From 2011 to 2014, I was a technical staff member in the Computing and Analytics Group at MIT Lincoln Laboratory. My responsibilities there included research, leading software projects, developing software, interacting with program managers (e.g., DARPA), and program development. I lead a software team (4-8 people) in the development of the LLMORE software framework for data to processor mapping and simulation of key Department of Defense applications to existing and experimental computer architectures. I also helped to developing high-performance computing algorithms and software for solving very large graph problems.
Michael M. Wolf and Benjamin A. Miller, "Sparse Matrix Partitioning for Parallel Eigenanalysis of Large Static and Dynamic Graphs," IEEE HPEC 2014, Waltham, MA, September 2014.
Daniel Kimball, Elizabeth Michel, Paul Keltcher, and Michael M. Wolf, "Quantifying the Effect of Matrix Structure on Multithreaded Performance of the SpMV Kernel," IEEE HPEC 2014, Waltham, MA, September 2014.
Julie S. Mullen, Michael M. Wolf, and Anna Klein, "PAKCK: Performance and Power Analysis of Key Computational Kernels on CPUs and GPUs," IEEE HPEC 2013, Waltham, MA, September 2013.
Dave Whelihan, et al., "P-sync: A Photonically Enabled Architecture for Efficient Non-local Data Access," 2013 IEEE 27th International Parallel and Distributed Processing Symposium (IPDPS), pp.189-200.
Michael M. Wolf, et al., "LLMORE: A Framework for Data Mapping and Architecture Analysis," IEEE HPEC 2012, Waltham, MA, September 2012.
"Detecting Anomalies in Very Large Graphs," The Sixth SIAM Workshop on Combinatorial Scientific Computing (CSC14), Lyon, France, July 21-23, 2014.
"Effective Parallel Computation of Eigenpairs to Detect Anomalies in Very Large Graphs," SIAM Conference on Parallel Processing for Scientific Computing (PP14), Portland, OR, February 18-21, 2014. (Contributed Presentation.)