In other news, the upcoming Microsoft Direct3D 11 will feature compute shaders. If I read correctly, this is shipping in Windows 7. NVIDIA is already out promoting the compatibility with CUDA. Apparently, this technology is also sometimes called DX Compute.
Direct3D 11 Compute Shaders
August 4, 2009
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datamining | Tagged: Cuda, GPGPU, Microsoft, multicore, NVidia, parallel, parallelism | 
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Posted by Karl W. Reinsch
A Survey Of Programming Video Cards For Other Purposes
August 3, 2009The August 2009 issue of ;login: from USENIX has a nice article on programming video cards by Tim Kaldewey entitled “Programming Video Cards For Database Applications”. Sadly, the article is only available to USENIX members until August of 2010.
Kaldewey surveys the past and present of programming video cards for non-graphics purposes – from the early days of using the graphics APIs to fool the GPU into thinking it is rendering graphics when it is really performing a general-purpose calculation, to the present era of general-purpose APIs such as CUDA.
He also shows a back-of-the-envelope calculation for building out a 100 teraflop data center using 100 GPUs versus 1400 CPUs, including power consumption differences.
If you are a USENIX member, the article is a good read. Sadly, it won’t be current when it finally becomes freely available.
[The same issue of ;login: also has a nice article by Leo Meyerovich: “Rethinking Browser Performance“.]
No Comments » | datamining, hardware, parallelism | Tagged: Cuda, datamining, GPGPU, Larrabee, multicore, parallel, parallelism | Permalink
Posted by Karl W. Reinsch
Moving AI Onto GPUs
February 16, 2009And what do we have here? It seems that Nvidia and AMD are already on top of the idea of offloading AI onto GPUs.
6 Comments | AI, video games | Tagged: AI, AMD, Cuda, GPGPU, multicore, NVidia, parallelism, video games | Permalink
Posted by Karl W. Reinsch
Multicore Video Cards (Again)
February 16, 2009I’ve previously posted on the topics of CUDA and Larrabee. I continue to be intrigued by the possibilities that open up as multi-core GPU programming becomes available. For applications that need many threads this should present interesting opportunities. Why bother struggling to run your parallel application in the meager 4 or 8 cores of your CPU when you can offload the work to 32 cores?
No Comments » | AI, games, hardware, parallelism, rules, video games | Tagged: AMD, ATI, Cuda, Dallas Gaming Mafia, GPGPU, Intel, Larrabee, Microsoft, multicore, NVidia, OpenCL, parallel, parallelism, Quake | Permalink
Posted by Karl W. Reinsch
