When I read the nbody code in Cuda-SDK, I went through some lines in the code and I found that it is a little bit different than their paper in GPUGems3 "Fast N-Body Simulation with CUDA".

My questions are: First, why the blockIdx.x is still involved in loading memory from global to share memory as written in the following code?

for (int tile = blockIdx.y; tile < numTiles + blockIdx.y; tile++)
{
    sharedPos[threadIdx.x+blockDim.x*threadIdx.y] =
        multithreadBodies ?
        positions[WRAP(blockIdx.x + q * tile + threadIdx.y, gridDim.x) * p + threadIdx.x] : //this line
        positions[WRAP(blockIdx.x + tile,                   gridDim.x) * p + threadIdx.x];  //this line

    __syncthreads();

    // This is the "tile_calculation" function from the GPUG3 article.
    acc = gravitation(bodyPos, acc);

    __syncthreads();
}

isn't it supposed to be like this according to paper? I wonder why

    sharedPos[threadIdx.x+blockDim.x*threadIdx.y] =
        multithreadBodies ?
        positions[WRAP(q * tile + threadIdx.y, gridDim.x) * p + threadIdx.x] :
        positions[WRAP(tile,                   gridDim.x) * p + threadIdx.x];

Second, in the multiple threads per body why the threadIdx.x is still involved? Isn't it supposed to be a fix value or not involving at all because the sum only due to threadIdx.y

if (multithreadBodies)
{
    SX_SUM(threadIdx.x, threadIdx.y).x = acc.x; //this line
    SX_SUM(threadIdx.x, threadIdx.y).y = acc.y; //this line
    SX_SUM(threadIdx.x, threadIdx.y).z = acc.z; //this line

    __syncthreads();

    // Save the result in global memory for the integration step
    if (threadIdx.y == 0)
    {
        for (int i = 1; i < blockDim.y; i++)
        {
            acc.x += SX_SUM(threadIdx.x,i).x; //this line
            acc.y += SX_SUM(threadIdx.x,i).y; //this line
            acc.z += SX_SUM(threadIdx.x,i).z; //this line
        }
    }
}

Can anyone explain this to me? Is it some kind of optimization for faster code?