Previous studies in software transactional memory mostly focused on reducing the overhead of transactional read and write operations. In this article, we introduce transaction coalescing, a profile-guided compiler optimization technique that attempts to reduce the overheads of starting and committing a transaction by merging two or more small transactions into one large transaction. We develop a profiling tool and a transaction coalescing heuristic to identify candidate transactions suitable for coalescing. We implement a compiler extension to automatically merge the candidate transactions at the compile time. We evaluate the effectiveness of our technique using the hash table micro-benchmark and the STAMP benchmark suite. Transaction coalescing improves the performance of the hash table significantly and the performance of Vacation and SSCA2 benchmarks by 19.4% and 36.4%, respectively, when running with 12 threads.
Abstract. Deterministic execution of a multi-threaded application guarantees that threads access shared memory in the same order and the application gives the same output when it runs with the same input parameters. Determinism provides repeatability, which helps a programmer in testing and debugging. Additionally, Transactional Memory (TM) simplifies development of applications that use transactions (instead of locks) to synchronize accesses to shared memory. However, transactions that call standard library functions have to be serialized, and the serialization causes a deadlock when applications run with the deterministic systems proposed so far. In this paper, we present DeTrans-lib, the first standard C library that provides deterministic execution of TM-based applications at user and standard-library level. DeTrans-lib avoids deadlocks by performing transaction serialization in deterministic order. We evaluate DeTrans-lib using benchmarks that perform I/O operations.
Previous studies in software transactional memory mostly focused on reducing the overhead of transactional read and write operations. In this article, we introduce transaction coalescing, a profile-guided compiler optimization technique that attempts to reduce the overheads of starting and committing a transaction by merging two or more small transactions into one large transaction. We develop a profiling tool and a transaction coalescing heuristic to identify candidate transactions suitable for coalescing. We implement a compiler extension to automatically merge the candidate transactions at the compile time. We evaluate the effectiveness of our technique using the hash table micro-benchmark and the STAMP benchmark suite. Transaction coalescing improves the performance of the hash table significantly and the performance of Vacation and SSCA2 benchmarks by 19.4% and 36.4%, respectively, when running with 12 threads.
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