The UC Berkeley crew has now shown the value of AI-based optimization work by having OpenEvolve work out a more efficient approach to load balancing across GPUs handling LLM inference.
Abstract: Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...
The WIAA has a new playoff qualification system for high school football starting in 2025. Playoff spots are no longer guaranteed by conference wins but by a new points-based matrix. A team's score is ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
When you watch “The Matrix” at Cosm, you’re essentially seeing a film within a film. A shot inside an apartment becomes a glimpse into an entire complex. A fight scene on a rooftop is now one small ...
Element-wise multiplication in Python is a fundamental operation, especially when working with numerical data using libraries like NumPy. Understanding how to perform this efficiently is crucial for ...
Erick Massoto is a Brazilian writer who's always loved film and TV and loves finding connections between them. That's why he supports double features, especially if they are of a modern film paired ...
Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.
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