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Content Provider | IEEE Xplore Digital Library |
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Author | Hang Zhang Putic, M. Lach, J. |
Copyright Year | 2014 |
Description | Author affiliation: Electr. & Comput. Eng, Univ. of Virginia, Charlottesville, VA, USA (Lach, J.) || Comput. Eng., Univ. of Virginia, Charlottesville, VA, USA (Hang Zhang; Putic, M.) |
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. |
Starting Page | 1 |
Ending Page | 6 |
File Size | 663462 |
Page Count | 6 |
File Format | |
ISBN | 9781479930173 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-06-01 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Association for Computing Machinery, Inc. (ACM) |
Subject Keyword | Graphics processing units Power demand Adders Measurement Hardware Computational modeling Linear approximation GPGPU Imprecise Hardware Approximate Computing Floating Point Unit Special Function Unit |
Content Type | Text |
Resource Type | Article |
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