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NESAP for Perlmutter

October 31, 2018 by Brandon Cook

 The National Energy Research Scientific Computing (NERSC) Center is now accepting applications from NERSC users for the NERSC Exascale Science Application Program (NESAP).

NESAP will partner with 25 simulation, data-intensive and machine learning applications to prepare workloads for the upcoming Perlmutter HPC system, which features both CPU and heterogeneous compute nodes, multiple NVIDIA accelerators per node, an all-flash file system and new Cray interconnect, code-named Slingshot, which is designed for data-centric computing. This call is open to applications with all levels of accelerator readiness.

  • NESAP for Simulations (N4S): Cutting-edge simulation of complex physical phenomena requires increasing amounts of computational resources due to factors such as larger model sizes, additional physics and parameter space searches. N4S enables simulations to make effective use of modern high-performance computing platforms by focusing on algorithm and data structure development and implementation on new architectures such as GPUs, exposing additional parallelism and improving scalability.

  • NESAP for Data (N4D):To answer today’s most complex experimental challenges, scientists are collecting exponentially more data and analyzing it with new computationally intensive algorithms.  N4D addresses data-intensive science pipelines that process massive datasets from experimental and observational science (EOS) facilities like synchrotron light sources, telescopes, microscopes, particle accelerators, or genome sequencers.  The goal is seamless integration and data flow between EOS facilities and supercomputing resources to enable scalable, real-time data analytics.

  • NESAP for Learning (N4L): Machine Learning (ML) and Deep Learning (DL)
    are powerful approaches to solving complicated classification, regression, and pattern recognition problems. N4L focuses on developing and implementing cutting-edge ML/DL solutions to improve the potential for scientific discovery arising from experimental or simulation data, or in high-performance computing (HPC) applications by replacing parts of the software stack or algorithms with ML/DL solutions.

Accepted teams will be partnered with resources at NERSC, Cray, and NVIDIA including access to:

  • NERSC Application Readiness staff assistance with code profiling and optimization
  • Collaboration with and assistance from NVIDIA and Cray engineers
  • Training sessions and hack-a-thons
  • Early access to GPU nodes on Cori
  • Early access to Perlmutter
  • Opportunity for a postdoctoral researcher to be placed within your application team (NERSC will fund up to 17 positions)

Selected teams will be responsible for:

  • Providing a benchmark problem & figure of merit on Edison (and Cori)
  • Designating a point of contact for their code team (committing a recommended 0.5 FTE of effort per year on NESAP and related accelerator focused application-performance activities)
  • Production of intermediate and final reports detailing science results and performance improvement

Submissions will be evaluated on:

  • Computing resource usage within DOE Office of Science
  • Representation within the 6 Programs in the Office of Science
  • Potential for scientific advancements
  • Potential for transfer of improvements to broader community
  • Resources available to augment NERSC/vendor resources
  • Commitment from team (FTEs, etc)

This call for proposals was open until December 18, 2018 12 PM PST and selections will be announced in February.  The call for proposals is now closed.

NERSC is also now accepting applications for NESAP Postdoctoral Fellowships!