Scholar
Edgar A. Leon
Google Scholar ID: srZuWIAAAAAJ
Computer Scientist, Lawrence Livermore National Laboratory
Citations & Impact
Citations
276
H-index
10
i10-index
10
Publications
20
Co-authors
11
list available
Contact
No contact links provided.
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published multiple papers, including 'Providing Cross-Architecture Affinity of Parallel Applications on Emerging Systems' at ISC 2019, 'Mapping Parallel Scientific Applications onto Complex Architectures Portably and Efficiently' at PASC 2019, and 'Achieving Transparency Mapping Parallel Applications: A Memory Hierarchy Affair' at MEMSYS 2018. Also received Best Paper Awards at INFOCOMP 2018 and HPDC 2017 (Karsten Schwan Best Paper Award).
Research Experience
- Currently conducts research on power-aware computing, emerging memory technologies, system noise, and resilience for exascale machines at Lawrence Livermore National Laboratory. Was a member of the Novel Systems Architecture group at IBM Research working on performance analysis and optimization for PERCS systems. Before IBM, worked for Sandia National Laboratories where he developed a scalable simulation environment to study the impact of novel architectures on the performance of MPI applications. Interned at IBM T. J. Watson Research Center and Intel Santa Clara Engineering Computing during his graduate work.
Education
- Received M.S. and Ph.D. degrees in computer science from the University of New Mexico (UNM) under the supervision of Dr. Arthur B. Maccabe. In his dissertation, he evaluated the impact of cache injection of incoming network messages on parallel application performance and collective operations to address the memory wall for I/O. For his master's thesis, he created a tool to measure parallel application sensitivity to variation in communication parameters based on the LogGP model of computation.
Background
- Research interests: Operating systems, distributed systems, networks, and computer architecture. In particular, identifying and addressing software challenges posed by emerging architectures in regards to performance, power, and usability. Research areas include performance analysis of parallel applications; high-performance communication interfaces and protocols for system area networks; and simulation of cluster systems.
