Welcome to the Neocortex User Portal

Last updated: 2023-09-13.

Neocortex - CS IP Addresses

We recommended using the system variable ${CS_IP_ADDR} instead of the actual CS machine IP address every time you need that value. For example when specifying the --cs_ip flag value when running jobs.

Good: --cs_ip ${CS_IP_ADDR}

Not recommended: --cs_ip 1.2.3.4

Please feel free to contact us at neocortex@psc.edu for any questions.

Current Goals/Action Items

  • Go over the "Getting Ready to Use the Neocortex System" training files, available under the "Resources" section below.
  • Submit and successfully execute a training job in the CS-2 servers (following instructions in the "Getting Ready to Use the Neocortex System" training files.
  • Use Bridges-2 to gather the metrics required as described in the "Key Compilation Metrics Needed" section below.
  • Share the key compilation metrics with the Neocortex team and gain full access to the SDFlex and the CS-2 servers.
  • Reserve a spot here for a project checkpoint session, as needed.

Resources:

  • The Neocortex System Slack Organization is now available. Please feel free to join if you want to communicate with other project team members through Slack.
  • The Neocortex Documentation. This is a living document. It has detailed instructions on how to use the Neocortex system, including step-by-step examples for training MNIST on the CS-2s and compiling code on either Neocortex or Bridges-2.
  • Cerebras Systems Overview: Cerebras whitepaper on the CS-2 system and environment.
  • Cerebras Model Zoo R_1.6.0: GitHub repository with the Cerebras modelzoo. It includes sample models in TensorFlow ready to run on the CS-2.
  • Research Plan: We ask you to generate the key metrics values and a research plan for your Neocortex application before we grant you complete access to your Neocortex system allocation. For the key metrics, please follow the instructions below to port your own code and compile it to generate key metrics values. This will verify that your team is ready to successfully run your applications on the CS-2.
  • Getting ready to use the Neocortex system training:
  • Previous Trainings
    • Webinar - Neocortex: CS-2 Overview. 2022-03-29
  • Cerebras Documentation version 1.6.0: Cerebras documentation portal with information about the CS-2, conceptual guides, step-by-step tutorials, best practices, release notes and FAQs. Please note that some instructions might not be directly applicable to the Neocortex system because of a different setup with SDFlex and slurm configuration.
  • Cerebras Discourse forum: Feel free to use the Cerebras Discourse platform to ask short or open-ended questions that will be visible to the whole community, similar to Quora or Stack Overflow. A registration is needed, but Neocortex users should be enabled to access the platform without problems.
  • Cerebras Developer Blog

As a reminder, the compute resources you have access to right now are:

  • Bridges-2 GPU partition
  • Bridges-2 GPU-AI partition
  • Bridges-2 EM partition
  • Bridges-2 RM partition
  • Ocean file system
Once you share the "Key Compilation Metrics" for your code, your team would gain access to:
  • Neocortex SDF partition
  • Neocortex CS-2 partition
Please complete the "Getting ready to use the Neocortex system" training and submit the "Key Compilation Metrics Needed" form to get full access to the Superdome Flex and CS-2s systems.

Note: You can get more details regarding your allocation by running the projects command.

Key Compilation Metrics Needed for ML/AI Projects

Before using the CS-2 and SDFlex servers, we ask that you collect representative key metrics from your dataset and your model. These metrics help inform the Neocortex program and also signal that your code is ready to be executed on the Cerebras systems. To learn how to capture these metrics, please visit the section Compilation key metrics to share in the Documentation.

We invite you to record the following metrics by using the Neocortex Project Key Metrics file and submitting it to the Key-compilation-metrics Submit Box link:

  1. Ratio of utilized components (as indicated in the Documentation).
  2. Cycles per sample (as indicated in the Documentation).
  3. Data sample size (in MB or GB).
  4. Number of samples in the training dataset.
  5. Maximum expected batch size (in number of samples or another representative).

Please use the Bridges-2 supercomputer to obtain these values. Remember to find instructions on measuring these numbers in the documentation.

The Neocortex team