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Contact

Office Location

440 Huntington Avenue
336 West Village H
Boston, MA 02115

Mailing Address

Northeastern University
ATTN: Gene Cooperman, 202 WVH
360 Huntington Avenue
Boston, MA 02115

Research Interests

Fault tolerance, with an emphasis on extending the frontiers of techniques such as transparent checkpointing to include applications covering: supercomputing, parallel computing, cloud computing, persistent desktops for engineers, GPU-accelerated graphics, GPGPU computing, the Internet of Things, formal verification, and cyber-security.

Education

  • PhD, Brown University
  • BS in Mathematics & Physics, University of Michigan

Biography

Gene Cooperman is a professor of the Khoury College of Computer Sciences. Professor Cooperman received his BS in 1974 from the University of Michigan, and his PhD from Brown University in 1978. Prior to joining Northeastern, he was a principal MTS at GTE Laboratories (1980-1986). He leads the High Performance Computing Laboratory at Northeastern University, and he currently co-leads an Inria associate team in a 3-year project called “FogRein: Steering Efficiency for
Distributed Applications”. In the past, he also held a 5-year IDEX Chair of Attractivity at the University of Toulouse in France, as well as visiting research positions at Concordia University, CERN, and Inria. As a result of the work at CERN, Professor Cooperman joined the Geant4 Collaboration and contributed to the foundational paper “GEANT4 – A Simulation Toolkit”, which currently has approximately 25,000 citations and is the most widely cited paper in high energy physics.

In the past, Professor Cooperman worked in a series of inter-disciplinary research areas, including applied mathematics, computational and symbolic algebra, numerical analysis, computing in high energy physics (including a 10-year association with CERN), bioinformatics, high performance computing, and computer systems. He has co-authored over 100 refereed publications. Professor Cooperman has advised PhD students and personally led several open source software projects:
TOP-C/C++ (Task-Oriented Parallel C/C++: a model for writing parallel software easily); Roomy (a middleware for big data that uses the many disks of a cluster to simulate many terabytes of RAM: used to show that 26 moves suffice for Rubik’s Cube, a record at its time); and ParGeant4 (distributed parallelism for the CERN-based Geant4 software for Monte Carlo particle-matter interaction in high energy physics).

Two further open source software projects have developed a life of their own. They are Geant4-MT and DMTCP. The first project, Geant4-MT (Geant4 Multithreaded) culminated, in Jan., 2014, with the incorporation of Geant4-MT into the Geant4 version 10.0 release, and is now maintained at CERN. In the 15 years prior to this, Geant4 had grown purely as a single-threaded package of almost a million lines of code. Hence, retroactively adding multi-threading to the Geant4 production software was both a major research effort (described in the PhD thesis of Xin Dong) and a major implementation effort that included five members of the Geant4 collaboration.

The second ongoing software project is DMTCP (Distributed Multi-Threaded CheckPpointing). The DMTCP approach emphasizes transparent checkpointing or snapshots (no modification to the target application binary) and transparent extensibility to external hardware/software environments (e.g., GPUs, MPI, distributed systems). The roots of this project began in 2004, and it is now in its third generation, incorporating results from a series of PhD theses, as well as the work of other students. The project provides both a production platform (available in all major Linux distros), and a research platform (used by independent researchers as documented in over 100 refereed research publications). Examples of research areas using DMTCP include circuit verification, formal verification, CPU chip design by Intel and others, VLSI circuit simulators, formalization of mathematics, bioinformatics (including a publication in the Proc. of the National Academy of Science), network simulation, high energy physics, cyber-security, big data, middleware, mobile computing, cloud computing, virtualization of GPUs, and high performance computing.