Computational Science Community Wiki

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== On Campus ==

GPUs: What are they?

Graphical Processing Units (GPUs) used to be for processing graphics for computer screens. Much of these processing was able to be carried out concurrently on small amounts of data. GPUs thus became capable of carrying out the same operations on different data at the same time - a known parallel processing pattern (the SIMD model). The jump was made to using the compute capability of GPUs to carry out not just processing of graphical information but of the main computation itself. This is what is currently know as GPGPU (general purpose GPU) programming, more commonly known now as just GPU programming.

What's Available?

Various vendors have product lines suitable for general purpose computing. Here's just a brief summary. Feel free to add and amend.

    • Fermi is an architecture designation (a follow on from the G80 and then GT200, sporting 128 and 240 stream processors): 512 stream processors, optional ECC, 2:1 DP support (vs. 8:1 for GT200)

    • Relevant NVIDIA product lines:
      • Tesla - high-end workstation card. Tesla 20-series includes: C2050/M2050/S2050 & C2070/M2070/S2070 (Workstation Card/Node-eMbedded/breakout Server respectively)

      • Quadro - High end workstation graphics card
      • GeForce - Consumer graphics card

  • AMD/ATi
    • Radeon
  • Intel
    1. Larrabee - potential for the future
  • Others

On Campus