Abstract: Convolution neural networks (CNNs) have been extensively used in machine learning applications. The most time-consuming part of CNNs are convolution operations. A common approach to ...

CUDA-L2 is a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels. CUDA-L2 ...

The Wachowskis once asked Hideo Kojima to make a Matrix game, but Konami said no, and history ended up taking a very different turn. By the late 1990s, Hideo Kojima was one of Konami’s most valuable ...

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Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Department of Chemistry and Research Institute for Natural Science, Korea University, Seoul 02841, Korea ...

Introduction: In recent years, lots of computational models have been proposed to infer potential lncRNA-disease associations. Methods: In this manuscript, we introduced a novel end-to-end learning ...

A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...

Reinforcement learning was tested as a means of improving liquid chromatography method development. KU Leuven and Vrije Universiteit Brussel researchers led efforts to improve deep reinforcement ...

Packing for a trip can be equally exciting and overwhelming. It's a real challenge to efficiently distill a closet full of clothes into a practical travel wardrobe without overpacking (a task loaded ...