How Oak Ridge National Laboratory Helps Researchers and Scientists Reach the Summit

At GTC, hear from the bright minds at ORNL on how they are using high performance computing to solve some of the world’s most complex problems.
by Geetika Gupta

Supernova simulations. Deep learning for scientific discovery. Energy exploration. All of these disciplines are reaping the benefits of GPU-accelerated computing to unravel complex scientific problems.

At the GPU Technology Conference, taking place March 26-29 in San Jose, representatives from the Oak Ridge National Laboratory will be lending their expertise to attendees and sharing their experience building Summit, one of the world’s fastest supercomputers.

oak ridge national laboratory sign Here are the sessions hosted by ORNL team members you won’t want to miss:

Austin Harris – Accelerated Simulations of Stellar Explosions with FLASH Towards Exascale Capability

Using OpenACC and GPU-enabled libraries coupled to new NVIDIA GPU hardware capabilities, ORNL has improved the physical fidelity of simulations by increasing the number of evolved nuclear species by more than an order of magnitude. Hear about these and other performance improvements to the FLASH code on Summit.

Jack Wells – Enabling Large-Scale Science on Summit Through the Center for Accelerated Application Readiness

The Center for Accelerated Application Readiness within the Oak Ridge Leadership Computing Facility is a program to prepare scientific applications for next-generation supercomputer architectures. This presentation will highlight the progress made by the teams that have used Titan, the 27 petaflops Cray XK7 with NVIDIA Tesla K20X GPUs; SummitDev, an early IBM Power8+ access system with NVIDIA Tesla P100 GPUs; and since very recently, Summit, OLCF’s new IBM Power9 system with NVIDIA Tesla V100 GPUs.

Stephen Abbott – Exposing Particle Parallelism in the XGC PIC code by exploiting GPU memory hierarchy

See how careful mapping of field and particle data structures to GPU memory allowed Abbott’s team to decouple the performance of the critical electron push routine from size of the simulation mesh and allowed the true particle parallelism to dominate. This improvement enables performant, high-resolution, ITER-scale simulations on Summit.

Andreas Tillack – GPU-Accelerated Performance of QMCPACK on Leadership-Class HPC Systems Using CUDA and Cublas

QMCPACK is an open-source, massively parallel Quantum Monte-Carlo code enabling the accurate calculation of quantum many-body problems such as systems of atoms, molecules and even solids. They’ll demonstrate the implementation of a rank-k matrix update scheme leading to increased compute density and performance improvements up to 1.5-fold compared to the current rank-1 update at every step.

James Phillips – Petascale Molecular Dynamics Simulations on the Summit POWER9/Volta Supercomputer

Learn the opportunities and pitfalls of running billion-atom science at scale on a next-generation, pre-exascale, GPU-accelerated supercomputer. This talk will cover the latest NAMD performance improvements and scaling results on Summit and other leading supercomputers.

Jack Wells and Arjun Shankar – Scaling Deep Learning for Scientific Workloads on Summit

HPC centers have been traditionally configured for simulation workloads, but deep learning has been increasingly applied alongside simulation on scientific datasets. Hear examples of how deep learning workflows are being deployed on next-generation systems at the Oak Ridge Leadership Computing Facility.

Register to attend GTC today, see the entire HPC track at the conference and follow @NVIDIADC on Twitter to hear the latest in accelerated computing.