Ahead-of-time data layout optimization by vertex reordering is a widely used technique to
improve memory access locality in graph analysis. While reordered graphs yield better …

In this paper, we realize a wideband fiber-optic Fabry-Perot (FP) acoustic sensing (FPAS)
scheme by utilizing a high-speed absolute cavity length demodulation with a 70-kHz …

The minimum st cut problem in graphs is one of the most fundamental problems in
combinatorial optimization, and graph cuts underlie algorithms throughout discrete …

We propose a fine-grained hypergraph model for sparse matrix-matrix multiplication
(SpGEMM), a key computational kernel in scientific computing and data analysis whose …

Sparse Matrix-Vector multiplication (SpMV) is a fundamental kernel, used by a large class of
numerical algorithms. Emerging big-data and machine learning applications are propelling …

Exploiting spatial and temporal localities is investigated for efficient row-by-row
parallelization of general sparse matrix-matrix multiplication (SpGEMM) operation of the …

The state-of-the-art deep neural networks (DNNs) have significant computational and data
management requirements. The size of both training data and models continue to increase …

The performance of parallel algorithms for sparse matrix-matrix multiplication is typically
determined by the amount of interprocessor communication performed, which in turn …

Sparse matrix-vector and matrix-transpose-vector multiplication (SpMM TV) repeatedly
performed as z← AT x and y← A z (or y A w) for the same sparse matrix A is a kernel …

Sparse matrix–vector multiplication (SpMV) on FPGAs has gained much attention. The
performance of SpMV is mainly determined by the number of multiplications between …