Report
ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems
| العنوان: | ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems |
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| المؤلفون: | Prabakaran, Bharath Srinivas, Mrazek, Vojtech, Vasicek, Zdenek, Sekanina, Lukas, Shafique, Muhammad |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Hardware Architecture |
| الوصف: | There has been abundant research on the development of Approximate Circuits (ACs) for ASICs. However, previous studies have illustrated that ASIC-based ACs offer asymmetrical gains in FPGA-based accelerators. Therefore, an AC that might be pareto-optimal for ASICs might not be pareto-optimal for FPGAs. In this work, we present the ApproxFPGAs methodology that uses machine learning models to reduce the exploration time for analyzing the state-of-the-art ASIC-based ACs to determine the set of pareto-optimal FPGA-based ACs. We also perform a case-study to illustrate the benefits obtained by deploying these pareto-optimal FPGA-based ACs in a state-of-the-art automation framework to systematically generate pareto-optimal approximate accelerators that can be deployed in FPGA-based systems to achieve high performance or low-power consumption. Comment: Accepted for Publication at the 57th Design Automation Conference (DAC), July 2020, San Francisco, CA, USA |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1109/DAC18072.2020.9218533 |
| URL الوصول: | http://arxiv.org/abs/2004.10502 |
| رقم الانضمام: | edsarx.2004.10502 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1109/DAC18072.2020.9218533 |
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