New NESAP Teams Start Prepping Applications for Next-Generation Perlmutter Architecture

The National Energy Research Scientific Computing (NERSC) Center has announced the latest round of NERSC Exascale Science Application Program (NESAP) teams that will focus on simulation, data analysis, and machine learning applications to prepare workloads for NERSC’s next supercomputer, Perlmutter.

Perlmutter, a pre-exascale Cray Shasta system slated to be delivered in 2020, will feature a number of new hardware and software innovations and is the first supercomputing system designed with both data analysis and simulations in mind.

“It is crucial that our broad user base can effectively use the Perlmutter system to run applications and complex workflows,” said Katie Antypas, NERSC Division Deputy and project director for Perlmutter. “We will have a large user engagement, training and readiness effort for simulation, data and learning applications. In addition, new software developed by the Exascale Computing Project will be deployed and supported on the new system.”

NESAP provides researchers an opportunity to prepare application codes for new architectures and to help advance the mission of the Department of Energy's Office of Science. NESAP partnerships allow projects to collaborate with NERSC and HPC vendors by providing access to early hardware, prototype software tools for performance analysis and optimization, special training and exclusive hack-a-thon events with vendor and NERSC staff.

Through NESAP, the participating teams will consider applications in three primary areas:

• 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-analysis 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 Perlmutter to enable scalable, real-time data analytics utilizing the GPU architecture on Perlmutter.
• NESAP for Learning (N4L): Machine learning and deep learning are powerful approaches to solving complicated classification, regression, and pattern recognition problems. N4L focuses on developing and implementing cutting-edge machine/deep learning solutions to improve the potential for scientific discovery arising from experimental or simulation data, or in HPC applications by replacing parts of the software stack or algorithms with machine/deep learning solutions optimized for the Perlmutter system and GPU architecture.

The accepted teams are being paired 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)

“We’ve built up a team of application-performance experts at NERSC through the NESAP process for Cori, and we are all really excited to engage a new set of application teams around preparing and optimizing codes for Perlmutter,” said Jack Deslippe, NERSC’s application performance group lead. “As the HPC community transitions to exascale like energy-efficient architectures, the goal of NESAP is to make sure that our user community is poised to make the most of the opportunities that come with new systems like Perlmutter.”

Brandon Cook, an application performance specialist at NERSC, described some of the opportunities and challenges in optimizing applications for Perlmutter. “Perlmutter is a really exciting system that offers the opportunity to accelerate scientific discovery,” he said. “However, taking advantage of all the new features Perlmutter has to offer while maintaining a productive and portable code base is a big challenge for the scientific community. At NERSC, we’re building a strategy to help users move their codes forward portably and productively to make the most out of Perlmutter and to position them for the coming exascale systems and beyond.”

Below are the NESAP teams and the applications they will focus on. Tier 1 teams will have access to the full list of resources described above, while Tier 2 teams will have access to the listed resources with the exception of eligibility for a postdoctoral researcher and a commitment of NERSC application readiness staff time.

Tier 1

           PI                       Institution              Project Name             Project Category

 Tier 2

           PI                 Institution                Project Name                Project Category