J
Jay Lofstead
Researcher at Sandia National Laboratories
Publications - 93
Citations - 2057
Jay Lofstead is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Computer science & Scalability. The author has an hindex of 18, co-authored 79 publications receiving 1817 citations. Previous affiliations of Jay Lofstead include Georgia Institute of Technology & Illinois Institute of Technology.
Papers
More filters
Proceedings ArticleDOI
Flexible IO and integration for scientific codes through the adaptable IO system (ADIOS)
TL;DR: The Adaptable IO System provides an API nearly as simple as POSIX IO that also provides developers with the flexibility of selection the optimal IO routines for a given platform, without recompilation.
Journal ArticleDOI
Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks
Qing Liu,Jeremy Logan,Yuan Tian,Hasan Abbasi,Norbert Podhorszki,Jong Youl Choi,Scott Klasky,Roselyne Tchoua,Jay Lofstead,Ron A. Oldfield,Manish Parashar,Nagiza F. Samatova,Nagiza F. Samatova,Karsten Schwan,Arie Shoshani,Matthew Wolf,Kesheng Wu,Weikuan Yu +17 more
TL;DR: The startling observations made in the last half decade of I/O research and development are described, and some of the challenges that remain as the coming Exascale era are detailed.
Proceedings ArticleDOI
PreDatA – preparatory data analytics on peta-scale machines
Fang Zheng,Hasan Abbasi,Ciprian Docan,Jay Lofstead,Qing Liu,Scott Klasky,Manish Parashar,Norbert Podhorszki,Karsten Schwan,Matthew Wolf +9 more
TL;DR: PreDatA, short for Preparatory Data Analytics, is an approach to preparing and characterizing data while it is being produced by the large scale simulations running on peta-scale machines that enhances the scalability and flexibility of the current I/O stack on HEC platforms.
Proceedings ArticleDOI
Managing Variability in the IO Performance of Petascale Storage Systems
Jay Lofstead,Fang Zheng,Qing Liu,Scott Klasky,Ron A. Oldfield,Todd Kordenbrock,Karsten Schwan,Matthew Wolf +7 more
TL;DR: These measurements motivate developing a 'managed' IO approach using adaptive algorithms varying the IO system workload based on current levels and use areas, which achieves higher overall performance and less variability in both a typical usage environment and with artificially introduced levels of 'noise'.
Proceedings ArticleDOI
Adaptable, metadata rich IO methods for portable high performance IO
TL;DR: ADIOS is employed, the ADaptable IO System, as an IO API, which makes it possible to independently select the IO methods being used by each grouping of data in an application, so that end users can use those IO methods that exhibit best performance based on both IO patterns and the underlying hardware.