1 / 1

H igh Performance Machine Learning Using Java

This document explores high-performance machine learning techniques using Java and OpenMPI, focusing on MPI Allreduce and Ping-Pong benchmarks. We evaluate performance metrics with Infiniband, specifically analyzing the capabilities of algorithms such as Deterministic Annealing in vector sponge configurations. The study presents a comparative analysis between Charge5 and Charge2 in pairwise clustering procedures, providing insights into their efficiency and effectiveness in machine learning applications. This research is aimed at optimizing computational resources for large-scale data processing.

osric
Download Presentation

H igh Performance Machine Learning Using Java

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. H High Performance Machine Learning Using Java Java OpenMPI MPI Allreduce (top) and Ping-Pong (bottom) Benchmarks with Infiniband Deterministic Annealing Vector Sponge Charge5 (left) and Charge2 (right) Performance Deterministic Annealing Pairwise Clustering Performance

More Related