CUDA Kernel 最佳实践

Memory Access Patterns

1. Coalesced Access (Global Memory)

Ensure that global memory accesses by threads within a warp are coalesced.

2. Shared Memory Usage

3. Avoid Bank Conflicts

When using shared memory, ensure that bank conflicts are minimized. Bank conflicts occur when multiple threads access the same memory bank simultaneously.

Thread Organization

1. Select Appropriate Block Size

2. Occupancy Considerations

High occupancy (the ratio of active warps to the maximum number of warps supported by a multiprocessor) may help hide latency of memory accesses.

3. Load Balancing

Ensure that the workload is evenly distributed across threads and blocks to prevent some threads from being idle while others are still processing. This can be achieved by designing kernel grids and blocks that match the problem’s dimension.

Minimizing Bottlenecks

1. Avoid Branch Divergence

Ensure that threads within the same warp follow the same execution path.

2. Use Asynchronous Memory Transfers

Utilize asynchronous memory transfers between host and device to overlap data transfer and computation. This can be achieved with CUDA streams.

3. Hardware Utilization

Fully utilize the computational resources of the GPU. Ensure that a sufficient number of threads are launched to fully load the GPU’s cores.