Node aware sparse matrix–vector multiplication
نویسندگان
چکیده
منابع مشابه
Node Aware Sparse Matrix-Vector Multiplication
where A is a sparse N ×N matrix and v is a dense N -dimensional vector. In parallel, the sparse system is often distributed across np processes such that each process holds a contiguous block of rows from the matrix A, and equivalent rows from the vectors v and w, as shown in Figure 1. A common approach is to also split the rows of A on a single process into two groups: an on-process block, con...
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In a large-scale and distributed matrix multiplication problem C = AB, where C ∈ Rr×t, the coded computation plays an important role to effectively deal with “stragglers” (distributed computations that may get delayed due to few slow or faulty processors). However, existing coded schemes could destroy the significant sparsity that exists in large-scale machine learning problems, and could resul...
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Routines callable from FORTRAN and C are described which implement matrix–matrix multiplication and transposition for a variety of sparse matrix formats. Conversion routines between various formats are provided.
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Partitioned global address space (PGAS) languages, such as Unified Parallel C (UPC) have the promise of being productive. Due to the shared address space view that they provide, they make distributing data and operating on ghost zones relatively easy. Meanwhile, they provide thread-data affinity that can enable locality exploitation. In this paper, we are considering sparse matrix multiplicatio...
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ژورنال
عنوان ژورنال: Journal of Parallel and Distributed Computing
سال: 2019
ISSN: 0743-7315
DOI: 10.1016/j.jpdc.2019.03.016