Work

Design-time methodology for optimizing mixed-precision CPU architectures on FPGA

Year: 2024

Type: article

Abstract: Approximate computing can significantly reduce the energy consumption of computing systems. Mixed-precision hardware architectures and precision-tuning tools for software provide the ability to introduce approximations, but when applied separately, they do not give complete control over the accuracy-energy trade-off. The co-optimization of approximations in hardware and software is a complex task, but it promises considerable benefits. We present a methodology for the fast design-time selection of mixed-precision hardware-software combinations that minimize the energy consumption and the area of the target FPGA-based softcore CPUs with configurable support for floating-point and fixed-point arithmetic. Our approach can evaluate configurations more than 2000 times faster than the alternative approach of using gate-level simulation. On benchmarks from the PolyBench suite the identified hardware-software configurations showed improvement of the energy-to-solution metric ranging from 20% to 95%.

Source: Journal of Systems Architecture

DOI: 10.1016/j.sysarc.2024.103257

Authors: Lev Denisov, Andrea Galimberti, Daniele Cattaneo, Giovanni Agosta, Davide Zoni

Institutions: Fondazione Politecnico di Milano, Politecnico di Milano

Language: English

Topic: Embedded Systems Design Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,910

Funder: European Commission