Post-Webinar - Neocortex Overview and Upcoming Call for Proposals
Presented on Monday, October 4, 2021, 2:00 - 3:00 pm (ET), by Paola Buitrago, Director of Artificial Intelligence and Big Data at the Pittsburgh Supercomputing Center (PSC), and Natalia Vassilieva, Ph.D. (Cerebras Systems Inc.).
This webinar gives an overview of Neocortex, a deployed NSF-funded AI supercomputer at PSC. Neocortex, which captures groundbreaking new hardware technologies, is designed to accelerate AI research in pursuit of science, discovery, and societal good. Join us to learn more about this exciting new system and how to be part of the next group of users. Neocortex has been deployed at the PSC early 2021 and currently supports research in drug discovery, genomics, molecular dynamics, climate research, computational fluid dynamics, signal processing and medical imaging analysis. For more information about Neocortex, please visit https://www.cmu.edu/psc/aibd/neocortex/.
Table of Contents |
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00:00 - Welcome |
Q&A
Could you post the link to the PEARC talk?
What does it mean the cores are AI optimized in terms of the architecture of the cores?
What's the proposal acceptance rate? Does the system support pipeline managers like Nextflow, Airflow etc?
Can LAIR be used to write programs that are not Tensorflow or Pytorch based?
Is any way to try the system before submitting the proposal and is there any preliminary data needed for the application
When I adopt my TF-based application for running on PSC with Cerebras, what changes do I need to make?
While programming Deep learning models, should we treat this as one big machine (akin to a GPU) with 18GB of memory or should we treat it as thousands of machines with very fast interconnect each with a small memory? I.e. Can we go to very large batch sizes or do we need to stick to small batch size but expect that the communication overload is small?
Can we submit proposals about studying/optimizing parallel deep learning performance itself? (So not about using Neocortex to run actual scientific workloads but more about benchmarking and developing performance models)
Yes, those proposals are also welcomed. We already have a couple of projects that would classify under this category. It is worth considering that a project of this nature requires a very close and involved collaboration between PSC, vendors, and the project members. It is for this reason that the number of projects of this kind that we are supporting can be limited.