decuda 0.1.1

CUDA to HIP, SYCL, OpenCL, and Rust GPU migration tool — automatic source-code translator for porting CUDA C++ kernels to AMD ROCm HIP, Intel oneAPI SYCL, Khronos OpenCL, and Rust GPU (cust / rust-gpu)
Documentation 
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// Generated by decuda. Edit with care.
// HIP is mostly source-compatible with CUDA at the kernel level.
// Compare against the original .cu file for sanity.

// Complex fixture: __device__ helper functions, __forceinline__ / __noinline__,
// __constant__ memory, warp intrinsics, and a __launch_bounds__ hint.
//
// Exercises:
//   - __device__ helper functions (one __forceinline__, one __noinline__)
//   - __constant__ memory arrays
//   - __launch_bounds__ (flagged in the report, not auto-translated)
//   - __laneid, __syncwarp, __syncthreads
//   - threadIdx / blockIdx / blockDim
//   - cudaMalloc / cudaFree / cudaMemcpy
//   - device_functions.h and cuda_runtime.h headers
#include <hip/hip_runtime.h> /* was: cuda_runtime.h */
#include <hip/device_functions.h> /* was: device_functions.h */

#define WARP 32

__constant__ float c_scale[4];

__device__ __forceinline__ float fast_scale(float v, int idx) {
    return v * c_scale[idx & 3];
}

__device__ __noinline__ float slow_path(float v) {
    if (v < 0.0f) return 0.0f;
    return __sinf(v);
}

__launch_bounds__(256, 2)
__global__ void apply(const float* in, float* out, int n) {
    int i = blockIdx.x * blockDim.x + threadIdx.x;
    if (i < n) {
        float v = fast_scale(in[i], i);
        out[i] = slow_path(v);
    }
}

__global__ void warp_sum(const float* in, float* out, int n) {
    int lane = __laneid()();
    float v = (threadIdx.x < n) ? in[threadIdx.x] : 0.0f;
    __syncwarp(0xFFFFFFFFu);
    // In-warp sum via shared memory.
    __shared__ float partial[WARP];
    partial[lane] = v;
    __syncthreads();
    if (lane == 0) {
        float s = 0.0f;
        for (int i = 0; i < WARP; ++i) s += partial[i];
        out[blockIdx.x] = s;
    }
}

int main(void) {
    const int N = 1 << 18;
    float* d_in = nullptr;
    float* d_out = nullptr;
    float* d_warp = nullptr;

    hipMalloc((void**)&d_in, N * sizeof(float));
    hipMalloc((void**)&d_out, N * sizeof(float));
    hipMalloc((void**)&d_warp, (N / WARP) * sizeof(float));

    float scale_init[4] = {1.0f, 2.0f, 3.0f, 4.0f};
    hipMemcpyToSymbol(c_scale, scale_init, sizeof(scale_init));

    dim3 grid(N / 256);
    dim3 block(256);
    hipLaunchKernelGGL(apply, dim3(grid), dim3(block), 0, 0, d_in, d_out, N);
    hipLaunchKernelGGL(warp_sum, dim3(N / WARP), dim3(WARP), 0, 0, d_in, d_warp, N);

    hipDeviceSynchronize();
    hipFree(d_in);
    hipFree(d_out);
    hipFree(d_warp);
    return 0;
}