Correctly Synchronised POSIX-threads Benchmark Applications

Abstract: With the future of high performance computing quickly moving towards a higher and higher count of CPU cores, the need for efficient memory coherence models is becoming more and more prevalent. Strict memory models, while convenient for the programmer, limit the scalability and overall performance of multi- and manycore systems. For this reason, relaxed memory models are looked into, both in academia and in the industry. Applications written for stronger memory models often contain data races, which cause unexpected behaviour in more relaxed models, many of which rely on data race free code to work. At the same time, some of the most widely used programming languages now require data race free code. For these reasons, the need for benchmarks based on properly synchronised code is bigger than ever. In this thesis, we will identify data races in major benchmark suites, remove them, and then quantify and compare the performance differences between the unmodified and the properly synchronised versions.