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Fast Sparse Matrix Multiplication on GPU

机译:GPU上快速稀疏矩阵乘法

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Sparse matrix multiplication is an important algorithm in a wide variety of problems, including graph algorithms, simulations and linear solving to name a few. Yet, there are but a few works related to acceleration of sparse matrix multiplication on a GPU. We present a fast, novel algorithm for sparse matrix multiplication, outperforming the previous algorithm on GPU up to 3× and CPU up to 30×. The principal improvements include more efficient load balancing strategy, and a faster sorting algorithm. The main contribution is design and implementation of efficient sparse matrix multiplication algorithm and extending it to sparse block matrices, which is to our best knowledge the first implementation of this kind.
机译:稀疏矩阵乘法是各种问题的重要算法,包括图形算法,模拟和线性求解,以命名几个。然而,但是,除了GPU上的稀疏矩阵乘法的加速有几种作品。我们为稀疏矩阵乘法提供了快速,新颖的算法,优于GPU上的先前算法,最多3×和CPU高达30×。主要改进包括更有效的负载平衡策略,以及更快的排序算法。主要贡献是有效稀疏矩阵乘法算法的设计和实现,并将其扩展到稀疏块矩阵,这是我们最佳知识的最佳知识。

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