The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL), home to the world’s fastest supercomputer, just installed two NVIDIA DGX-2 systems for use in machine learning tasks.
“[The] powerful GPU-accelerated appliances will provide ORNL researchers with enhanced opportunities to conduct science—machine learning and data-intensive workloads,” the ORNL team wrote in a blog post.
The new machines will help ORNL researchers test their projects before running them on the 200 petaflop Summit supercomputer.
“As Summit enters production, these DGX-2 systems supply ORNL with exploratory multipurpose computing resources,” said CADES director Arjun Shankar. “Early results suggest the [NVIDIA] DGX-2s will provide novel opportunities in data analysis, machine learning, and modeling and simulation that support the AI-driven transformation that is changing how science is conducted.”
In today’s blog post, the ORNL team describes how a staff scientist at the organization trained and optimized reinforcement learning algorithms on the new machines for cancer research. By running the algorithms on the NVIDIA DGX-2 systems, the team was able to develop software at a fraction of the time it would have taken on another system.
“We couldn’t have done this without a DGX-2 because the problem space that we were exploring was so large and sample inefficient,” said Arvind Ramanathan, a staff scientist in ORNL’s computer science and engineering division. “Because these GPUs can essentially be used in a unified way, we can do things that are much more difficult to do on other systems, especially in terms of moving data and doing analysis.”