Dr. Dorian Arnold,
Professor, UNM Dept of Computer Science, University of New Mexico
Dorian is an assistant professor in the Department of Computer Science at the University of New Mexico. His research focuses on the performance and reliability of extremely large scale systems with tens of thousands, hundreds of thousands or even millions of processing elements.
Dorian is working with Mike Lang, Hugh Greenberg and the USRC Systems Group on the Redfish Project. This group investigates the basic, general computation, communication and storage primitives that underlie HPC system services and provide a library of building blocks that provides a flexible, resilient and scalable implementation of these primitives.
Dr. Patrick Bridges,
Assistant Professor in Computer Science, University of New Mexico
Patrick Bridges is an Assistant Professor of Computer Science at UNM. He received his PhD (2002) from the U of Arizona and his BS (1994) from Mississippi State University. Patrick is co-director of the UNM Scalable Systems Laboratory, where his research is focused on configurable high-performance system software, including HPC operating systems and MPI implementations, lightweight performance monitoring systems, and adaptation in system software. Much of his recent research in this area has been supported by and done in collaboration with researchers at Sandia National Labs
Dr. David Du,
Professor, UMN, Dept of Computer Science & Engineering, University of Minnesota
Dr. Du has a wide range of research expertise including multimedia computing, mass storage systems, high-speed networking, sensor networks, cyber security, high-performance file systems and I/O, database design, and CAD for VLSI circuits.
Dr. Du worked on integrating new storage devices like flash-memory based Solid State Drives (SSD) or Phase-Change Memory (PCM) into the existing memory/storage hierarchies to deal with the scale ability of the future exascale computing. He is also interested in how to use these new storage devices to efficient solving large scale computing problems like checkpointing/restart.
Dr. Song Fu,
Assistant Professor in Computer Science and Engineering, University of North Texas
Song Fu is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas. His research focuses on reliability and energy efficiency of parallel and distributed systems. Song works with Nathan DeBardeleben, Mike Lang, and the USRC Systems Group on resilience, fault tolerance, and power management of ultra-scale computers. The goal is to reduce the vulnerability of HPC applications and systems to soft errors and failures and to improve power utilization to maximize machine room throughput.
Dr. William M Jones,
Associate Professor and Chair, Coastal Carolina University
Will is an associate professor and chair of the Department of Computing Sciences at Coastal Carolina University (CCU). He attended Clemson University where he obtained a BS ('99), MS ('00) and PhD ('05), each in Computer Engineering. Before accepting a position at CCU, Will was an assistant professor in the Department of Electrical and Computer Engineering at the United States Naval Academy, as well as an adjunct professor at Clemson University in the ECE department and at Tri-County Technical College in the Department of Mathematics. His research interests include parallel computing, parallel file systems, computational grids, job scheduling, resilience, fault injection, performance evaluation and modeling, and discrete event simulation. In addition to traditional computer science courses, he also enjoys teaching computer architecture, digital logic design, FPGA programming and AC/DC circuit analysis. Will has been investigating the behavior of ABFT algorithms in the presences of hardware and memory faults through the use of F-SEFI, a soft error fault injector. This work has been in collaboration with Claude Davis, a Clemson University master's student, CCU student Scott Lavigne, a CS undergraduate, along with several members of the HPC-5 group, including Nathan DeBardeleben, Laura Monroe, Sean Blanchard, and Qiang Guan.
Dr. Carlos Maltzahn,
Associate Adjunct Professor Computer Science Dept, UC Santa Cruz
Carlos’ current research interests include scalable scientific data management, storage QoS, data management games, network intermediaries, information retrieval, and cooperation dynamics. As a Visiting Scientist at USRC, Carlos worked with students on their Ph.D. projects, including scalable parallel querying of scientific data, scalable map/reduce processing of scientific data, scalable simulation of parallel file systems, and predictable performance in very large storage systems. A high priority goal for him is to form collaborative projects with USRC scientists and get those collaborations funded.
Dr. Adam Manzanares,
Assistant Professor, California State University, Chico
Adam Manzanares is currently an assistant professor at the California State University, Chico. Prior to that, Adam was a Nicholas C. Metropolis postdocgtoral fellow at the Los Alamos National Laboratory (LANL). He received his Ph.D. from Auburn University in May 2010 where he worked on energy efficient storage systems.
At USRC, Adam focuses on storage systems for high performance computing (HPC) applications. Adam develops middleware layers to improve the performance of HPC storage systems. He is also currently researching compression techniques and data formatting libraries for scientific data sets.
Dr. Satyajayant Misra,
Assist Professor, Computer Science Dept, New Mexico State University
Dr. Satyajayant Misra’s research interests are anonymity, security, and survivability in wireless sensor networks, wireless ad hoc networks, and vehicular networks. He is also interested in the design of algorithms for energy harvesting wireless sensor networks and to support real time and multimedia communication in wireless networks. Dr. Misra works with USRC on resilience, fault tolerance, and load balancing in ultra-scale supercomputing architectures. He concentrated on optimization of service placement in supercomputing networks under various operating constraints. His primary goal was to improve system utilization, resilience, fault-tolerance and reduce system bottlenecks.
Dr. Ioan Raicu,
Assistant Professor in Computer Science , Illinois Institute of Technology
Dr. Ioan Raicu is an assistant professor in CS at Illinois Institute of
Technology, as well as a guest research faculty in MCS at Argonne
National Laboratory. He is also the founder (2011) and director of the
Data-Intensive Distributed Systems Laboratory at IIT. His research work
and interests are in the general area of distributed systems. His work
focuses on a relatively new paradigm of Many-Task Computing (MTC), which
aims to bridge the gap between two predominant paradigms from
distributed systems, High-Throughput Computing (HTC) and
High-Performance Computing (HPC). His work has focused on defining and
exploring both the theory and practical aspects of realizing MTC across
a wide range of large-scale distributed systems. He is particularly
interested in resource management in large scale distributed systems
with a focus on many-task computing, data intensive computing, cloud
computing, grid computing, and many-core computing. Dr. Raicu has been
working with Mike Lang for several years co-mentoring graduate students
on exploring extreme-scale simulations in distributed services. The
projects include exploring the scalability of distributed NoSQL
key/value storage systems with different architectures, and distributed
job-launch and scheduling through work-stealing for both MTC and HPC
Dr. Paolo Rech,
Associate Professor, UFRGS
Paolo Rech received his master and Ph.D. degrees from Padova University, Padova, Italy, in 2006 and 2009, respectively. He is currently an associate professor at the Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil.
His main research interests include the evaluation and mitigation of radiation induced effects in large-scale HPC centers and safety-critical applications. Paolo lead the group that performed the first radiation experiment on GPUs in 2011. Since then, he has been studying the effects of radiation in parallel HPC devices. Now, he is collaborating with NVIDIA and AMD to evaluate and enhance the reliability of modern architectures. In collaboration with LANL and USRC he is designing experimentally-tuned selective hardening strategies to detect critical SDCs without unnecessary overhead. Lately, Paolo has been working on automotive applications reliability, understanding the error propagation in neural networks and designing novel hardening solutions for embedded safety critical applications.