
                    (void **)&api->cublasLtMatmulDescSetAttribute) &&
        load_symbol(api->lib, "cublasLtMatrixLayoutCreate", (void **)&api->cublasLtMatrixLayoutCreate) &&
        load_symbol(api->lib, "cublasLtMatrixLayoutDestroy", (void **)&api->cublasLtMatrixLayoutDestroy) &&
        load_symbol(api->lib,
                    "cublasLtMatmulPreferenceCreate",
                    (void **)&api->cublasLtMatmulPreferenceCreate) &&
        load_symbol(api->lib,
                    "cublasLtMatmulPreferenceDestroy",
                    (void **)&api->cublasLtMatmulPreferenceDestroy) &&
        load_symbol(api->lib,
                    "cublasLtMatmulPreferenceSetAttribute",
                    (void **)&api->cublasLtMatmulPreferenceSetAttribute) &&
        load_symbol(api->lib,
                    "cublasLtMatmulAlgoGetHeuristic",
                    (void **)&api->cublasLtMatmulAlgoGetHeuristic) &&
        load_symbol(api->lib, "cublasLtMatmul", (void **)&api->cublasLtMatmul);
}

static const char *cublas_status_text(cublasStatus_t status) {
    switch (status) {
        case CUBLAS_STATUS_SUCCESS:
            return "CUBLAS_STATUS_SUCCESS";
        case CUBLAS_STATUS_NOT_INITIALIZED:
            return "CUBLAS_STATUS_NOT_INITIALIZED";
        case CUBLAS_STATUS_ALLOC_FAILED:
            return "CUBLAS_STATUS_ALLOC_FAILED";
        case CUBLAS_STATUS_INVALID_VALUE:
            return "CUBLAS_STATUS_INVALID_VALUE";
        case CUBLAS_STATUS_ARCH_MISMATCH:
            return "CUBLAS_STATUS_ARCH_MISMATCH";
        case CUBLAS_STATUS_MAPPING_ERROR:
            return "CUBLAS_STATUS_MAPPING_ERROR";
        case CUBLAS_STATUS_EXECUTION_FAILED:
            return "CUBLAS_STATUS_EXECUTION_FAILED";
        case CUBLAS_STATUS_INTERNAL_ERROR:
            return "CUBLAS_STATUS_INTERNAL_ERROR";
        case CUBLAS_STATUS_NOT_SUPPORTED:
            return "CUBLAS_STATUS_NOT_SUPPORTED";
        default:
            return "CUBLAS_STATUS_UNKNOWN";
    }
}

static int check_cublas(const char *step, cublasStatus_t status) {
    if (status == CUBLAS_STATUS_SUCCESS) {
        return 1;
    }
    fprintf(stderr, "%s failed: %s (%d)\n", step, cublas_status_text(status), (int)status);
    return 0;
}

static size_t bytes_for_elements(cudaDataType_t type, uint64_t elements) {
    switch (type) {
        case CUDA_R_32F:
            return (size_t)(elements * 4u);
        case CUDA_R_16F:
        case CUDA_R_16BF:
            return (size_t)(elements * 2u);
        case CUDA_R_8F_E4M3:
        case CUDA_R_8F_E5M2:
            return (size_t)(elements);
#if defined(CUDA_R_4F_E2M1)
        case CUDA_R_4F_E2M1:
            return (size_t)((elements + 1u) / 2u);
#endif
        default:
            return (size_t)(elements * 4u);
    }
}

static size_t fp4_scale_bytes(uint64_t rows, uint64_t cols) {
    uint64_t row_tiles = (rows + 127u) / 128u;
    uint64_t col_tiles = (cols + 63u) / 64u;
    return (size_t)(row_tiles * col_tiles * 128u);
}

static uint64_t choose_square_dim(size_t budget_bytes, size_t bytes_per_cell, int multiple) {
    double approx = sqrt((double)budget_bytes / (double)bytes_per_cell);
    uint64_t dim = (uint64_t)approx;
    if (dim < (uint64_t)multiple) {
        dim = (uint64_t)multiple;
    }
    dim = (uint64_t)round_down_size((size_t)dim, (size_t)multiple);
    if (dim < (uint64_t)multiple) {
        dim = (uint64_t)multiple;
    }
    if (dim > 8192u) {
        dim = 8192u;
    }
    return dim;
}

static int device_upload(struct cuda_api *cuda, CUdeviceptr dev, const void *src, size_t bytes) {
    return check_rc(cuda, "cuMemcpyHtoD", cuda->cuMemcpyHtoD(dev, src, bytes));
}

static int alloc_filled(struct cuda_api *cuda, CUdeviceptr *ptr, size_t bytes, unsigned char pattern) {
    if (!check_rc(cuda, "cuMemAlloc", cuda->cuMemAlloc(ptr, bytes))) {
        return 0;
    }
    if (!check_rc(cuda, "cuMemsetD8", cuda->cuMemsetD8(*ptr, pattern, bytes))) {
        cuda->cuMemFree(*ptr);
        *ptr = 0;
        return 0;
    }
    return 1;
}

static size_t profile_scale_bytes(const struct profile_desc *desc, uint64_t m, uint64_t n, uint64_t k) {
    size_t bytes = 0;
    if (desc->needs_scalar_scale) {
        bytes += 2u * sizeof(float);
    }
#if defined(CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3)
    if (desc->needs_block_scale) {
        bytes += fp4_scale_bytes(k, m);
        bytes += fp4_scale_bytes(k, n);
    }
#else
    (void)m;
    (void)n;
    (void)k;
#endif
    return bytes;
}

static void destroy_profile(struct cublaslt_api *cublas, struct cuda_api *cuda, struct prepared_profile *profile) {
    if (profile->workspace_dev) {
        cuda->cuMemFree(profile->workspace_dev);
    }
    if (profile->a_scale_dev) {
        cuda->cuMemFree(profile->a_scale_dev);
    }
    if (profile->b_scale_dev) {
        cuda->cuMemFree(profile->b_scale_dev);
    }
    if (profile->d_dev) {
        cuda->cuMemFree(profile->d_dev);
    }
    if (profile->c_dev) {
        cuda->cuMemFree(profile->c_dev);
    }
    if (profile->b_dev) {
        cuda->cuMemFree(profile->b_dev);
    }
    if (profile->a_dev) {
        cuda->cuMemFree(profile->a_dev);
    }
    if (profile->preference) {
        cublas->cublasLtMatmulPreferenceDestroy(profile->preference);
    }
    if (profile->d_layout) {
        cublas->cublasLtMatrixLayoutDestroy(profile->d_layout);
    }
    if (profile->c_layout) {
        cublas->cublasLtMatrixLayoutDestroy(profile->c_layout);
    }
    if (profile->b_layout) {
        cublas->cublasLtMatrixLayoutDestroy(profile->b_layout);
    }
    if (profile->a_layout) {
        cublas->cublasLtMatrixLayoutDestroy(profile->a_layout);
    }
    if (profile->op_desc) {
        cublas->cublasLtMatmulDescDestroy(profile->op_desc);
    }
    memset(profile, 0, sizeof(*profile));
}

static int prepare_profile(struct cublaslt_api *cublas,
                           cublasLtHandle_t handle,
                           struct cuda_api *cuda,
                           const struct profile_desc *desc,
                           size_t profile_budget_bytes,
                           struct prepared_profile *out) {
    memset(out, 0, sizeof(*out));
    out->desc = *desc;

    size_t bytes_per_cell = 0;
    bytes_per_cell += bytes_for_elements(desc->a_type, 1);
    bytes_per_cell += bytes_for_elements(desc->b_type, 1);
    bytes_per_cell += bytes_for_elements(desc->c_type, 1);
    bytes_per_cell += bytes_for_elements(desc->d_type, 1);
    if (bytes_per_cell == 0) {
        return 0;
    }

    uint64_t dim = choose_square_dim(profile_budget_bytes, bytes_per_cell, desc->min_multiple);
    out->m = dim;
    out->n = dim;
    out->k = dim;

    size_t desired_workspace = profile_budget_bytes / 8u;
    if (desired_workspace > 32u * 1024u * 1024u) {
        desired_workspace = 32u * 1024u * 1024u;
    }
    desired_workspace = round_down_size(desired_workspace, 256u);

    size_t a_bytes = 0;
    size_t b_bytes = 0;
    size_t c_bytes = 0;
    size_t d_bytes = 0;
    size_t scale_bytes = 0;
    while (1) {
        a_bytes = bytes_for_elements(desc->a_type, out->k * out->m);
        b_bytes = bytes_for_elements(desc->b_type, out->k * out->n);
        c_bytes = bytes_for_elements(desc->c_type, out->m * out->n);
        d_bytes = bytes_for_elements(desc->d_type, out->m * out->n);
        scale_bytes = profile_scale_bytes(desc, out->m, out->n, out->k);

        size_t matrix_bytes = a_bytes + b_bytes + c_bytes + d_bytes + scale_bytes;
        if (matrix_bytes <= profile_budget_bytes) {
            size_t remaining = profile_budget_bytes - matrix_bytes;
            out->workspace_size = desired_workspace;
            if (out->workspace_size > remaining) {
                out->workspace_size = round_down_size(remaining, 256u);
            }
            break;
        }

        if (out->m <= (uint64_t)desc->min_multiple) {
            return 0;
        }
        out->m -= (uint64_t)desc->min_multiple;
        out->n = out->m;
        out->k = out->m;
    }

    if (!alloc_filled(cuda, &out->a_dev, a_bytes, 0x11) ||
        !alloc_filled(cuda, &out->b_dev, b_bytes, 0x11) ||
        !alloc_filled(cuda, &out->c_dev, c_bytes, 0x00) ||
        !alloc_filled(cuda, &out->d_dev, d_bytes, 0x00)) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    if (!check_cublas("cublasLtMatmulDescCreate",
                      cublas->cublasLtMatmulDescCreate(&out->op_desc, desc->compute_type, CUDA_R_32F))) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    cublasOperation_t transa = CUBLAS_OP_T;
    cublasOperation_t transb = CUBLAS_OP_N;
    if (!check_cublas("set TRANSA",
                      cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                             CUBLASLT_MATMUL_DESC_TRANSA,
                                                             &transa,
                                                             sizeof(transa))) ||
        !check_cublas("set TRANSB",
                      cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                             CUBLASLT_MATMUL_DESC_TRANSB,
                                                             &transb,
                                                             sizeof(transb)))) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    if (desc->needs_scalar_scale) {
        float one = 1.0f;
        if (!alloc_filled(cuda, &out->a_scale_dev, sizeof(one), 0x00) ||
            !alloc_filled(cuda, &out->b_scale_dev, sizeof(one), 0x00)) {
            destroy_profile(cublas, cuda, out);
            return 0;
        }
        if (!device_upload(cuda, out->a_scale_dev, &one, sizeof(one)) ||
            !device_upload(cuda, out->b_scale_dev, &one, sizeof(one))) {
            destroy_profile(cublas, cuda, out);
            return 0;
        }
        void *a_scale_ptr = (void *)(uintptr_t)out->a_scale_dev;
        void *b_scale_ptr = (void *)(uintptr_t)out->b_scale_dev;
        if (!check_cublas("set A scale ptr",
                          cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                                 CUBLASLT_MATMUL_DESC_A_SCALE_POINTER,
                                                                 &a_scale_ptr,
                                                                 sizeof(a_scale_ptr))) ||
            !check_cublas("set B scale ptr",
                          cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                                 CUBLASLT_MATMUL_DESC_B_SCALE_POINTER,
                                                                 &b_scale_ptr,
                                                                 sizeof(b_scale_ptr)))) {
            destroy_profile(cublas, cuda, out);
            return 0;
        }
    }

#if defined(CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3)
    if (desc->needs_block_scale) {
        size_t a_scale_bytes = fp4_scale_bytes(out->k, out->m);
        size_t b_scale_bytes = fp4_scale_bytes(out->k, out->n);
        if (!alloc_filled(cuda, &out->a_scale_dev, a_scale_bytes, 0x11) ||
            !alloc_filled(cuda, &out->b_scale_dev, b_scale_bytes, 0x11)) {
            destroy_profile(cublas, cuda, out);
            return 0;
        }
        cublasLtMatmulMatrixScale_t scale_mode = CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3;
        void *a_scale_ptr = (void *)(uintptr_t)out->a_scale_dev;
        void *b_scale_ptr = (void *)(uintptr_t)out->b_scale_dev;
        if (!check_cublas("set A scale mode",
                          cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                                 CUBLASLT_MATMUL_DESC_A_SCALE_MODE,
                                                                 &scale_mode,
                                                                 sizeof(scale_mode))) ||
            !check_cublas("set B scale mode",
                          cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                                 CUBLASLT_MATMUL_DESC_B_SCALE_MODE,
                                                                 &scale_mode,
                                                                 sizeof(scale_mode))) ||
            !check_cublas("set A block scale ptr",
                          cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                                 CUBLASLT_MATMUL_DESC_A_SCALE_POINTER,
                                                                 &a_scale_ptr,
                                                                 sizeof(a_scale_ptr))) ||
            !check_cublas("set B block scale ptr",
                          cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
                                                                 CUBLASLT_MATMUL_DESC_B_SCALE_POINTER,
                                                                 &b_scale_ptr,
                                                                 sizeof(b_scale_ptr)))) {
            destroy_profile(cublas, cuda, out);
            return 0;
        }
    }
#endif

    if (!check_cublas("create A layout",
                      cublas->cublasLtMatrixLayoutCreate(&out->a_layout, desc->a_type, out->k, out->m, out->k)) ||
        !check_cublas("create B layout",
                      cublas->cublasLtMatrixLayoutCreate(&out->b_layout, desc->b_type, out->k, out->n, out->k)) ||
        !check_cublas("create C layout",
                      cublas->cublasLtMatrixLayoutCreate(&out->c_layout, desc->c_type, out->m, out->n, out->m)) ||
        !check_cublas("create D layout",
                      cublas->cublasLtMatrixLayoutCreate(&out->d_layout, desc->d_type, out->m, out->n, out->m))) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    if (!check_cublas("create preference", cublas->cublasLtMatmulPreferenceCreate(&out->preference))) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    if (out->workspace_size > 0) {
        if (!alloc_filled(cuda, &out->workspace_dev, out->workspace_size, 0x00)) {
            destroy_profile(cublas, cuda, out);
            return 0;
        }
    }

    if (!check_cublas("set workspace",
                      cublas->cublasLtMatmulPreferenceSetAttribute(
                          out->preference,
                          CUBLASLT_MATMUL_PREF_MAX_WORKSPACE_BYTES,
                          &out->workspace_size,
                          sizeof(out->workspace_size)))) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    int found = 0;
    if (!check_cublas("heuristic",
                      cublas->cublasLtMatmulAlgoGetHeuristic(handle,
                                                             out->op_desc,
                                                             out->a_layout,
                                                             out->b_layout,
                                                             out->c_layout,
                                                             out->d_layout,
                                                             out->preference,
                                                             1,
                                                             &out->heuristic,
                                                             &found))) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }
    if (found <= 0) {
        destroy_profile(cublas, cuda, out);
        return 0;
    }

    out->ready = 1;
    return 1;
}

static int run_cublas_profile(cublasLtHandle_t handle,
                              struct cublaslt_api *cublas,
                              struct prepared_profile *profile) {
    float alpha = 1.0f;
    float beta = 0.0f;
    return check_cublas(profile->desc.name,
                        cublas->cublasLtMatmul(handle,
                                               profile->op_desc,
                                               &alpha,
                                               (const void *)(uintptr_t)profile->a_dev,
                                               profile->a_layout,
                                               (const void *)(uintptr_t)profile->b_dev,
                                               profile->b_layout,
                                               &beta,
                                               (const void *)(uintptr_t)profile->c_dev,
                                               profile->c_layout,
                                               (void *)(uintptr_t)profile->d_dev,
                                               profile->d_layout,
                                               &profile->heuristic.algo,
                                               (void *)(uintptr_t)profile->workspace_dev,
                                               profile->workspace_size,
                                               (cudaStream_t)0));
}

static int run_cublaslt_stress(struct cuda_api *cuda,
                               CUdevice dev,
                               const char *device_name,
                               int cc_major,
                               int cc_minor,
                               int seconds,
                               int size_mb,
                               struct stress_report *report) {
    struct cublaslt_api cublas;
    struct prepared_profile prepared[sizeof(k_profiles) / sizeof(k_profiles[0])];
    cublasLtHandle_t handle = NULL;
    CUcontext ctx = NULL;
    uint16_t sample[256];
    int cc = cc_major * 10 + cc_minor;
    int planned = 0;
    int active = 0;

    memset(report, 0, sizeof(*report));
    snprintf(report->backend, sizeof(report->backend), "cublasLt");
    snprintf(report->device, sizeof(report->device), "%s", device_name);
    report->cc_major = cc_major;
    report->cc_minor = cc_minor;
    report->buffer_mb = size_mb;

    if (!load_cublaslt(&cublas)) {
        snprintf(report->details, sizeof(report->details), "cublasLt=unavailable\n");
        return 0;
    }
    if (!check_rc(cuda, "cuCtxCreate", cuda->cuCtxCreate(&ctx, 0, dev))) {
        return 0;
    }
    if (!check_cublas("cublasLtCreate", cublas.cublasLtCreate(&handle))) {
        cuda->cuCtxDestroy(ctx);
        return 0;
    }

    for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
        if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc) {
            planned++;
        }
    }
    if (planned <= 0) {
        snprintf(report->details, sizeof(report->details), "cublasLt_profiles=unsupported\n");
        cublas.cublasLtDestroy(handle);
        cuda->cuCtxDestroy(ctx);
        return 0;
    }

    size_t total_budget = (size_t)size_mb * 1024u * 1024u;
    if (total_budget < (size_t)planned * 4u * 1024u * 1024u) {
        total_budget = (size_t)planned * 4u * 1024u * 1024u;
    }
    size_t per_profile_budget = total_budget / (size_t)planned;
    if (per_profile_budget < 4u * 1024u * 1024u) {
        per_profile_budget = 4u * 1024u * 1024u;
    }

    for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
        const struct profile_desc *desc = &k_profiles[i];
        if (!(desc->enabled && cc >= desc->min_cc)) {
            append_detail(report->details,
                          sizeof(report->details),
                          "%s=SKIPPED cc<%d\n",
                          desc->name,
                          desc->min_cc);
            continue;
        }
        if (prepare_profile(&cublas, handle, cuda, desc, per_profile_budget, &prepared[i])) {
            active++;
            append_detail(report->details,
                          sizeof(report->details),
                          "%s=READY dim=%llux%llux%llu block=%s\n",
                          desc->name,
                          (unsigned long long)prepared[i].m,
                          (unsigned long long)prepared[i].n,
                          (unsigned long long)prepared[i].k,
                          desc->block_label);
        } else {
            append_detail(report->details, sizeof(report->details), "%s=SKIPPED unsupported\n", desc->name);
        }
    }

    if (active <= 0) {
        cublas.cublasLtDestroy(handle);
        cuda->cuCtxDestroy(ctx);
        return 0;
    }

    double deadline = now_seconds() + (double)seconds;
    while (now_seconds() < deadline) {
        for (size_t i = 0; i < sizeof(prepared) / sizeof(prepared[0]); i++) {
            if (!prepared[i].ready) {
                continue;
            }
            if (!run_cublas_profile(handle, &cublas, &prepared[i])) {
                append_detail(report->details,
                              sizeof(report->details),
                              "%s=FAILED runtime\n",
                              prepared[i].desc.name);
                for (size_t j = 0; j < sizeof(prepared) / sizeof(prepared[0]); j++) {
                    destroy_profile(&cublas, cuda, &prepared[j]);
                }
                cublas.cublasLtDestroy(handle);
                cuda->cuCtxDestroy(ctx);
                return 0;
            }
            prepared[i].iterations++;
            report->iterations++;
            if (now_seconds() >= deadline) {
                break;
            }
        }
    }

    if (!check_rc(cuda, "cuCtxSynchronize", cuda->cuCtxSynchronize())) {
        for (size_t i = 0; i < sizeof(prepared) / sizeof(prepared[0]); i++) {
            destroy_profile(&cublas, cuda, &prepared[i]);
        }
        cublas.cublasLtDestroy(handle);
        cuda->cuCtxDestroy(ctx);
        return 0;
    }

    for (size_t i = 0; i < sizeof(prepared) / sizeof(prepared[0]); i++) {
        if (!prepared[i].ready) {
            continue;
        }
        append_detail(report->details,
                      sizeof(report->details),
                      "%s_iterations=%lu\n",
                      prepared[i].desc.name,
                      prepared[i].iterations);
    }

    for (size_t i = 0; i < sizeof(prepared) / sizeof(prepared[0]); i++) {
        if (prepared[i].ready) {
            if (check_rc(cuda, "cuMemcpyDtoH", cuda->cuMemcpyDtoH(sample, prepared[i].d_dev, sizeof(sample)))) {
                for (size_t j = 0; j < sizeof(sample) / sizeof(sample[0]); j++) {
                    report->checksum += sample[j];
                }
            }
            break;
        }
    }

    for (size_t i = 0; i < sizeof(prepared) / sizeof(prepared[0]); i++) {
        destroy_profile(&cublas, cuda, &prepared[i]);
    }
    cublas.cublasLtDestroy(handle);
    cuda->cuCtxDestroy(ctx);
    return 1;
}
#endif

int main(int argc, char **argv) {
    int seconds = 5;
    int size_mb = 64;
    for (int i = 1; i < argc; i++) {
        if ((strcmp(argv[i], "--seconds") == 0 || strcmp(argv[i], "-t") == 0) && i + 1 < argc) {
            seconds = atoi(argv[++i]);
        } else if ((strcmp(argv[i], "--size-mb") == 0 || strcmp(argv[i], "-m") == 0) && i + 1 < argc) {
            size_mb = atoi(argv[++i]);
        } else {
            fprintf(stderr, "usage: %s [--seconds N] [--size-mb N]\n", argv[0]);
            return 2;
        }
    }
    if (seconds <= 0) {
        seconds = 5;
    }
    if (size_mb <= 0) {
        size_mb = 64;
    }

    struct cuda_api cuda;
    if (!load_cuda(&cuda)) {
        fprintf(stderr, "failed to load libcuda.so.1 or required Driver API symbols\n");
        return 1;
    }
    load_symbol(cuda.lib, "cuGetErrorName", (void **)&cuda.cuGetErrorName);
    load_symbol(cuda.lib, "cuGetErrorString", (void **)&cuda.cuGetErrorString);

    if (!check_rc(&cuda, "cuInit", cuda.cuInit(0))) {
        return 1;
    }

    int count = 0;
    if (!check_rc(&cuda, "cuDeviceGetCount", cuda.cuDeviceGetCount(&count))) {
        return 1;
    }
    if (count <= 0) {
        fprintf(stderr, "no CUDA devices found\n");
        return 1;
    }

    CUdevice dev = 0;
    if (!check_rc(&cuda, "cuDeviceGet", cuda.cuDeviceGet(&dev, 0))) {
        return 1;
    }

    char name[128] = {0};
    if (!check_rc(&cuda, "cuDeviceGetName", cuda.cuDeviceGetName(name, (int)sizeof(name), dev))) {
        return 1;
    }

    int cc_major = 0;
    int cc_minor = 0;
    if (!query_compute_capability(&cuda, dev, &cc_major, &cc_minor)) {
        return 1;
    }

    struct stress_report report;
    int ok = 0;

#if HAVE_CUBLASLT_HEADERS
    ok = run_cublaslt_stress(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, &report);
#endif
    if (!ok) {
        if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, &report)) {
            return 1;
        }
    }

    printf("device=%s\n", report.device);
    printf("compute_capability=%d.%d\n", report.cc_major, report.cc_minor);
    printf("backend=%s\n", report.backend);
    printf("duration_s=%d\n", seconds);
    printf("buffer_mb=%d\n", report.buffer_mb);
    printf("iterations=%lu\n", report.iterations);
    printf("checksum=%llu\n", (unsigned long long)report.checksum);
    if (report.details[0] != '\0') {
        printf("%s", report.details);
    }
    printf("status=OK\n");
    return 0;
}