@article {26461,
	title = {Performance optimization and modeling of fine-grained irregular communication in UPC},
	journal = {Scientific Programming},
	volume = {2019},
	year = {2019},
	month = {03/2019},
	pages = {Article ID 6825728},
	publisher = {Hindawi},
	abstract = {The UPC programming language offers parallelism via logically partitioned shared\&nbsp;memory, which typically spans physically disjoint memory sub-systems.\&nbsp;One convenient feature of UPC is\&nbsp;its ability to automatically execute between-thread data movement,\&nbsp;such that the entire content of a shared data array appears to be freely\&nbsp;accessible by all the threads. The\&nbsp;programmer friendliness, however, can come at the cost of substantial\&nbsp;performance penalties. This is especially true when indirectly indexing\&nbsp;the elements of a shared array, for which the induced between-thread data\&nbsp;communication can be irregular and have a fine-grained pattern.\&nbsp;In this paper we study performance enhancement strategies specifically targeting\&nbsp;such fine-grained irregular communication in UPC.\&nbsp;Starting from explicit thread privatization,\&nbsp;continuing with block-wise communication, and arriving at message condensing and\&nbsp;consolidation, we obtained considerable performance improvement of UPC\&nbsp;programs that originally require fine-grained irregular communication.\&nbsp;Besides the performance enhancement strategies, the main contribution of the present paper is to propose performance models for the different scenarios, in form of quantifiable formulas that hinge on the actual volumes of\&nbsp;various data movements\&nbsp;plus a small number of easily obtainable hardware characteristic parameters.\&nbsp;These performance models help to verify the enhancements obtained, while also providing insightful predictions of\&nbsp;similar parallel\&nbsp;implementations, not limited to UPC, that also involve between-thread or\&nbsp;between-process irregular communication. As a further validation,\&nbsp;we also apply our performance modeling methodology and hardware\&nbsp;characteristic parameters to an existing UPC code for solving a 2D\&nbsp;heat equation on a uniform mesh.},
	keywords = {Fine-grained irregular communication, performance modeling, Performance optimization, Sparse matrix-vector multiplication, UPC programming language},
	doi = {https://doi.org/10.1155/2019/6825728},
	url = {https://www.hindawi.com/journals/sp/2019/6825728/},
	author = {Lagravi{\`e}re, J{\'e}r{\'e}mie and Langguth, Johannes and Prugger, Martina and Einkemmer, Lukas and Phuong H. {Ha} and Cai, Xing}
}
