Abstract
An efficient implementation of task parallelism is important for high productivity languages. Specifically, it requires a tasking layer that fulfills following requirements: (i) its performance scales to high core counts, and (ii) it is seamlessly integrated into a runtime system that performs inter-node communication and synchronization. More specifically, it should facilitate interactions between tasks and threads dedicated for inter-node communication. There have been many implementations that satisfy (i), but, to the best of our knowledge, none of such systems satisfy both requirements.
To address this issue, we propose a thread library called MassiveThreads. It provides not only lightweight threads and a scalable dynamic load-balancing mechanism among CPU cores, but also Pthread-compatible API and I/O semantics. In MassiveThreads, issuing a blocking I/O call triggers a user-level context switch instead of blocking the underlying OS-level thread. These features simplify interactions between tasks and communication threads by instantiating both of them on top of MassiveThreads.
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Nakashima, J., Taura, K. (2014). MassiveThreads: A Thread Library for High Productivity Languages. In: Agha, G., et al. Concurrent Objects and Beyond. Lecture Notes in Computer Science, vol 8665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44471-9_10
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DOI: https://doi.org/10.1007/978-3-662-44471-9_10
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