Carnegie Mellon University

Hands-on Virtual Training - Getting Ready to Use the Neocortex System

This training is available to Neocortex Early User Program (EUP) users exclusively.

Session 1 presented on Tuesday, December 8, 2020, 11:00 - 1:00 pm (ET), 
Session 2 presented on Thursday, December 10, 2020, 11:00 - 1:00 pm (ET)

Training presented by Natalia Vassilieva, Ph.D. (Cerebras Systems Inc.)

In this hands-on virtual training, we offer the Neocortex Early User Program (EUP) users access to an environment where they can compile their code with Cerebras specific tools and can also produce metrics that would inform the approach to optimally execute their code on the Cerebras CS-1 servers available in the Neocortex system. Users are also presented with sample models that can inform their own model development and instructed on the resources available to advance EUP preparatory activities.

Access the recording, slides, and other content related to this training available to EUP users via the designated Box folder.

Abstract

The Cerebras CS-1 is the groundbreaking specialized AI hardware technology to be featured on Neocortex, PSC’s upcoming NSF-funded AI supercomputer. This 2-hour hands-on training session is designed for users selected for the Neocortex EUP. The training focuses on subjects including learning how to prepare existing code for running on the Cerebras CS-1 servers. That training explored how to make the codebase of the EUP groups compatible with the Cerebras compiler, as well as how to calculate key performance aspects such as the theoretical max throughput for optimal code execution.

This training involves hands-on running DL models on the proxy compiling environment. An overview of the subjects covered is presented next:
  1. Outline of the Cerebras software stack and Neocortex execution model.
  2. Deep dive into a relevant Cerebras specific API with a detailed description of various functions and parameters.
  3. Training a simple MNIST model with Cerebras specific API.
  4. Evaluating the execution on CPU and GPU sample nodes.
  5. Resources for using TF and the Cerebras estimator.

Access the recording, slides, and other content related to this training available to EUP users via the designated Box folder.

About the Instructor

Natalia Vassilieva, Ph.D., (Cerebras Systems Inc. | Computer Scientist )

Dr. Vassilieva is a Sr. Technical Product Manager at Cerebras Systems, an innovative computer systems company dedicated to accelerating deep learning. Natalia’s main interests and expertise are in machine learning, artificial intelligence, analytics, and application-driven software-hardware optimization and co-design. Prior to Cerebras, Dr. Vassilieva was affiliated to Hewlett Packard Labs where she led the Software and AI group from 2015 till 2019 and served as the head of HP Labs Russia from 2011 to 2015. From 2012 to 2015, Natalia also served as a part-time Associate Professor at St. Petersburg State University and a part-time lecturer at the Computer Science Center, St. Petersburg, Russia. Before joining HP Labs in 2007, Natalia worked as a Software Engineer for different IT companies in Russia from 1999 till 2007. Natalia holds a Ph.D. in Computer Science from St. Petersburg State University.

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