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Success and Failure Stories

The slides can be downloaded from here.

Some wrap-up of the most common reasoning for and against GPGPU computation (on a very high level):


  • Hundredfold performance gain for some (easily parallelizable) applications


  • Hard to program
  • Restrictive architecture, memory access
  • Different execution paths cause idle time on other threads
  • Performance gains hard to get for other applications than the ones that properly fit the model
  • Host-device memory transfer is slow ¿ latency
    • Not usable for smaller problem instances

I've only listed a single "pro", but it's a fairly major one...

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