![]() ![]() LISTING TWO: assn.upc creates a shared array of integers. Sterling T, Yelick K (2003) UPC: distributed shared-memory programming. This limitation was addressed with a wrapper from UPC to MPI collectives developed by the Berkeley UPC Project. This paper presents an evaluation, using UPC, of the most common sparse storage formats with different implementations of the matrix-vector and matrix-matrix products, which are key kernels in many scientific applications. and Lawrence Berkeley National Laboratory (LBNL) which offers a UPC implementation and is. As UPC shared arrays cannot be distributed with a variable block size. ![]() Among them, the selection of an adequate storage format for the sparse matrices can significantly improve the efficiency of the parallel codes. However, the performance issues that arise in this language due to the irregular structure of sparse matrix operations have not yet been studied. Shared allocations in UPC can span tasks in linear or. Unified Parallel C (UPC) is a Partitioned Global Address Space (PGAS) language whose popularity has increased during the last years owing to its high programmability and reasonable performance through an efficient exploitation of data locality, especially on hierarchical architectures like multicore clusters. hierarchy of computing nodes, the building blocks of su- percomputers (b) many-core devices. Recent attention on the UPC programming language has resulted in a number of conventional parallel programs, for example MPI programs, being ported to UPC. González-Domínguez, Jorge García-López, Óscar Taboada, Guillermo Martín, María Touriño, Juan This is done using UPC block transfer functions. Block size 0 ('indefinite') frequently is used for a pointer-to-shared so that it can point to data with affinity to a single thread. Performance evaluation of sparse matrix products in UPC Performance evaluation of sparse matrix products in UPC This is the case since UPC has the ability to recognize local-shared memory accesses, and perform them.
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