Summit supercomputer simulation shows principle of Laser Wakefield Electron Acceleration, a laser pulse that forms an electron plasma wave
In advance of the scheduled shipment this year of the U.S.’s first exascale supercomputer, Frontier, at Oak Ridge National Laboratory, an international team of software developers led by a University of Delaware professor is working on a plasma physics application.
An article published yesterday in the university’s UDaily by Tracey Bryant details the work underway by UD’s Sunita Chandrasekaran, assistant professor of computing and information sciences, along with her team, which is one of eight working on applications for Frontier, an HPE-Cray system powered by AMD CPUs and GPUs.
The plasma physics application under development, PIConGPU (Particle in Cell), is designed to rapidly generate simulations for next-generation plasma (particle) accelerators, critical to advancing radiation therapies for cancer and to expanding the use of X-rays to probe the structure of materials.
“Dr. Chandrasekaran’s PIConGPU team is an elite group spanning many geographic regions, scientific domains and backgrounds,” said Dr. Nicolas Malaya, technical lead from Advanced Micro Devices (AMD) for the Exascale Centers of Excellence. “I fully expect this application to generate important scientific results from this team in computational science, supercomputing and plasma physics.”
Bryant’s article includes a Q&A with Chandrasekaran, here are excerpts:
Q: How is the project going?
Chandrasekaran: Pretty fantastic. We are thrilled to have gotten access to the new AMD Instinct MI100 (data center GPU) accelerator cards. We ran the full PIConGPU on these newly released cards, and in our studies using a single GPU, we observed a 1.4 times increase in speed compared to MI60. This is promising and gives us a lot to look forward to, for the next-generation CPUs and GPUs for Frontier.
AMD Instinct MI100 GPU
The team is using accelerator cards like this from Advanced Micro Devices (AMD) to speed the processing of plasma simulations and perform other intensive calculations.
Q: In looking at these two supercomputing titans, how do you compare Frontier’s speed to Summit’s?
Chandrasekaran: Chatting with my collaborator, Dr. Alexander Debus (head of the Center for Advanced Systems Understanding [CASUS] at HZDR, a research laboratory based in Germany) helped me make some observations — simulations like ours with PIConGPU that would take two months on Summit might end up taking one week on Frontier. This also means we would now be able to run several 10-million time-step simulations on Frontier (each time step would take ~50 milliseconds). Time-step simulations allow us to analyze the operation of the computer’s power system from hour-to-hour intervals, right down to thousandths of a second.
Q: Who are your collaborators and what is it like coalescing an international team?
Chandrasekaran: My collaborators are from ORNL, HZDR, CASUS, and the Georgia Institute of Technology. I have not met half of my team in person, yet it feels like we have been working together for years. We are now a small family. Please see this webpage for details.
Prof. Sunita Chandrasekaran
Once every few months, we make sure to discuss the team’s, as well the project’s, common vision and goals to ensure the short- and long-term goals align well with CAAR (cost analysis and resolution) deliverables. This is particularly important for an international team like ours. Most of the conversations and discussions are hashed out over email/Slack prior to scheduling a group phone call, given that there are more than a few hours of time difference between the U.S. and Germany.
Q: What is the most exciting/rewarding aspect of the project for you?
Chandrasekaran: I believe it is the interdisciplinary component of this project. It is intriguing to think about applying computer science concepts to a real-world scientific application. I am also thrilled that our close collaborations have led to this project being funded by Dr. Michael Bussmann (CASUS at HZDR, Germany). This is my first internationally funded collaborative project.
Q: What are the areas where Frontier is poised to have the greatest impact? Do you expect Frontier to help advance future virus research, for example?
Chandrasekaran: I believe so, especially when we are in the phase of integrating high-performance computing (HPC), artificial intelligence (AI) and data science. Large-scale (and fast) simulations that couldn’t be imagined just a few years ago are now going to become possible with the massive compute resources that Frontier is going to offer. Not just virus research, but such compute capabilities are of paramount importance to studies like finding a cure for Alzheimer’s disease or studying climate change.
Q: How are UD students contributing to the effort?
Chandrasekaran: My Ph.D. student, Matt Leinhauser, has been working on this project since its inception. With mentorship from myself and my CAAR team (especially Rene Widera, Sergei Bastrakov and former CAAR liaison Ronnie Chatterjee), Matt has been able to put together two technical documents on profilers — these are tools that identify portions in the computer program that take the most computation time. We have so far used NVIDIA’s nvprof and Nsight profiler tools to dive deeper into the code. HZDR also invited Matt to spend last winter (January 2020) with them, which was a rewarding opportunity when he was still in his first year of the Ph.D. program.
Q: What’s on the horizon?
Chandrasekaran: With support from the Frontier Center of Excellence team, we will be marching forward to port PIConGPU on the early access systems and preparing the application for Frontier, which is being built as we speak. As next steps, we will be working on optimizing PIConGPU on the early access systems and speeding up the simulations even further.
