High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...
Imagine driving down a busy highway. You need to check your speed and navigation, but glancing down at the dashboard takes ...
New computational holography algorithms cut processing time by over half and enable multi-depth augmented reality displays, a ...
A new holographic computation method could significantly advance augmented‑reality head‑up displays (AR‑HUDs) for vehicles.
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 ...
Discover how Markov chains predict real systems, from Ulam and von Neumann’s Monte Carlo to PageRank, so you can grasp ...
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: Resistive RAM (RRAM) technology has emerged as a viable candidate for artificial intelligence and machine learning applications due to its matrix multiplication capability through in-memory ...
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