A Survey on Hardware and Software Support for Thread Level Parallelism

TL;DR

This survey reviews hardware and software mechanisms for thread level parallelism, highlighting diverse models, hardware support, and management issues to improve multicore system performance.

Contribution

It provides a comprehensive overview of current solutions and challenges in hardware and software support for thread management in multicore systems.

Findings

Hybrid programming models are promising for heterogeneous hardware.

Hardware support at runtime significantly impacts system performance.

Software support enhances deterministic behavior during thread execution.

Abstract

To support growing massive parallelism, functional components and also the capabilities of current processors are changing and continue to do so. Todays computers are built upon multiple processing cores and run applications consisting of a large number of threads, making runtime thread management a complex process. Further, each core can support multiple, concurrent thread execution. Hence, hardware and software support for threads is more and more needed to improve peak-performance capacity, overall system throughput, and has therefore been the subject of much research. This paper surveys, many of the proposed or currently available solutions for executing, distributing and managing threads both in hardware and software. The nature of current applications is diverse. To increase the system performance, all programming models may not be suitable to harness the built-in massive parallelism of multicore processors. Due to the heterogeneity in hardware, hybrid programming model (which combines the features of shared and distributed model) currently has become very promising. In this paper, first, we have given an overview of threads, threading mechanisms and its management issues during execution. Next, we discuss about different parallel programming models considering to their explicit thread support. We also review the programming models with respect to their support to shared-memory, distributed-memory and heterogeneity. Hardware support at execution time is very crucial to the performance of the system, thus different types of hardware support for threads also exist or have been proposed, primarily based on widely used programming models. We also further discuss on software support for threads, to mainly increase the deterministic behavior during runtime. Finally, we conclude the paper by discussing some common issues related to the thread management.