A systematic survey of general sparse matrix-matrix multiplication
General Sparse Matrix-Matrix Multiplication (SpGEMM) has attracted much attention from
researchers in graph analyzing, scientific computing, and deep learning. Many optimization …
researchers in graph analyzing, scientific computing, and deep learning. Many optimization …
Csr implication and disclosure in higher education: Uncovered points. results from a systematic literature review and agenda for future research
This research reviews and analyzes prior corporate social responsibility (CSR) studies
centered on its implications and disclosure in higher education institutions (HEIs). Nine …
centered on its implications and disclosure in higher education institutions (HEIs). Nine …
An artificial intelligence perspective on mobile edge computing
The interest of artificial intelligence (AI) and mobile edge computing (MEC) has increased in
recent years. As a fundamental building block for the development of mobile edge …
recent years. As a fundamental building block for the development of mobile edge …
HARP: Hardware-Based Pseudo-Tiling for Sparse Matrix Multiplication Accelerator
General sparse matrix-matrix multiplication (SpGEMM) is a memory-bound workload, due to
the compression format used. To minimize data movements for input matrices, outer product …
the compression format used. To minimize data movements for input matrices, outer product …
PCPD: A parallel crime pattern discovery system for large-scale spatiotemporal data based on fuzzy clustering
In this paper, we focus on the discovering criminal behaviors and patterns issue and
propose a Parallel Crime Pattern Discovery system using machine learning and high …
propose a Parallel Crime Pattern Discovery system using machine learning and high …
ahSpMV: An autotuning hybrid computing scheme for SpMV on the sunway architecture
The prevalence of the Internet of Things (IoT) and the explosion of available information on
the Web have led to an enormous amount of widely available IoT data sets with sparsity …
the Web have led to an enormous amount of widely available IoT data sets with sparsity …
tpSpMV: a two-phase large-scale sparse matrix-vector multiplication kernel for manycore architectures
Sparse matrix-vector multiplication (SpMV) is one of the important subroutines in numerical
linear algebras widely used in lots of large-scale applications. Accelerating SpMV on …
linear algebras widely used in lots of large-scale applications. Accelerating SpMV on …
Neighborhood Learning-Based Cuckoo Search Algorithm for Global Optimization
Y Xiong, J Cheng, L Zhang - International Journal of Pattern …, 2022 - World Scientific
This paper presents a new variant of cuckoo search (CS) algorithm named neighborhood
learning-based CS (NLCS) to address global optimization problems. Specifically, in this …
learning-based CS (NLCS) to address global optimization problems. Specifically, in this …
A load-balanced acceleration method for small and irregular batch matrix multiplication on GPU
Y Zhang, L Lu, Z Yang, Z Liang, S Suo - Journal of Systems Architecture, 2025 - Elsevier
As an essential mathematical operation, GEneral Matrix Multiplication (GEMM) plays a vital
role in many applications, such as high-performance computing, machine learning, etc. In …
role in many applications, such as high-performance computing, machine learning, etc. In …
SMASH: Sparse matrix atomic scratchpad hashing
K Shivdikar - 2021 - search.proquest.com
In 1812, a French mathematician named Jacques Philippe Marie Binet pointed out several
important computations involved the multiplication of two matrices [53]. On November 30 of …
important computations involved the multiplication of two matrices [53]. On November 30 of …