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Asked: 2026-05-24T08:33:44+00:00

I first got into GPGPU with my (now aging) NVIDIA 9800GT 512MB via CUDA.

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I first got into GPGPU with my (now aging) NVIDIA 9800GT 512MB via CUDA. It seems these days my GPU just doesn’t cut it.

I’m specifically interested in OpenCL, as opposed to CUDA or StreamSDK, though some info on whether either of these are still worth pursuing would be nice.

My budget is around 150 GBP plus/minus 50 GBP. I’m a little out of the loop on which GPUs are best for scientific computing (specifically fluid simulation and 3D medical image processing).

A comparison of ATI vs. NVIDIA may also be helpful, if they are really so disparate.

[I’d also be interested to hear any suggestions on games that make use of GPGPU capabilities, but that’s a minor issue next to the potential for scientific computing.]

I’m also a little lost when it comes to evaluating the pros/cons of memory speed vs. clock speed vs. memory capacity, etc, so any info with regard to these more technical aspects would be most appreciated.

Cheers.

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  1. Editorial Team

    If you were going purely off OpenCL being the requirement, I would say you go with ATI because they have a released version of OpenCL 1.1 drivers where as nVidia had beta drivers almost instantly when the spec was published, but has not updated them since and they have a couple bugs from what I’ve read in the nVidia open OpenCL forums.

    Personally I chose nVidia because it gives me all the options. You really ought to check out CUDA. It’s a far more productive approach to leveraging the GPU and CPU using a common language. Down the road Microsoft’s AMP language extensions for C++ are going to provide the same sort of approach as CUDA in a more platform agnostic way though and I’m sure that will be more widely adopted by the community at that point than CUDA.

    Another reason to choose nVidia is because that’s what the HPC system builders have been building systems with since nVidia made a huge push for GPGPU computing where as it’s less backed by AMD/ATI. There really is no answer to the Tesla lineup from that camp. Even Amazon EC2 offers a GPU compute cluster based on Tesla. So, if you’re looking for reach and scale beyond the desktop, I think nVidia is a better bet.

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