NVIDIA Tesla: GPU computing gets its own brand @ Beyond3d

Vikingod · Jun 21, 2007, 02:32 PM

Source: Beyond3d
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When NVIDIA's G80 launched in November 2006, there was a brief mention of a new toolkit that would greatly simplify GPU computing development. Called CUDA (for Complete Unified Device Architecture), we knew at the time that it was a C derivative that would run on the GPU without using any 3D API as an intermediary. We also knew that the lead architect for CUDA was Ian Buck, a student of the legendary Pat Hanrahan at Stanford and one of the authors of the original BrookGPU paper. Considering its pedigree, we were very excited to see what he could do with G80. While we waited to get our hands on CUDA, we saw three major advantages to NVIDIA's approach. First, by bypassing 3D APIs, there's no concern about future drivers breaking an application as has plagued them in the past; consider Folding@Home's initial release on R580 and the continued absence of G80 support as an example. Second, it makes GPU computing more accessible by allowing developers to write their applications in a potentially more familiar manner, as opposed to shoehorning their application to fit within a 3D API's paradigm. Finally, it allows developers to access portions of the chip that they wouldn't be able to use directly in a 3D API.

Jun 21, 2007, 02:32 PM	#1
Vikingod Int'l Fish Liaison Join Date: Jul 2004 Location: By the light of lamp I sit and type... Posts: 16,197 Rep Power: 112 System Specs	NVIDIA Tesla: GPU computing gets its own brand @ Beyond3d Source: Beyond3d ___________ When NVIDIA's G80 launched in November 2006, there was a brief mention of a new toolkit that would greatly simplify GPU computing development. Called CUDA (for Complete Unified Device Architecture), we knew at the time that it was a C derivative that would run on the GPU without using any 3D API as an intermediary. We also knew that the lead architect for CUDA was Ian Buck, a student of the legendary Pat Hanrahan at Stanford and one of the authors of the original BrookGPU paper. Considering its pedigree, we were very excited to see what he could do with G80. While we waited to get our hands on CUDA, we saw three major advantages to NVIDIA's approach. First, by bypassing 3D APIs, there's no concern about future drivers breaking an application as has plagued them in the past; consider Folding@Home's initial release on R580 and the continued absence of G80 support as an example. Second, it makes GPU computing more accessible by allowing developers to write their applications in a potentially more familiar manner, as opposed to shoehorning their application to fit within a 3D API's paradigm. Finally, it allows developers to access portions of the chip that they wouldn't be able to use directly in a 3D API.