Maya Gokhale is Distinguished Member of Technical Staff at the Lawrence Livermore National Laboratory, USA. Her career spans research conducted in academia, industry, and National Laboratories. Maya received a Ph.D. in Computer Science from University of Pennsylvania in 1983. Her current research interests include data intensive architectures and reconfigurable computing. Maya is co-recipient of an R&D 100 award for a C-to-FPGA compiler, co-recipient of four patents related to memory architectures for embedded processors, reconfigurable computing architectures, and cybersecurity, and co-author of more than one hundred technical publications.
Data-centric computing architectures
High performance embeddable architectures
Parallel computing systems
Computer and Information Sciences, University of Pennsylvania, 1983
Computer and Information Sciences, University of Pennsylvania, 1977
Math, Wake Forest University, 1972
Recent Professional Experience
Computer Scientist, Center for Applied Scientific Computing, Lawrence Livermore National Laboratory (LLNL), Livermore, CA
Team Leader (2005-2007, Application Specific Architectures in Advanced Computing Lab); Deputy Group Leader (2002-2004, Space Data Systems); Project Leader (1999-2002, Deployable Adaptive Processing Systems in Space Data Systems)
Honors and Organizations
Magna Cum Laude
Phi Beta Kappa
National Intelligence Community Award co-recipient
R&D 100 co-recipient for Trident C to FPGA compiler
Selected Publications and Presentations
A. K. Jain, G. S. Lloyd, and M. Gokhale, “Performance assessment of emerging memories through FPGA emulation,” IEEE Micro, vol. 39, no. 1, pp. 8–16, 2019. [Online]. Available: https://doi.org/10.1109/MM.2018.2877291
Scott Lloyd and Maya Gokhale, “In-memory data rearrangement for irregular, data intensive computing,” IEEE Computer, August 2015, v. 48, no. 8, pp. 18–25.
Roger Pearce, Maya Gokhale, and Nancy Amato, “Faster Parallel Traversal of Scale Free Graphs at Ex- treme Scale with Vertex Delegates,” International Conference for High Performance Computing, Networking, Storage, and Analysis, November 2014.
I. B. Peng, M. McFadden, E. Green, K. Iwabuchi, K. Wu, D. Li, R. Pearce, and M. Gokhale, “Umap : Enabling application-driven optimizations for page management,” in Workshop on Memory Centric HPC, SC19, 2019.
Sasha K. Ames, David A. Hysom, Shea N. Gardner, G. Scott Lloyd, Maya B. Gokhale and Jonathan E. Allen, “Scalable metagenomic taxonomy classification using a reference genome database,” Bioinformatics, July 2, 2013 (open access).
Justin L. Tripp, Maya B. Gokhale, Kristopher D. Peterson, “Trident: From High-Level Language to Hardware Circuitry,” IEEE Computer, March 2007.
Maya Gokhale and Paul Graham, Reconfigurable Computing: Accelerating Computation with Field-Programmable Gate Arrays, Springer, 2005.
Maya Gokhale, Dave Dubois, Andy Dubois, Mike Boorman, Steve Poole, Vic Hogsett, “Granidt: Towards Gi- gabit Rate Network Intrusion Detection Technology,” Field Programmable Logic 2002 , Sept. 2002. Selected in 2015 as one of 27 significant papers in 25 years of FPL.
Maya Gokhale, Janice Stone, Jeff Arnold, and Mirek Kalinowski, “Stream-Oriented FPGA programming in the Streams-C High Level Language”, IEEE Conference on FPGAs for Custom Computing FCCM 2000. Selected in 2013 as one of the 25 significant papers in the past 20 years of FCCM.
M. Gokhale, B. Holmes, and K. Iobst, "Processing in Memory: The Terasys Massively Parallel Processor-in-Memory Array," IEEE Computer, April, 1995, pp. 23--31.
M. Gokhale, W. Holmes, A. Kopser and S. Lucas and R. Minnich and D. Sweely and D. Lopresti, “Building and using a highly parallel programmable logic array”, IEEE Computer, Jan. 1991, pp. 81–89.