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 article, 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.

We consider the problem of the robust stability of a class of uncertain T–S fuzzy neutral systems with time delay under time-varying parametric uncertainties using the Lyapunov–Krasovskii approach, where the parametric uncertainty is assumed to be norm bounded. By choosing a new Lyapunov–Krasovskii function, we are able to propose less conservative robust stability criteria in terms of linear matrix inequalities (LMIs) such that the uncertain T–S fuzzy neutral system under consideration remains asymptotically stable. The reduced conservatism of the proposed stability criterion compared with recently reported results is attributed to our using the Jensen inequality. The obtained results can also reduce the computational complexity.