Dec. 7, 2021 — In the latest episode of the Let’s Talk Exascale Podcast, Scott Gibson interviews Harry Yoo, Thomas Brettin, and Venkatram Vishwanath of Argonne National Laboratory and the CANDLE project. The podcast was published on December 7, 2021.
Hi and welcome to episode 91 of the Let’s Talk Exascale podcast. This is where we explore the efforts of the Department of Energy’s Exascale Computing Project—from the development challenges and achievements to the ultimate expected impact of exascale computing on society.
And this is the fourth in a series of episodes based on work aimed at sharing best practices in preparing applications for the upcoming Aurora exascale supercomputer at the Argonne Leadership Computing Facility.
The series is highlighting achievements in optimizing code to run on GPUs. We are also providing developers with lessons learned to help them overcome any initial hurdles.
This time we focus on the computer codes used in a project called CANDLE, which stands for CANcer Distributed Learning Environment. It is addressing three significant science challenge problems in cancer research, and we’ll hear about those shortly. The emphasis of the work is on machine learning and in particular builds on a single scalable deep neural network, or DNN, code that also bears the name CANDLE. The project is developing highly efficient DNNs optimized for the unique architectures provided by exascale-class computing platforms such as the upcoming Aurora and Frontier systems.
The CANDLE project is a collaborative effort with the U.S. Department of Energy and the National Cancer Institute (NCI), involving Argonne, Lawrence Livermore, Los Alamos, and Oak Ridge National Laboratories.
The guests for the program are Thomas Brettin, Venkatram Vishwanath, and Harry Hyunseung Yoo of Argonne National Laboratory and the CANDLE project.
Our topics: an overview of the project’s three challenges, how CANDLE will benefit from exascale computing systems, the role of ECP in CANDLE development, and more.
Link to listen and access a full transcript:
Source: Scott Gibson, Exascale Computing Project