Neocortex Spring 2024 Workshop

Presented on March 29, 2024, by Mei-Yu Wang, PhD., Machine Learning Research Scientist, and Julian Uran, Machine Learning Research Engineer, of the Pittsburgh Supercomputing Center’s AI & Big Data Team.

This webinar was presented as a part of the ByteBoost program, and provides a system overview of Neocortex, an AI-specialized NSF-funded supercomputer deployed at PSC/CMU.

For more information about Neocortex, explore the Neocortex project page. For questions about this webinar, please email neocortex@psc.edu.

Important dates and deadlines

Application begins: March. 15, 2023
Application ends: April 19, 2023 (Anywhere on earth time zone)
Response ends: May 10, 2023

Neocortex User Guide

Large-Scale Evolution Simulations on PSC’s Neocortex Tackle Questions about Hypermutator Evolution

Vastly Expanded Populations Allowed by Wafer-Scale Engines Help Pinpoint Factors that Can Allow Hypermutators to Take Over

Parkinson’s Research, Evolution of Vocalization, AI Training Tool, and National AI Collaboration Underlie Four HPCwire Awards to PSC

High Performance Computing Achievements Recognized by Peers, Editors of Leading Trade Press Magazine at SC24 Conference in Atlanta

ByteBoost Workshop: Accelerating HPC Skills and Advancing Computational Research

Student Projects Tackle Challenges in Drug Discovery, Congressional Policy, Coordinating Heavy Air Traffic, and More

Dana O’Connor – MCS Senior Rookie Awardee

Dana O’Connor, Machine Learning Research Scientist, talks about her recent Senior Rookie award and her work at PSC.

PSC’s Bridges-2 Joins Neocortex Among Elite Artificial Intelligence Computers Allocated through National NAIRR Pilot Project

The Pittsburgh Supercomputing Center’s Bridges-2 supercomputer is now available to scientists through the National AI Research Resource (NAIRR) Pilot Project.

Neocortex Office Hours

Wednesdays, 2-3 EST. Learn more

Contact us

Email us at neocortex@psc.edu

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Join the Neocortex-updates mailing list

This material is based upon work supported by the National Science Foundation under Grant Number 2005597. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.