Abstract: We consider the distributed memory parallel multiplication of a sparse matrix by a dense matrix (SpMM). The dense matrix is often a collection of dense vectors. Standard implementations will ...

This issue is an evolving document describing the design and implementation of using sparse matrix instructions for optimizing skinny GEMM on AMDGPU in IREE. Using FP8 as an example: currently skinny ...

The sparse crowd at Target Field on Tuesday night was not hesitant about making its feelings known. As things went from bad to worse for the hometown team and the Minnesota Twins continued to fall ...

ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...

Abstract: Sparsification technology is crucial for deploying convolutional neural networks in resource-constrained environments. However, the efficiency of sparse models is hampered by irregular ...

Orthogonal Frequency Division Multiplexing (OFDM) is widely recognized for its high efficiency in modulation techniques and has been extensively applied in underwater acoustic communication. However, ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...