Abstract:
An energy-quality scalable coarse grain reconfigurable architecture (CGRA) based on the voltage overscaling (VOS) technique is presented. The approximation level of each ...Show MoreMetadata
Abstract:
An energy-quality scalable coarse grain reconfigurable architecture (CGRA) based on the voltage overscaling (VOS) technique is presented. The approximation level of each processing element (PE) in the CGRA is determined by the applied VOS-determined voltage level. By employing the technique, the architecture may be configured for accurate or approximate modes of computation depending on a user-specified output quality-of-service target for a given application. More precisely, operating voltages used for performing various operations in the application dataflow graph are minimized subject to the output quality constraint by using an energy-quality tradeoff algorithm. To make the hardware implementation of the scheme more efficient, PEs are clustered into groups of (e.g., 3 × 1 and 2 × 1) voltage islands. To assess the efficacy of the proposed method in improving the power (energy) consumption and reliability of CGRAs, different combinations of minimum output quality constraints, voltage levels, and cluster sizes for several benchmarks are studied. Simulation results indicate considerable reductions in energy consumption (up to 43%) and aging rate (up to 73%) when compared with the conventional CGRA with perfect output quality (i.e., with no approximate computations).
Published in: IEEE Journal on Emerging and Selected Topics in Circuits and Systems ( Volume: 8, Issue: 3, September 2018)