High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...
Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...
Discover how Markov chains predict real systems, from Ulam and von Neumann’s Monte Carlo to PageRank, so you can grasp ...
Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.
Matrix multiplication is expensive O(n^3) operations! But what if we could verify the result without doing the full computation? I implemented Freivalds' algorithm in C to probabilistically verify ...
Abstract: High-dimensional and incomplete (HDI) matrices are commonly encountered in various big data-related applications for illustrating the complex interactions among numerous entities, like the ...
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 ...
Abstract: Real-time movie recommendation systems must efficiently handle large amounts of sparse user-item interaction data while maintaining great prediction accuracy. Conventional collaborative ...
WAIKOLOA, Hawaii — In a panel discussion at Orthopedics Today Hawaii, Aaron J. Krych, MD, reviewed three papers on meniscus tears published in 2025 that have impacted his practice.
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