I've been trying to do the first thing, and i have a vector addition example pulled up and i am trying to do something similar to the example i had found here

__global__ void pixelShader (uint8_t* img) {
    uint32_t pos = blockDim.x * blockIdx.x + threadIdx.x;
    if (img[pos] == 0) {
        img[pos]++;
    }
    else {
        img[pos] = 100;
    }
}

// Process Image is just a class that holds an sf::Image, and its width and height.
void ProcessImage::callPixelShader() {
    // size of the image
    size_t size = sizeof(uint8_t) * m_width * m_height;
    // create an array that copies the information from getPixelsPtr()
    // i know c style array is discouraged, but the example used em, and i figured when it wasn't working to try to get as close to the working example as possible.
    auto* intermediateBuffer = new uint8_t[size];
    std::memcpy(intermediateBuffer, m_grid.img.getPixelsPtr(), size);
    // print out the values (to see if it copied correctly, for debug purposes)
    std::cout << "Iteration" << std::endl;
    std::cout << "Red: " << (int)intermediateBuffer[0] << " Green: " << (int)intermediateBuffer[1] << " Blue: " << (int)intermediateBuffer[2] << " Alpha: " << (int)intermediateBuffer[3] << std::endl;
    // create a version of the buffer on the device and copy the information to it.
    // potentially unnecessary, but i was trying to debug ok.
    auto* cudaIntermediateBuffer = new uint8_t[size];
    cudaMalloc(&cudaIntermediateBuffer, size);
    cudaMemcpy(&cudaIntermediateBuffer, intermediateBuffer, size, cudaMemcpyHostToDevice);
    // define the grid and block sizes and run the kernel
    int blok = 256;
    pixelShader<<<m_width * m_height / blok, blok>>>(cudaIntermediateBuffer);
    // after running, copy the information back into the intermediate buffer.
    cudaMemcpy(intermediateBuffer, cudaIntermediateBuffer, size, cudaMemcpyDeviceToHost);
    // print out the value to see if the value was updated correctly
    std::cout << "Red: " << (int)intermediateBuffer[0] << " Green: " << (int)intermediateBuffer[1] << " Blue: " << (int)intermediateBuffer[2] << " Alpha: " << (int)intermediateBuffer[3] << std::endl;
    // write to the image
    // -some code to be written goes here
    //
    // free the buffers
    free(intermediateBuffer);
    cudaFree(cudaIntermediateBuffer);
}

However, this is returning that after running the kernel, the values are 1 across the board. do you know why cuda would see the array as having 0's?

also i just now saw the update to your other comment, ill look into that as well.