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SyNeRGy Research

Systems, Networking, and Renaissance Grokking () Lab conducts basic and applied research in parallel and distributed computing that provides scientists and engineers with scalable and efficient computational tools that enable them to concentrate on their science and engineering rather than on the computer science and engineering. To that end, we explore a breadth of complementary intellectual activities in parallel computing that span the high-performance & enterprise-wide spectrum - from systems software to middleware to applications software to tools - in order to empower cyber-scientists and cyber-engineers of tomorrow.

Our research is typically focused at the synergistic intersection of Systems Software & Middleware, Architecture, Application Software and Tools. Below we showcase select research. Please see our publications page for a complete picture.

Systems Software & Middleware

  • Parallel Computing
    • Architecture: Mixin Layers*, MPI-ACC, ...
    • Benchmarks: OpenDwarfs, ...
    • Scheduling: SyMMer, CoreTSAR, ...
    • Virtualization: VOCL
  • Distributed Computing
    • Cloud Computing: SeqInCloud, CloudFlow, ...
    • I/O: ParaMEDIC, Asynchronous Collectives, ...
    • MapReduce: MOON, StreamMR, ...
    • Virtual Machines: SERViCE* → MyVICE
  • Networking
    • Hybrid: CHEETAH*
    • Protocols: Transport, ...
    • Security: Wireless*, ...
  • Green Computing
    • EnergyFit, EcoDaemon


  • Big Data: Genomes Galore, ...
  • Compute the Cure (for Cancer)
  • Education: CS Education, MyVICE
  • Life Sciences: mpiBLAST, Sequence Alignment, Genomic Sequence Searching, Long-Range Interactions → Molecular Modeling
  • Medical Sciences: Neuroinformatics, Human Computer Interaction in Radiology*

Green Computing

  • Architecture: Green Destiny
  • System Software: EnergyFit, EcoDaemon ...
  • Modeling: Power & Performance
  • Benchmarks & Tools: Green500, Gbench, Green Index, ...


  • Profiling: CampProf, Extensions to Cbench, ...
  • Productivity: CU2CL

Performance Modeling, Analysis, Evaluation and Optimization

  • Networking
    • HW: Quadrics*, 10 GigE*, ...
    • Protocols: Cascaded TCP, TCP Vegas*, Autotuning TCP Flow Control*, ...
    • Modeling: Q-Composer and CpR*
  • Emerging Processor Technologies
    • APU: Characterization, ...
    • GPU: Architecture-Aware Optimizations, Synchronization, ...
    • FPGA: Characterization, ...
Note: Research areas annotated with an asterisk (*) are relatively dormant.

Research Grants

External Funding: Research

IUCRC Phase I Virginia Tech: Center for Space, High-Performance, and Resilient Computing (SHREC). NSF
RAPID: A Computational Deep-Learning Approach for Fast, Accurate CT Testing and Monitoring of COVID-19.
RAPID: Higher Accuracy and Availability of COVID-19 Testing and Monitoring via Post-CT Image Boosting and Analysis. ORNL
Models and Evaluation of Scaling Deep Learning at Oak Ridge Leadership Computing (OLCF).
Performance Evaluation and Optimization of Parallel Runtime Systems for Large-Scale, Data Analytics Applications on HPC Supercomputing Environments. LLNL
Directive-Based Pipelining Extensions and Unified Memory of GPU Computing.
XPS: SDA: Collaborative Research: A Scalable and Distributed System Framework for Compute-Intensive and Data-Parallel Applications. AFOSR
Hardware/Software Co-Design for MAV Aerodynamics.
Democratizing the Teaching of Parallel Computing Concepts.  NSF
Genomes Galore - Core Techniques, Libraries, and Domain Specific Languages for High-Throughput DNA Sequencing. 
Analytical Electrostatics: Methods and Biological Applications. DOE
Kinematic and Waveform Inversion of Microearthquake and Ambient Noise Data for Three-Dimensional Velocity Structure in Geothermal Reservoirs.

External Funding: Equipment

MRI-R2: Acquisition of a Heterogeneous Supercomputing Instrument for Transformative Interdisciplinary Research.     More Past Grants ...