LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A Scalable Body Bias Optimization Method Toward Low-Power CGRAs

Photo by acfb5071 from unsplash

Body biasing is one of the critical techniques to realize more energy-efficient computing with reconfigurable devices, such as coarse-grained reconfigurable architectures. Its benefit depends on the control granularity, whereas fine-grained… Click to show full abstract

Body biasing is one of the critical techniques to realize more energy-efficient computing with reconfigurable devices, such as coarse-grained reconfigurable architectures. Its benefit depends on the control granularity, whereas fine-grained control makes it challenging to find the best body bias voltage for each domain due to the complexity of the optimization problem. This work reformulates the optimization problem and introduces continuous relaxation to solve it faster than previous work based on an integer linear program. Experimental result shows the proposed method can solve the problem within 0.5 s for all benchmarks in any conditions. For a middle-class problem, up to 5.65× speedup and a geometric mean of 2.06× speedup are demonstrated compared to the previous method with negligible loss of accuracy. Besides, we explore finer body bias control considering the power- and area-overhead of an on-chip body bias generator and suggest the most reasonable design saves 66% of energy consumption.

Keywords: problem; power; body bias; scalable body; optimization; body

Journal Title: IEEE Micro
Year Published: 2023

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.