Large language models (LLMs), such as GPT-3, PaLM, and OPT, have dazzled the AI world with their exceptional performance and ability to learn in-context. However, their significant drawback is their ...
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: Sparse Matrix-Matrix Multiplication (SpMM) is a widely used algorithm in Machine Learning, particularly in the increasingly popular Graph Neural Networks (GNNs). SpMM is an essential ...
This project is for the course project of Parallel Programming in NYCU CSIE. We implement the sparse matrix multiplication Parallel Optimization in PyTorch extension. We also provide a benchmark tool ...
Is your feature request related to a problem? Please describe. I am not sure if I am doing something wrong but I am using scipy.sparse.csr_matrix object and contract it with a np.ndarray object using ...
A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. They are a crucial part of linear algebra and have various applications in fields like engineering, ...
Abstract: Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...
ABSTRACT: Embedded systems used in real-time applications require low power, less area and high computation speed. For digital signal processing, image processing and communication applications, data ...
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