Improving Transactional Memory Performance for Irregular Applications

Transactional memory (TM) offers optimistic concurrency support in modern multicore architectures, helping the programmers to extract parallelism in irregular applications when data dependence information is not available before runtime. In fact, recent research focus on exploiting thread-level parallelism using TM approaches. However, the proposed techniques are of general use, valid for any type of application. This work presents ReduxSTM, a software TM system specially designed to extract maximum parallelism from irregular applications. Commit management and conflict detection are tailored to take advantage of both, sequential transaction ordering to assure correct results, and privatization of reduction patterns, a very frequent memory access pattern in irregular applications. Both techniques are used to avoid unnecessary transaction aborts. A function in 300.twolf package from SPEC CPU2000 was taken as a motivating irregular program. This code was parallelized using ReduxSTM and an ordered version of TinySTM, a state-of-the-art TM system. Experimental evaluation shows that ReduxTM exploits more parallelism from the sequential program and obtains better performance than the other system.