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 ...
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
Abstract: In this paper, we report on the development of an efficient GPU implementation of the Strassen-Winograd matrix multiplication algorithm for matrices of arbitrary sizes. We utilize ...
Discover eight practical ways to multiply in Excel, from basic formulas to advanced tips. Perfect for beginners and Excel enthusiasts looking to improve efficiency. #ExcelTips #ExcelTutorial ...
No single solution universally wins between Large Language Models (LLMs, ≥30B parameters, often via APIs) and Small Language Models (SLMs, ~1–15B, typically open-weights or proprietary specialist ...
You can now order an “Iron Dome” for mosquitoes. Its name is the Photon Matrix, a black box about the size of a smartphone that can detect, track, and eliminate mosquitoes mid-flight using an ...
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 ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...
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