Murali Emani is an Assistant Computer Scientist in the Data Science group with the Argonne Leadership Computing Facility (ALCF) at Argonne National Laboratory. Prior, he was a Postdoctoral Research Staff Member at Lawrence Livermore National Laboratory, US. Murali obtained a PhD from the Institute for Computing Systems Architecture at the School of Informatics, University of Edinburgh, UK under the guidance of Prof. Michael O'Boyle. His research interests are in Scalable Machine Learning, Runtime Systems, Emerging HPC architectures, Parallel programming models, High Performance Computing, Online Adaptation. Some of his current projects include:

• Developing performance models to identifying and addressing bottlenecks while scaling machine learning and deep learning frameworks on emerging supercomputers for scientific applications.
• Co-design of emerging hardware architectures to scale up machine learning algorithms.
• Efforts on benchmarking ML/DL frameworks and methods on HPC systems.

At ALCF, he co-leads the AI Testbed where we explore the performance, efficiency of AI accelerators for scientific machine learning applications. He chairs the MLPerf HPC group at MLCommons, to benchmark large scale ML on HPC systems.

More details of his work can be found at https://memani1.github.io