coalesced-access

Performance Characteristics for Sparse Matrix-Vector Multiplication on GPUs

The massive parallelism provided by the graphics processing units (GPUs) offers tremendous performance in many high-performance computing applications. One such application is Sparse Matrix-Vector (SpMV) multiplication, which is an essential building …

SURAA: A Novel Method and Tool for Loadbalanced and Coalesced SpMV Computations on GPUs

Sparse matrix-vector (SpMV) multiplication is a vital building block for numerous scientific and engineering applications. This paper proposes SURAA (translates to speed in arabic), a novel method for SpMV computations on graphics processing units …