Are cuda kernel calls synchronous or asynchronous

by

Kernel calls are asynchronous from the point of view of the CPU so if you call 2 kernels in succession the second one will be called without waiting for the first one to finish. It only means that the control returns to the CPU immediately.

On the GPU side, if you haven’t specified different streams to execute the kernel they will be executed by the order they were called (if you don’t specify a stream they both go to the default stream and are executed serially). Only after the first kernel is finished the second one will execute.

This behavior is valid for devices with compute capability 2.x which support concurrent kernel execution. On the other devices even though kernel calls are still asynchronous the kernel execution is always sequential.

Check the CUDA C programming guide on section 3.2.5 which every CUDA programmer should read.

More Related Contents:

  1. How do I choose grid and block dimensions for CUDA kernels?
  2. Error Message : Cannot find or open the PDB file
  3. What is the correct version of CUDA for my nvidia driver?
  4. How is CUDA memory managed?
  5. How to measure the inner kernel time in NVIDIA CUDA?
  6. How do CUDA blocks/warps/threads map onto CUDA cores?
  7. Understanding CUDA grid dimensions, block dimensions and threads organization (simple explanation) [closed]
  8. What can I do against ‘CUDA driver version is insufficient for CUDA runtime version’?
  9. What is a bank conflict? (Doing Cuda/OpenCL programming)
  10. nvidia-smi Volatile GPU-Utilization explanation?
  11. 128 bit integer on cuda?
  12. How do I use Nvidia Multi-process Service (MPS) to run multiple non-MPI CUDA applications?
  13. Cuda kernel returning vectors
  14. Why is NVIDIA Pascal GPUs slow on running CUDA Kernels when using cudaMallocManaged
  15. How do I select which GPU to run a job on?
  16. How can I make tensorflow run on a GPU with capability 2.x?
  17. why do we need cudaDeviceSynchronize(); in kernels with device-printf?
  18. CUDA determining threads per block, blocks per grid
  19. How does CUDA assign device IDs to GPUs?
  20. Using Java with Nvidia GPUs (CUDA)
  21. Thrust inside user written kernels
  22. Structure of Arrays vs Array of Structures
  23. Can anyone provide sample code demonstrating the use of 16 bit floating point in cuda?
  24. CUDA: How many concurrent threads in total?
  25. multi-GPU basic usage
  26. Reset Cuda Context after exception
  27. In a CUDA kernel, how do I store an array in “local thread memory”?
  28. How to implement device side CUDA virtual functions?
  29. How to profile PyCuda code with the Visual Profiler?
  30. Installing theano on Windows 8 with GPU enabled

Leave a Comment