High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

Abstract: In this paper, we propose three modular multiplication algorithms that use only the IEEE 754 binary floating-point operations. Several previous studies have used floating-point operations to ...

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Gordon Scott has been an active investor and technical analyst or 20+ years. He is a Chartered Market Technician ...

As Transformer models continue to grow in size and complexity, numerous high-fidelity pruning methods have been proposed to mitigate the increasing parameter count. However, transforming these ...

Abstract: General sparse matrix-matrix multiplication (SpGEMM) is a fundamental computational method with wide-ranging applications in scientific simulations, machine learning, and image processing.

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