Comments on: How GPU came to be used for general computation

By: Ankush Desai

Ankush Desai — Sun, 17 Jul 2011 16:01:32 +0000

Hey Igor,
This is a really informative blog and there are many ideas which popped up in my mind.
I recently started working on Parallelizing programs such that they scale for really large datasets. Microsoft .Net has many features which provide easy ways of parallelizing codes. Like PLINQ, PSEQ, DryadLINQ. Extensions like PLINQ exploit parallelism by creating tasks for each chunk of work, these tasks are then executed by threads in the .NET threads-pool. Thousands of tasks are being created and they are then fed to these compute threads. Degree of parallelism of the program largely depends on this compute threads degree of parallelism.
If for example the UDFs( User defined Funtion) in PLINQ queries are pure that is they do not have side-effects then they can be executed in parallel.
I am new to GPGPU but then is it possible that we can run this tasks in the .NET framework on GPU cores and exploit larger degree of parallelism. If these are completely data parallel then I guess it should be possible. I would be really grateful to know your views on this.

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By: Kakkoii

Kakkoii — Wed, 02 Jun 2010 04:24:20 +0000

Great article, little mistake though..

You accidentally put the amount of threads a GPU core can run as the actual core count for current GPU’s. The current highest core count being 1600 from ATI and 480 from Nvidia, on a single GPU chip. (It should be noted though that ATI’s cores aren’t directly comparable to NVidia’s, so while one might think with such a higher core count the ATI card would be fast, it is not. It takes ATI’s cores 3 cycles to do the same thing Nvidia’s do in 1 cycle. Among many other differences.)

By: Justin Blanton | How the GPU came to be used for general computation

Justin Blanton | How the GPU came to be used for general computation — Mon, 22 Mar 2010 06:31:30 +0000

[...] How the GPU came to be used for general computation. [...]

By: Tzachi

Tzachi — Fri, 19 Mar 2010 14:35:56 +0000

Great post,
Could you give a quick example on how to use the nvcc to compile Cuda code. or a link to such example. I find the nvcc documentation to be not easy to understand.

Thanks

By: berne

berne — Thu, 18 Mar 2010 22:00:38 +0000

1 GFLOP = 1 billion floating point operations / second and…

1 TFLOP = 1000 billion floating point operations / second, right?

By: AndyB

AndyB — Thu, 18 Mar 2010 16:21:08 +0000

Very informative article.