Sparse matrix-vector multiplication on graphics processor units

Techniques for optimizing sparse matrix-vector multiplication (SpMV) on a graphics processing unit (GPU) are provided. The techniques include receiving a sparse matrix-vector multiplication, analyzing the sparse matrix-vector multiplication to identify one or more optimizations, wherein analyzing th...

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Hauptverfasser: BASKARAN MUTHU M, BORDAWEKAR RAJESH J
Format: Patent
Sprache:eng
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Zusammenfassung:Techniques for optimizing sparse matrix-vector multiplication (SpMV) on a graphics processing unit (GPU) are provided. The techniques include receiving a sparse matrix-vector multiplication, analyzing the sparse matrix-vector multiplication to identify one or more optimizations, wherein analyzing the sparse matrix-vector multiplication to identify one or more optimizations comprises analyzing a non-zero pattern for one or more optimizations and determining whether the sparse matrix-vector multiplication is to be reused across computation, optimizing the sparse matrix-vector multiplication, wherein optimizing the sparse matrix-vector multiplication comprises optimizing global memory access, optimizing shared memory access and exploiting reuse and parallelism, and outputting an optimized sparse matrix-vector multiplication.