Game on for acceleration [graphics processors]

Game on for acceleration [graphics processors]

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Supercomputer users could provide the impetus for a change in the way ordinary PCs are designed and used. Among scientific users there is one big concern: today's GPUs are designed to run single- precision floating-point calculations efficiently. But scientific users like being able to use double-precision. The performance gains made possible by GPUs in supercomputing may feedback into the architecture of the mainstream PC or even embedded computer. Architects are wondering what shape a future processor will take now that the multicore philosophy is embedded into most processor roadmaps. The main strength of FPGAs in high-performance computing lies in the ability to reorganise the internal structure of a machine to feed data-to-data processors at high-speed instead of forcing them to made continual memory requests, making FPGAs much better at sustaining performance compared with processors. Although the GPU may support higher performance at lower power, applications will determine who ends up owning the PC's main socket. If only a small subset of specialist programs need the GPU, the dominance is likely to remain with Intel and other host- processor suppliers. But, if more software writers adopt environments such as CUDA, the balance of power could easily shift.

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