Hari Subramoni
Biography
Hari Subramoni received the Ph.D. degree in Computer Science from
The Ohio State University, Columbus, OH, in 2013. He is a research
scientist in the Department of Computer Science and Engineering at the
Ohio State University, USA, since September 2015. His current research
interests include high performance interconnects and protocols,
parallel computer architecture, network-based computing, exascale
computing, network topology aware computing, QoS, power-aware LAN-WAN
communication, fault tolerance, virtualization, big data, and cloud
computing. He has published over 50 papers in international journals
and conferences related to these research areas. Recently, Dr.
Subramoni is doing research and working on the design and development
of MVAPICH2, MVAPICH2-GDR, and MVAPICH2-X software packages. He is a
member of IEEE. More details about Dr. Subramoni are available from: http://www.cse.ohio-state.edu/~subramon
The Ohio State University, Columbus, OH, in 2013. He is a research
scientist in the Department of Computer Science and Engineering at the
Ohio State University, USA, since September 2015. His current research
interests include high performance interconnects and protocols,
parallel computer architecture, network-based computing, exascale
computing, network topology aware computing, QoS, power-aware LAN-WAN
communication, fault tolerance, virtualization, big data, and cloud
computing. He has published over 50 papers in international journals
and conferences related to these research areas. Recently, Dr.
Subramoni is doing research and working on the design and development
of MVAPICH2, MVAPICH2-GDR, and MVAPICH2-X software packages. He is a
member of IEEE. More details about Dr. Subramoni are available from: http://www.cse.ohio-state.edu/~subramon
Presentations
Workshop
W
Tutorial
Introductory
Networks
Photonics
TUT
Paper
Algorithms
MPI
Networks
TP
Workshop
Scalable MPI Collectives Using SHARP: Large Scale Performance Evaluation on the TACC Frontera System
W
Paper
Accelerators, FPGA, and GPUs
Machine Learning, Deep Learning and Artificial Intelligence
Scalable Computing
TP
Chair of Sessions