A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...
This project provides a massively parallel implementation of a Minimum Spanning Tree (MST) graph algorithm using NVIDIA CUDA. The implementation is based on Borůvka's algorithm, which is highly ...
Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...
A hybrid retrieval-augmented generation (RAG) system for educational content, specifically designed for the CDER Parallel and Distributed Computing curriculum. This system integrates Neo4j knowledge ...
Abstract: We present SNAP (Small-world Network Analysis and Partitioning), an open-source graph framework for exploratory study and partitioning of large-scale networks. To illustrate the capability ...
A startup named TigerGraph emerged from stealth today with a new native parallel graph database that its founder thinks can shake up the analytics market. With $31 million in venture funding and ...
Abstract: This paper proposed a timescale graph-parallel (GP) computation method to solve the real-time optimization problem of nonlinear predictive energy-saving control, thus to realize the ...
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