An Algorithm-Centric Energy-Aware Design Methodology

The goal of this brief is to present a unique top-down design methodology for developing energy-aware algorithms based on energy profiling. The key idea revolves around identifying and measuring components of code with high energy consumption. There are two major contributions of this brief: 1) a method for identifying components with high energy consumption in compute-intensive applications. To this end, we target operations called kernels, which are frequently used operations in the algorithm; 2) a method for estimating software energy for the identified software components, in particular for kernels and load/store operations. The energy evaluation method involves isolated code with assembly injection. Furthermore, to ensure reliable results, we use physical energy measurements conducted on specially instrumented circuit boards to provide actual and not just simulated measurements. To evaluate the proposed methods, we conducted two case studies using data mining algorithms: K-nearest neighbors and linear regression. The results highlight the contributions of kernels and memory energy to total energy.