Neocortex Allocations

Allocation requests for Neocortex are accepted by the NSF ACCESS program on a rolling basis.

For further information on the type of projects encouraged to apply, see  the Neocortex documentation.

To see what kind of projects have been allocated, see the  Neocortex active projects page.

For specifics on the ML layers supported by the Cerebras hardware, see the Cerebras documentation.

Eligibility

Eligibility criteria to use this resource free of charge are as follows. Please contact us at neocortex@psc.edu if you have questions about your eligibility to apply.

• Projects must be non-proprietary.
• Applicants must be a researcher or educator at a US academic or non-profit research institution.
• A principal investigator (PI) is required. PIs may not be a high school, undergraduate or graduate student; a qualified advisor must serve in this capacity. Postdocs are eligible to serve as PI.

Successful applicants must agree to abide by the Neocortex Acceptable Use Policy in order to gain access and use the system.

Awardees are wholly responsible for conducting their research project activities and preparing results for publication. In a few cases, members of the Neocortex team can be available to collaborate in a more involved manner.

For more information about Neocortex, see the Neocortex home page.

Additional resources

• See information on Neocortex project tracks in the Supported Applications section of the Neocortex documentation.
• See a list of active projects on Neocortex
• See a list of former projects on Neocortex
• Check the Cerebras documentation

 Acknowledgment in publications

Please use the following citation when acknowledging the use of computational time on Neocortex:

Buitrago P.A., Nystrom N.A. (2021) Neocortex and Bridges-2: A High Performance AI+HPC Ecosystem for Science, Discovery, and Societal Good. In: Nesmachnow S., Castro H., Tchernykh A. (eds) High Performance Computing. CARLA 2020. Communications in Computer and Information Science, vol 1327. Springer, Cham. https://doi.org/10.1007/978-3-030-68035-0_15

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.