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• W4250869868 abstract "Massively parallel computation in GPUs significantly boosts performance of compute-intensive applications but creates power and thermal issues that limit further performance scaling. This paper demonstrates significant GPGPU power savings by relaxing application accuracy requirements and enabling the use of low power imprecise hardware (IHW). A synthesized set of novel imprecise floating point arithmetic units is presented. GPGPU-Sim and GPUWattch are used to estimate impacts of IHW units on output quality and system-level power consumption, providing a quality-power tradeoff model for application-specific optimization. Experimental results for a 45 nm process show up to 32% power savings with negligible impacts on output quality." @default.
• W4250869868 created "2022-05-12" @default.
• W4250869868 creator A5010326266 @default.
• W4250869868 creator A5074743331 @default.
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• W4250869868 date "2014-06-01" @default.
• W4250869868 modified "2023-10-03" @default.
• W4250869868 title "Low power GPGPU computation with imprecise hardware" @default.
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• W4250869868 doi "https://doi.org/10.1109/dac.2014.6881426" @default.
• W4250869868 hasPublicationYear "2014" @default.
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