Cache-Oblivious Sparse Matrix–Vector Multiplication by Using Sparse Matrix Partitioning Methods
نویسندگان
چکیده
منابع مشابه
Cache-Oblivious Sparse Matrix--Vector Multiplication by Using Sparse Matrix Partitioning Methods
In this article, we introduce a cache-oblivious method for sparse matrix vector multiplication. Our method attempts to permute the rows and columns of the input matrix using a hypergraph-based sparse matrix partitioning scheme so that the resulting matrix induces cache-friendly behaviour during sparse matrix vector multiplication. Matrices are assumed to be stored in row-major format, by means ...
متن کاملTwo-dimensional cache-oblivious sparse matrix-vector multiplication
In earlier work, we presented a one-dimensional cache-oblivious sparse matrix–vector (SpMV) multiplication scheme which has its roots in one-dimensional sparse matrix partitioning. Partitioning is often used in distributed-memory parallel computing for the SpMV multiplication, an important kernel in many applications. A logical extension is to move towards using a two-dimensional partitioning. ...
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Sparse matrix-vector multiplication (SpMxV) is a kernel operation widely used in iterative linear solvers. The same sparse matrix is multiplied by a dense vector repeatedly in these solvers. Matrices with irregular sparsity patterns make it difficult to utilize cache locality effectively in SpMxV computations. In this work, we investigate singleand multiple-SpMxV frameworks for exploiting cache...
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ژورنال
عنوان ژورنال: SIAM Journal on Scientific Computing
سال: 2009
ISSN: 1064-8275,1095-7197
DOI: 10.1137/080733243