DTAP: Accelerating Strongly-Typed Programs with Data Type-Aware Hardware Prefetching

Abstract

Queries on linked data structures, such as trees and graphs, often suffer from frequent cache misses and significant performance loss due to dependent and random pointer-chasing memory accesses. In this paper, we propose a software-hardware co-designed solution for accelerating linked data structures implemented in strongly typed languages. The solution incorporates a compiler extension and a hardware prefetcher. The compiler extension extracts type information from the code, annotates each load instruction, and forwards the type information to the hardware prefetcher. The prefetcher leverages the type information to fetch the referred objects and identify the associated pointers in advance. By doing so, the program can find these objects in the cache when it follows the prefetched pointers, thus minimizing cache misses. In the evaluation, the proposed solution achieves an average speedup of 1.37 × over a set of memory-intensive benchmarks.