Algorithm Selection: A Quantitative Computation-intensive Optimization Approach

Abstract

Given a set of specifications for a targeted application, algorithm selection refers to choosing the most suitable algorithm for a given goal, among several functionally equivalent algorithms. We demonstrate an extraordinary potential of algorithm selection for achieving high throughput, low cost, and low power implementations. We introduce an efficient technique for low-bound evaluation of the throughput and cost during algorithm selection and propose a relaxation-based heuristic for throughput optimization. We also present an algorithm for cost optimization using algorithm selection. The effectiveness of methodology and algorithms is illustrated using examples.