Computational Science Community Wiki

Differences between revisions 14 and 15
Revision 14 as of 2011-07-06 21:34:35
Size: 2867
Editor: MichaelBane
Comment:
Revision 15 as of 2011-07-07 12:59:51
Size: 2950
Editor: BenSattelle
Comment:
Deletions are marked like this. Additions are marked like this.
Line 42: Line 42:
  i. On the [[../HectorGpu|HECToR GPU Testbed]] all NVidia GPUs are in Default compute mode (checked on 10 June 2011)   i. On the [[../HectorGpu|HECToR GPU Testbed]] all NVidia GPUs are now in Exclusive Process Mode (many threads in one process is able to use cudaSetDevice() with this device) - checked on 7 July 2011

University of Manchester GPU FAQ


alt="NVIDIA CUDA Research Centre"

  • Software for GPUs inc. compiler/directives, maths libs & tools (debuggers and profilers)


Please login and add your own questions or solutions

Performance

  • Q: how do I get max performance from NVIDIA cards?
    1. A: you need to use pinned memory and asynchronous comms
  • Q: how do I profile my GPU codes?
    1. SDK solution:
    2. add calls to clock() but beware asynchronicity

  • Q: how do I determine the amount of memory actually used by the GPU?
    1. CUDA Driver API has cuMemGetInfo and there is a CLI command cuda-memcheck

  • Q: how do I debug my GPU codes?
    1. CUDA SDK has cuda-gdb
  • Q: how can I tell if my NVIDIA card is running in exclusive mode or not?
    1. A: load the SDK and run deviceQuery and examine the computeMode output

  • Q: what does the computeMode output mean on NVIDIA cards?

    1. CUDA 4.0 has 4 compute modes
      • Default: Multiple host threads can use the device
      • Exclusive-process: Only one CUDA context may be created on the device across all processes in the system and that context may be current to as many threads as desired within the process that created that context.
      • Exclusive-process-and-thread: Only one CUDA context may be created on the device across all processes in the system and that context may only be current to one thread at a time.
      • Prohibited: No CUDA context can be created on the device.
    2. CUDA 3 has 3 compute nodes
      • Default - same as CUDA 4.0
      • Exclusive - only one host thread to use device at any given time.
      • Prohibited - same as CUDA 4.0
  • Q: how can I (and only me) run on a GPU card?
    1. There's two ways of setting this up on NVIDIA cards
      1. set your card to be in exclusive mode (see above); OR

      2. grab a whole node (using, eg, qsub -pe mpich 4 if 4 slots per node) AND explicitly select each GPU (eg from your CUDA or OpenCL context) if using more than one card otherwise the kernels all run on same card

    2. The HECToR GPU testbed consists of 4 nodes, each with multiple GPUs (see here). Therefore it is important to consider how programs running on the same node share these nodes, which is controlled by the compute modes.

    3. For more information see section 3.6 in the NVIDIA CUDA C Programming Guide

    4. On the HECToR GPU Testbed all NVidia GPUs are now in Exclusive Process Mode (many threads in one process is able to use cudaSetDevice() with this device) - checked on 7 July 2011

  • Q: What about exclusive use of AMD cards?
    1. they don't have different modes

Accessing GPU Resources

  • Q: how do I use the GPU testbed on HECToR?
    1. A: Accessing and running; contact us <its-research@manchester.ac.uk> if you'd like trial access