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Rob Farber

Rob Farber (CEO/Publisher)

A recognized global technology leader (US, Europe, Middle East, Asia-Pacific) who is highly-rated, highly visible, and in-demand as a technology/scientific advisor, teacher, and collaborator. Proven individual who has demonstrated a strong creative ability in establishing the field of machine learning while a scientist in the Theoretical Division at Los Alamos National Laboratory and while acting as an author, senior scientist, principal investigator, corporate leader, technical architect, and media consultant. He has contracts with fortune 100 companies (Intel, NVIDIA, AMD, and others), research organizations (DARPA, ONR, Cold Spring Harbor and others) plus numerous small companies. Co-founder of a computational drug discovery and computer manufacturing company that achieved liquidity events. Rob also has an extensive background in research (the theoretical division at LANL, external faculty at the Santa Fe Institute, NERSC in Berkeley and PNNL in Washington state). Widely-read and referenced in both the media and scientific literature with a substantial record encompassing hundreds of publications covering a range of fields including peer-reviewed scientific research, machine learning, commercial development, plus the design and implementation of advanced computer software and hardware. Notable projects span the gamut from a 13 PF/s average sustained “deep-learning” performance on the ORNL Titan GPU-based supercomputer; the design and analysis of the NERSC global unified file system architecture; planning metrics for supercomputer procurements; massively-parallel online social media analysis; a commercial drug design supercomputer and software system; a linearly scalable enterprise distributed file system with quality of service guarantees for streaming media (video and audio); a real time 1015 byte/s pattern recognition particle tracker for the SSC; a six billion agent epidemic modeling system; a highly efficient neural network compiler and nonlinear optimization system; plus an active participant in leading-edge technology from producing an early virtual memory microcomputer to working with present day latest-generation massively parallel processors and storage technology.

Books

The English version of my book, “CUDA Application Design and Development” can be purchased from booksellers or on-line from vendors around the world. Here is an Amazon link. A Chinese version of my book can also be purchased (Amazon link ).

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My newest book is also available for purchase in English and Chinese versions.

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Publications

Invited chapters

Chapter 25 “Power Analysis for Applications and Data Centers, “Volume 2 High Performance Parallelism Pearls“, Morgan Kaufmann; 1 edition (August 6, 2015)

Editor, “High Performance Parallel Programming“, Morgan Kaufmann; 1 edition (November 17, 2014)

Chapter 7, “Deep-learning and Numerical Optimization” in “High Performance Parallel Programming“, Morgan Kaufmann; 1 edition (November 17, 2014)

Scientific Editor, “GPU Computing Gems Emerald Edition (Applications of GPU Computing Series)”, Morgan-Kaufman, (2011), ISBN-13: 978-0123849885.

“Bioinformatics: High Performance Parallel Computer Architectures“, CRC Press

“Handbook of Research on Computational Science and Engineering: Theory and Practice“, IGI Global

“Multi-Threaded Architectures: Evolution, Costs, Opportunities“, IGI Global

“Topical perspective on massive threading and parallelism“,  The Journal of Molecular Graphics and Modelling

Peer-Reviewed Publications

“Sociolect-Based Community Detection”, William N. Reynolds, William J. Salter, Robert M. Farber, Courtney Corley, Chase P. Dowling, William O. Beeman, Lynn Smith-Loving and Joon Nak Choi, Proceedings of the IEEE International Conference on Intelligence and Security Informatics, 2013.

“High-performance the CUDA Application Design and Development: Methods and Best Practices”, (Chinese Edition) 2013, ISBN-13: 978-7111404460, R. Farber

“Thought Leaders During Crises in Massive Social Networks”, Courtney D. Corley, Robert M. Farber, William N. Reynolds, in Statistical Analysis and Data Mining edited by Joseph Verducci, Wiley Periodicals, Inc., 2012.

“CUDA Application Design and Development” Morgan-Kaufman, (2011), ISBN-13: 978-0123884268, R. Farber.

“Multi-Threaded Architectures: Evolution, Costs, Opportunities” in “Computational Science and Engineering: Theory and Practice”, IGI Press 2011, I. Girotto and R. Farber, ISBN13: 9781613501160.

Scientific Editor, “GPU Computing Gems Emerald Edition (Applications of GPU Computing Series)”, Morgan-Kaufman, (2011), ISBN-13: 978-0123849885.

“Topical perspective on massive threading and parallelism”, J Mol Graph Model. 2011 Sep;30:82-9. doi: 10.1016/j.jmgm.2011.06.007. Epub 2011 Jun 29, Farber RM.

“Massive Social Network Analysis: Mining Twitter for Social Good”, Ediger, et. al. Proceedings of the 39th International Conference on Parallel Processing 2010

“Social and Social Reality Theory, Evidence and Validation”, Farber, et. al. Proceedings of the IEEE International Conference on Intelligence and Security Informatics, 2010

“Experimental Comparison of Emulated Lock-free vs. Fine-grain Locked Data Structures on the Cray XMT”, Rob Farber and David W. Mizell, MTAAP’10, April, 2010

“An Introduction to GPGPUs and Massively-threaded Programming”, Farber, R., “Emerging Parallel Architectures and Programming Models,” edited by Bertil Schmidt, Francis and Taylor, LLC, July 2010, ISBN 10: 1439814880.

“Massively Parallel Near-Linear Scalability Algorithms with Application to Unstructured Video Analysis”, Robert Farber and Harold Trease, Proceedings of TeraGrid 2008, June 2008.

“Unstructured Data Analysis of Streaming Video Using Parallel, High-Throughput Algorithms”, Trease HE, T Carlson, R Mooney, R Farber, and LL Trease. 200, Proceedings of the Ninth Iasted International Conference on Signal and Image Processing, (2007) pp. 305-310. Acta Press, Anaheim, CA.

“Balancing Computation and Experiment” Farber, R., Innovation: America’s Journal of Technology Commercialization, vol. 5 no. 24, (April/May 2007), pg 24+.

“Exploring Protein Sequence Space Using Knowledge Based Potentials”, Aderonke Bajide, Robert Farber, Ivo L. Hofacker, Jeff Inman, Alan S. Lapedes, and Peter F. Stadler, Journal of Theoretical Biology 212(1). (Sept. 7, 2001), p.35-46.

“The Geometry of Shape Space: Application to Influenza” Lapedes, A; Farber, R., Journal of Theoretical Biology (Sep 7 2001). p. 57-69.

“Covariation of Mutations in H3N2 (HA1) Influenza Sequences”, Holly Tao, Robert Farber, Alan Lapedes, LANL internal paper, (1999).

“Following Influenza’s Jet Stream” 10/15/98 Chicago Tribune article referencing influenza work. Follow-up articles appeared in The New Mexican and The Albuquerque Journal.

“A Mutual Information Analysis of tRNA sequence and modification patterns distinctive of species and phylogenic domain”, Francisco M. De La Vega, Carlos Cerpa, Gabriel Guarneros and Robert M. Farber, “Biocomputing: Proceedings of the 1996 Pacific Symposium,” edited by Lawrence Hunter and Teri Klein, World Scientific Publishing Co, Singapore, 1996.

“Use of Adaptive Networks to Define Highly Predictable Protein Secondary-Structure Classes”, Alan S. Lapedes, Evan Steeg, Robert Farber, 21, 103-124, 1995, Machine Learning, Kluwer Academic Publishers, Boston.

“Neural Net Representations of Empirical Protein Potentials”, Tal Grossman, Alan Lapedes, Robert Farber, Evan Steeg, Santa Fe Institute Working Papers (96-05-029), 1995.

“Neural Network Definitions of Highly Predictable Protein Secondary Structure Classes”, Alan Lapedes, Robert Farber, Evan Steeg, LA‑UR 94‑110, 1995.

“Learning Affinity Landscapes: Prediction of Novel Peptides”, Alan Lapedes and Robert Farber, Los Alamos National Laboratory Technical Report LA-UR-94-4391 (1994).

“Global Bifurcations in Rayleigh‑Benard Convection: Experiments, Empirical Maps and Numerical Bifurcation Analysis“, I. G. Kevrekidis, R. Rico‑Martinez, R. E. Ecke, R. M. Farber and A. S. Lapedes, LA‑UR 92‑4200, Physica D, 1993.

“Identification of Continuous‑Time Dynamical Systems: Neural Network Based Algorithms and Parallel Implementation“, R. M. Farber, A. S. Lapedes, R. Rico‑Martinez and I. G. Kevrekidis, Proceedings of the 6th SIAM Conference on Parallel Processing for Scientific Computing, Norfolk, Virginia, March 1993.

“Covariation of Mutations in the V3 Loop of HIV‑1: An Information Theoretic Analysis”, Bette T.M. Korber, Robert M. Farber, David H. Wolpert, and Alan S. Lapedes, P.N.A.S. 1993.

“Efficiently Modeling Neural Networks on Massively Parallel Computers”, Los Alamos National Laboratory Technical Report LA‑UR‑92‑3568.

“A Parallel Non‑Neural Trigger Tracker for HEP Colliders”, R.M. Farber, W. Kinnison, and A.S. Lapedes, Proceedings of the Erice Conference on Pattern Recognition for High Energy Physics, Erice, Sicily (1992).

“Determination of Eukaryotic Protein Coding Regions Using Neural Networks and Information Theory”, R.M. Farber, Alan Lapedes, and Karl Sirotkin, J. Mol. Biology (1992) 226, 471‑479.

“A Parallel Non‑Neural Trigger Tracker for the SSC”, R.M. Farber, W. Kinnison, and A.S. Lapedes, IJCNN‑91‑Seattle Conference, (1991). (also: LANL technical report LA‑UR‑91‑607 and a 1995 Santa Fe Institute working paper 95-02-012).

“Efficiently Modeling Neural Networks on Massively Parallel Computers”, NASA workshop on parallel computing, (November 1991).

“Use of Neural Nets for DNA Sequence Analysis: Results on Combined Donor/Acceptor Splice Site Recognition”, K. Sirotkin, R. Farber, and A. Lapedes, Symposium on Artificial Intelligence and Molecular Biology (Stanford University) (1990).

“Neural Networks as Statistics”, A. Lapedes, R.M. Farber, Proceedings of the 10th International Biophysical Congress (Vancouver, Canada) (1990).

“Nonlinear Signal Processing and System Identification: Applications To Time Series From Electrochemical Reactions”, R.A. Adomaitis, R.M. Farber, J.L. Hudson, I.G. Kevrekidis, M. Kube, A.S. Lapedes, Chemical Engineering Science, ISCRE‑11, (1990).

“Application of Neural Nets to System Identification and Bifurcation Analysis of Real World Experimental Data“, R.A. Adomaitis, R.M. Farber, J.L. Hudson, I.G. Kevrekidis, M. Kube, A.S. Lapedes, International Conference on Neural Networks Proceedings, Lyons France (1990).

“Applications of Neural Net and Other Machine Learning Algorithms to DNA Sequence Analysis”, A.S. Lapedes, C. Barnes, C. Burks, R.M. Farber, K. Sirotkin, Computers and DNA, SFI Studies in the Sciences of Complexity, vol. VII, Eds. G. Bell and T. Marr, Addison‑Wesley, (1989).

“How Neural Nets Work,” Neural Information Processing Systems, Proceedings of IEEE 1987 Denver Conference on Neural Networks, A.S. Lapedes, R.M. Farber. (D.Z. Anderson, editor), (1988).

“How Neural Nets Work“, A.S. Lapedes, R.M. Farber, reprinted in Evolution, Learning, Cognition, and Advanced Architectures, World Scientific Publishing. Co., (1987).

“Nonlinear Signal Processing Using Neural Networks, Prediction and System Modeling”, A.S. Lapedes, R.M. Farber, LANL Technical Report, LA‑UR‑87‑2662, (1987).

“A Theory of Stochastic Neural Activity,” J.D. Cowan, R.M. Farber, A.S. Lapedes, D. H. Sharp, Rev. Mod. Phys.

“Programming a Massively Parallel System: Static Behavior,” A.S. Lapedes, R.M. Farber, Proceedings of the First Snowbird Conference on Neural Nets and Computation, September 1986, A.I.P. Press.

“Collective Arithmetic”, A.S. Lapedes, R.M. Farber, Los Alamos Technical Report.

“A Self Optimizing Neural Net for Content Addressable Memory and Pattern Recognition,”, A.S. Lapedes, R.M. Farber, Physica D,247 (1986).

“32-bit ‘Megamicro’ exploits hardware virtual memory and ‘RAM disk’”, Stan Metcalf, and Robert M. Farber, Mini-micro systems, October (1983).

Recent presentations and interviews:

An Intel Xeon Phi tutorial series on Doctor Dobb’s Journal

An OpenACC tutorial series “Pragmatic Parallelism” on Doctor Dobb’s Journal

A popular 28-part Doctor Dobb’s Journal GPU tutorial series.

CUDA lets you work with familiar programming concepts while developing software that can run on a GPU

An OpenCL tutorial series on The Code Project

Regular contributor to the Scientific Computing print and on-line articles (in chronological order):

Power and cooling in a Moore’s Law world