Can Traditional Programming Bridge the Ninja Performance Gap for Parallel Computing Applications?

摘要

Current processor trends of integrating more cores with wider Single-instruction multiple-data (SIMD) units, along with a deeper and complex memory hierarchy, have made it increasingly more challenging to extract performance from applications. It is believed by some that traditional approaches to programming do not apply to these modern processors and hence radical new languages must be designed. In this paper, we question this thinking and offer evidence in support of traditional programming methods and the performance-versus-programming effort effectiveness of multi-core processors and upcoming many-core architectures in delivering significant speedup, and close-to-optimal performance for commonly used parallel computing workloads.