Today, your computer has at least two processors, the main unit or CPU, and the GPU, dedicated to graphics. But it's a little-known secret that the GPU is now much more powerful that the CPU. The GPU has some drawbacks, such as a small memory, a difficult programming model or an almost general lack of floating-point precision. However, it's tempting to harness the GPU power to help the main CPU to do the general computation.
In "Supernova collapse simulated on a GPU," EE Times describes how computer scientists from Los Alamos National Laboratory have developed the Scout project to do this. With the use of an Nvidia Quadro 3400 card, "Scout has achieved improved computational rates that are roughly 20 times faster than a 3-GHz Intel Xeon EM64T processor without the use of streaming SIMD extensions, and approximately four times faster than SIMD-enabled, fully optimized code."
Impressive, isn't? Now, they want to go further and operate hundreds of GPUs in parallel. Read more for selected excerpts, other references, images and some remarkably simple and elegant of Scout code.
In "Supernova collapse simulated on a GPU," EE Times describes how computer scientists from Los Alamos National Laboratory have developed the Scout project to do this. With the use of an Nvidia Quadro 3400 card, "Scout has achieved improved computational rates that are roughly 20 times faster than a 3-GHz Intel Xeon EM64T processor without the use of streaming SIMD extensions, and approximately four times faster than SIMD-enabled, fully optimized code."
Impressive, isn't? Now, they want to go further and operate hundreds of GPUs in parallel. Read more for selected excerpts, other references, images and some remarkably simple and elegant of Scout code.
| :: posted by Roland Piquepaille, 3:41 PM | Comments (0)
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