The Parallel Systems Group carries out research to facilitate the use of extreme scale computers for scientific discovery. We are especially focused on tools research to maximize the effectiveness of applications running on today’s largest parallel computers. Our expertise includes performance measurement, analysis, and optimization in addition to debugging and power optimization. We also have expertise in existing and new programming models, power-aware supercomputing, fault tolerant computing, I/O, and numerical kernel optimization.
Group Lead
Kathryn Mohror: performance measurement and analysis, fault-tolerance, scalable tools, high performance storage and I/O
Research Staff
Michael Barrow: video rate computer vision, power efficient embedded systems, efficient multi-agent AI
Kshitij Bhardwaj: heterogeneous systems-on-chip, hardware accelerator design, system optimization using machine learning, reconfigurable computing, and on-chip interconnection networks
David Boehme: performance analysis tools, performance optimization, parallel and distributed architectures, parallel programming paradigms
Stephanie Brink: performance analysis tools, performance optimization, power-aware HPC, low-level power management and control
Hariharan Devarajan: high performance storage and I/O, storage for AI, heterogeneous storage architectures, composable storage architecture, and performance measurement and analysis tools
Giorgis Georgakoudis: program analysis, compiler optimization (Clang/LLVM), parallel programming models and runtimes, performance analysis and tuning, fault tolerance
Maya Gokhale: data intensive computing, reconfigurable computing, co-processor accelerators, HPC architectures
Marc Jasper: program analysis and optimization, portability, parallelism representations and process algebras, benchmark synthesis, model checking and temporal logics
Ignacio Laguna: program analysis, software correctness, compiler analysis, resilience, fault tolerance, debugging
Aniruddha Marathe: power-aware and power-constrained supercomputing, performance analysis and optimization, HPC in cloud
Harshitha Menon: approximate computing, mixed-precision computing, performance analysis, fault tolerance, run-time system, load balancing, charm++
Dan Milroy: converged HPC and cloud resource and job management, software correctness, program analysis
Konstantinos Parasyris: programming models, fault tolerance, low-energy and low-power technologies, undervolting
Tapasya Patki: power-aware supercomputing, HPC scheduling and resource management, performance modeling and optimization, multi-constraint performance optimization, low-level heterogeneous architecture interfaces
Barry Rountree: power telemetry and control, performance optimization under power bounds, machine learning for climate simulation performance optimization, system programming tools
Abhik Sarkar: multi-processor architecture, system software performance analysis and optimization, binary translation and processor virtualization