Distributed Speculative Parallelization using Checkpoint Restart

Speculative software parallelism has gained renewed interest recently as a mechanism to leverage multiple cores on emerging architectures. Two major mechanisms have been used to implement speculation-based parallelism in software, software transactional memory and speculative threads. We propose a third mechanism based on checkpoint restart. With recent developments in checkpoint restart technology this has become an attractive alternative. The approach has the potential advantage of the conceptual simplicity of transactional memory and flexibility of speculative threads. Since many checkpoint restart systems work with large distributed memory programs, this provides an automatic way to perform distributed speculation over clusters. Additionally, since checkpoint restart systems are primarily designed for fault tolerance, using the same system for speculation could provide fault tolerance within speculative execution as well when it is embedded in large-scale applications where fault tolerance is desirable. In this paper we use a series of micro-benchmarks to study the relative performance of a speculative system based on the DMTCP checkpoint restart system and compare it against a thread level speculative system. We highlight the relative merits of each approach and draw some lessons that could be used to guide future developments in speculative systems.