This research demonstrates that applying custom, task-specific power limits to modern superchips is a highly effective strategy for saving significant amounts of GPU energy in high-performance computing.
High-performance computing systems consume vast amounts of energy, particularly when moving data between different parts of the machine. To address this challenge, a research team investigated a novel strategy for optimizing data transfers.
The Simplified Interface to Complex Memories (SICM) project delivers a powerful software solution that abstracts away the complexity of modern, multi-tiered memory systems.
The research team developed an intelligent, automated software solution that elegantly solves the complex problem of managing data in modern computers with multiple memory types.
This research introduces a data-efficient, AI-driven framework for making smarter scheduling decisions in High-Performance Computing.
Summary: Automation and autonomy can enable revolutionary scientific advances by coordinating a diverse array of experimental and computational capabilities more efficiently and more effectively than current hands-on approaches.
A multidisciplinary team of researchers from Oak Ridge National Laboratory (ORNL) and other institutions created a Machine Learning (ML) library for the training of classifiers on spectrographic chemical data.
A multidisciplinary team of researchers from Oak Ridge National Laboratory (ORNL) pioneered the use of the LLVM-based high-productivity/high-performance Julia language unifying capabilities to write an end-to-end workflow on Frontier, the first US Depar
A team of researchers from Oak Ridge National Laboratory (ORNL) released the initial draft of the Interconnected Science Ecosystem (INTERSECT) architecture specification.