Add to ORKGAbstract—Recently, we have introduced an approach to basic sparse matrix computations on multicore cache based machines using recursive partitioning. Here, the memory representation of a sparse matrix consists of a set of submatrices, which are used as leaves of a quad-tree structure. In this paper, we evaluate the performance impact, on the Sparse Matrix-Vector Multiplication (SpMV), of a modification to our Recursive CSR implementation, allowing the use of multiple data structures in leaf matrices (CSR/COO, with either 16/32 bit indices). I
In this work we present a heuristic to select the appropriate compressed storage format when computi...
The sparse matrix is one of the most important data storage format for large amount of data. Sparse ...
The sparse matrix–vector (SpMV) multiplication is an important kernel in many applications. When the...
Abstract—Recently, we have introduced an approach to basic sparse matrix computations on multicore c...
In our earlier work, we have investigated the feasibility of utilization of recursive partitioning i...
In earlier work we have introduced the “Recursive Sparse Blocks ” (RSB) sparse matrix storage scheme...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
Sparse matrix-vector multiplication (SpMV) is an important operation in scientific computations. Com...
In this article, we introduce a cache-oblivious method for sparse matrix–vector multiplication. Our ...
Recently, we have proposed a recursive partitioning based layout for multi-core computations on spar...
The thesis introduces a cache-oblivious method for the sparse matrix-vector (SpMV) multiplication, w...
Abstract—Sparse matrix-vector multiplication (SpM×V) has been characterized as one of the most signi...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
Sparse computations are ubiquitous in computational codes, with the sparse matrix-vector (SpMV) mult...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
In this work we present a heuristic to select the appropriate compressed storage format when computi...
The sparse matrix is one of the most important data storage format for large amount of data. Sparse ...
The sparse matrix–vector (SpMV) multiplication is an important kernel in many applications. When the...
Abstract—Recently, we have introduced an approach to basic sparse matrix computations on multicore c...
In our earlier work, we have investigated the feasibility of utilization of recursive partitioning i...
In earlier work we have introduced the “Recursive Sparse Blocks ” (RSB) sparse matrix storage scheme...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
Sparse matrix-vector multiplication (SpMV) is an important operation in scientific computations. Com...
In this article, we introduce a cache-oblivious method for sparse matrix–vector multiplication. Our ...
Recently, we have proposed a recursive partitioning based layout for multi-core computations on spar...
The thesis introduces a cache-oblivious method for the sparse matrix-vector (SpMV) multiplication, w...
Abstract—Sparse matrix-vector multiplication (SpM×V) has been characterized as one of the most signi...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
Sparse computations are ubiquitous in computational codes, with the sparse matrix-vector (SpMV) mult...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
In this work we present a heuristic to select the appropriate compressed storage format when computi...
The sparse matrix is one of the most important data storage format for large amount of data. Sparse ...
The sparse matrix–vector (SpMV) multiplication is an important kernel in many applications. When the...