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Interesting move. We just bought two Tesla Cards for a university project so I know how much people could save by just prototyping on a "small" card that can do

by rb2k_ 16y ago

Interesting move. We just bought two Tesla Cards for a university project so I know how much people could save by just prototyping on a "small" card that can do ?OpenCL? and then using a Quadruple Extra Large instance at $2.10 per hour for the actual computation instead of buying a 5 digit Euro workstation

tomjen3 16y ago
The problem is that you need to tailor your problem to the core thats actually running, which means you can't really develop on any old NVIDIA gpu and expect optimal performance on the cluster. But on the other hand a developer who works for 8 hours a day is going to cost about 22 dollars -- which isn't that much when you take his salary into account. In other words: stop being cheap and start saving money.
- rbanffy 16y ago
  > you can't really develop on any old NVIDIA gpu and expect optimal performance on the cluster. OTOH, you can optimize your code to run on the bigger iron while you check it on the small one on your desk to see if the results are correct. Computers can make billions of miscalculations per second if the programmer is not watchful enough. And 22 dollars an hour is really cheap.
  - jedbrown 16y ago
    $22 was not salary, it was some estimate of the cost of developing on the GPU instance, per day. (Seems high though, should be $2.10/hour * 8 hours unless there are other fees I didn't notice.) In any case, this is very cheap compared to the developer's salary, and since there are multiple cores, could be shared. OTOH, there is some cost to developing on a remote machine since it takes time to set up an environment as productive as the local one you already have.
    - tomjen3 16y ago
      I didn't really want to go back, but I though it was $2.30/hour.
- JabavuAdams 16y ago
  Yeah, I tried an OpenCL FFT example, and it was very sensitive to a number of non-obvious hardware tuning parameters. That actually turned me off OpenCL at the time. Are there any black boxish GPU-accelerated FFT implementations? I'd like a drop-in replacement for FFTW.
  - cjenkins 16y ago
    I'm not sure how the API compares to FFTW, but if you're on Nvidia hardware the toolkit comes with the CUFFT library http://developer.nvidia.com/object/cuda_3_2_toolkit_rc.html http://developer.nvidia.com/object/cuda_3_2_toolkit_rc.html which is tuned for their hardware. I seem to recall needing to transfer the data to GPU memory and other things like that when I last used it, but that was prior to toolkit 2.0 IIRC.
    - JabavuAdams 16y ago
      Thanks. I also just found PyFFT, here: http://pypi.python.org/pypi/pyfft/0.3.1 http://pypi.python.org/pypi/pyfft/0.3.1 I'll start with this and see how it goes.

by rb2k_ 16y ago

tomjen3 16y ago

The problem is that you need to tailor your problem to the core thats actually running, which means you can't really develop on any old NVIDIA gpu and expect optimal performance on the cluster. But on the other hand a developer who works for 8 hours a day is going to cost about 22 dollars -- which isn't that much when you take his salary into account. In other words: stop being cheap and start saving money.

rbanffy 16y ago
> you can't really develop on any old NVIDIA gpu and expect optimal performance on the cluster. OTOH, you can optimize your code to run on the bigger iron while you check it on the small one on your desk to see if the results are correct. Computers can make billions of miscalculations per second if the programmer is not watchful enough. And 22 dollars an hour is really cheap.
- jedbrown 16y ago
  $22 was not salary, it was some estimate of the cost of developing on the GPU instance, per day. (Seems high though, should be $2.10/hour * 8 hours unless there are other fees I didn't notice.) In any case, this is very cheap compared to the developer's salary, and since there are multiple cores, could be shared. OTOH, there is some cost to developing on a remote machine since it takes time to set up an environment as productive as the local one you already have.
  - tomjen3 16y ago
    I didn't really want to go back, but I though it was $2.30/hour.
JabavuAdams 16y ago
Yeah, I tried an OpenCL FFT example, and it was very sensitive to a number of non-obvious hardware tuning parameters. That actually turned me off OpenCL at the time. Are there any black boxish GPU-accelerated FFT implementations? I'd like a drop-in replacement for FFTW.
- cjenkins 16y ago
  I'm not sure how the API compares to FFTW, but if you're on Nvidia hardware the toolkit comes with the CUFFT library http://developer.nvidia.com/object/cuda_3_2_toolkit_rc.html http://developer.nvidia.com/object/cuda_3_2_toolkit_rc.html which is tuned for their hardware. I seem to recall needing to transfer the data to GPU memory and other things like that when I last used it, but that was prior to toolkit 2.0 IIRC.
  - JabavuAdams 16y ago
    Thanks. I also just found PyFFT, here: http://pypi.python.org/pypi/pyfft/0.3.1 http://pypi.python.org/pypi/pyfft/0.3.1 I'll start with this and see how it goes.