Abstract
The potential of heterogeneous multicores, like the Cell BE, can only be exploited if the host and the accelerator cores are used in parallel and if the specific features of the cores are considered. Parallel programming, especially when applied to irregular task-parallel problems, is challenging itself. However, heterogeneous multicores add to that complexity due to their memory hierarchy and specialized accelerators. As a solution for these issues we present CellCilk, a prototype implementation of Cilk for heterogeneous multicores with a host/accelerator design, using the Cell BE in particular. CellCilk introduces a new keyword (spu_spawn) for task creation on the accelerator cores. Task scheduling and load balancing are done by a novel dynamic cross-hierarchy work-stealing regime. Furthermore, the CellCilk runtime employs a garbage collection mechanism for distributed data structures that are created during scheduling. On benchmarks we achieve a good speedup and reasonable runtimes, even when compared to manually parallelized codes.
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Werth, T., Schreier, S., Philippsen, M. (2013). CellCilk: Extending Cilk for Heterogeneous Multicore Platforms. In: Rajopadhye, S., Mills Strout, M. (eds) Languages and Compilers for Parallel Computing. LCPC 2011. Lecture Notes in Computer Science, vol 7146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36036-7_7
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DOI: https://doi.org/10.1007/978-3-642-36036-7_7
Publisher Name: Springer, Berlin, Heidelberg
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