Gene-Patterns: Should Architecture be Customized for Each Application?

TL;DR

This paper introduces Gene-Patterns, a set of base application patterns, and a methodology to identify them, aiming to guide architecture customization for improved performance across diverse applications.

Contribution

It presents a novel approach to extract and analyze core application patterns, demonstrating their limited diversity and guiding architecture design.

Findings

Number of base patterns is small despite many applications.

Memory access patterns can be categorized using PT-MAP.

Mismatch between patterns and micro-architecture causes inefficiency.

Abstract

Providing architectural support is crucial for newly arising applications to achieve high performance and high system efficiency. Currently there is a trend in designing accelerators for special applications, while arguably a debate is sparked whether we should customize architecture for each application. In this study, we introduce what we refer to as Gene-Patterns, which are the base patterns of diverse applications. We present a Recursive Reduce methodology to identify the hotspots, and a HOtspot Trace Suite (HOTS) is provided for the research community. We first extract the hotspot patterns, and then, remove the redundancy to obtain the base patterns. We find that although the number of applications is huge and ever-increasing, the amount of base patterns is relatively small, due to the similarity among the patterns of diverse applications. The similarity stems not only from the algorithms but also from the data structures. We build the Periodic Table of Memory Access Patterns (PT-MAP), where the indifference curves are analogous to the energy levels in physics, and memory performance optimization is essentially an energy level transition. We find that inefficiency results from the mismatch between some of the base patterns and the micro-architecture of modern processors. We have identified the key micro-architecture demands of the base patterns. The Gene-Pattern concept, methodology, and toolkit will facilitate the design of both hardware and software for the matching between architectures and applications.