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

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 ...

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 ...

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 ...

Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.