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RMS-TM: A transactional memory benchmark for recognition, mining and synthesis applications

ABSTRACT Transactional Memory (TM) is a new concurrency control mechanism that aims to make parallel programming for Chip MultiProcessors (CMPs) easier. Recently, this topic has re-ceived substantial research attention with various software and hardware TM proposals and designs that promise to make TM both more efficient. These proposals are usually analyzed using existing TM-benchmarks, however the per-formance evaluation of TM proposals would be more solid if it included more representative benchmarks, especially from the emerging future CMP applications in the Recognition, Mining and Synthesis (RMS) domain. In this work, we introduce RMS-TM, a new TM bench-mark suite that includes selected RMS applications. Besides being non-trivial and scalable, RMS-TM applications have several important properties that make them promising can-didates as good TM workloads, such as I/O operations inside critical sections, nested locking, and various percentages of time spent in atomic sections and high commit/abort rates depending on the application. We propose a methodical process to construct a TM benchmark suite from candidate applications: in this en-deavor, we divide the application selection process into static and dynamic pre-transactification phases and propose crite-ria for selecting the most suitable applications. Analyzing all the BioBench and MineBench RMS applications and apply-ing our methodology, we selected 4 applications which form the RMS-TM benchmark suite. Our experiments show that the transactified versions of RMS-TM applications scale as well as their lock-based versions.

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