Abstract
Partitioned Global Address Space (PGAS) languages are a popular alternative when building applications to run on large scale parallel machines. Unified Parallel C (UPC) is a well known PGAS language that is available on most high performance computing systems. Good performance of UPC applications is often one important requirement for a system acquisition. This paper presents the memory management techniques employed by the IBM XL UPC compiler to achieve optimal performance on systems with Remote Direct Memory Access (RDMA). Additionally we describe a novel technique employed by the UPC runtime for transforming remote memory accesses on a same shared memory node into local memory accesses, to further improve performance. We evaluate the proposed memory allocation policies for various UPC benchmarks and using the IBM® Power® 775 supercomputer [1].
Researchers are supported by the IBM Center for Advanced Studies, and by the Defense Advanced Research Projects Agency under its Agreement No. HR0011-07-9-0002.
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Dalton, B., Tanase, G., Alvanos, M., Almási, G., Tiotto, E. (2015). Memory Management Techniques for Exploiting RDMA in PGAS Languages. In: Brodman, J., Tu, P. (eds) Languages and Compilers for Parallel Computing. LCPC 2014. Lecture Notes in Computer Science(), vol 8967. Springer, Cham. https://doi.org/10.1007/978-3-319-17473-0_13
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