Parallel data management is a complex problem at large-scale HPC environments. The HPC I/O stack can be viewed as a multi-layered cake and presents an high-level abstraction to the scientists. While this abstraction shields the users from many of the I/O system details, it is very hard to obtain parallel I/O performance or functionality without understanding the end-to-end hierarchical I/O stack in today’s modern complex HPC environments. This talk will introduce the basic parallel I/O concepts and will provide guidelines on obtaining better I/O performance on large-scale parallel platforms.

Presenter

• Feiyi Wang (Oak Ridge Leadership Computing Facility)

Presenter Bio

Feiyi Wang received his Ph.D. in Computer Engineering from North Carolina State University (NCSU). Before he joined Oak Ridge National Laboratory as research scientist, he worked at Cisco Systems and Microelectronic Center of North Carolina (MCNC) as a lead developer and principal investigator for several DARPA-funded projects. His current research interests include high performance storage system, parallel I/O and file systems, fault tolerance and system simulation, and scientific data management and integration. Dr. Wang is a Joint Faculty Professor at EECS Department of University of Tennessee and a senior member of IEEE.