Thomas Furlani, PhD

Director of CCR

Dr. Furlani serves as Director of the University at Buffalo's Center for Computational Research, a leading academic supercomputing center. As Director of CCR, Dr. Thomas Furlani, whose Ph.D. is in Computational Chemistry, manages the day-to-day operations of the center as well as oversees its research activities. CCR maintains an extensive array of computing resources, including an 8000 core Linux cluster and GPU based cluster. The total aggregate compute capacity of the center is more than 300 Tflop/s.   One of the primary focuses of CCR is to support the New York State Center of Excellence in Bioinformatics and Life Sciences, which is comprised of UB, the Roswell Park Cancer Institute, and the Hauptman-Woodward Medical Research Institute.  CCR provides several layers of support for the life sciences/bioinformatics initiatives, including access to specialized hardware and software to facilitate research, the development of customized software/databases to support data analysis (ex, REDFly), individual and group training on software packages supported by CCR, and collaboration with CCR staff to facilitate research and for proposal development.

A National Science Foundation Pre-doctoral Fellow, Dr. Furlani has more than 25 years experience in research computing and visualization, including high-performance computing, computational chemistry, and cloud computing. In addition to supporting research, Education and Outreach has been an important component of CCR's mission since its inception, with on-going K-12, undergraduate and graduate level programs. In terms of K-12 outreach, CCR each year runs the Eric Pitman Annual Summer Workshop in Computational Science. Every summer, high school sophomores, juniors, and seniors spend two weeks learning computer programming and its application to problems in chemistry, visualization, and most recently bioinformatics.

 

Relevant Accomplishments:

  • Founding Member of the National Transportation Research Board (TRB) Visualization in Transportation Committee (ABJ95),
  • Founding member of the New York State High Performance Computing Consortium (hpc-ny.org).
  • Member of the Board of Directors for NYSERNet (http://www.nysernet.org).
  • Co-developer of High School outreach program in computational science at UB.  Focus on attracting students, especially underrepresented groups, into science and engineering http://ccr.buffalo.edu/outreach/k-12-outreach/summer-workshop.html.

 

Research Interests:

HPC Metrics on Demand:  Development of metrics and auditing framework for high performance computing systems.

 

High performance computing (HPC) systems, more commonly known as supercomputers, are essential tools in a diverse range of areas including science, finance, oil and gas exploration, pharmaceutical drug design, and medical and basic research.   Given the crucial role they play in research in the U.S., it is important to ensure that HPC systems, which are a complex combination of computer hardware and software, are operating as efficiently as possible.  My research focuses on the development of XDMoD, a software tool that system support personnel and scientists can use to achieve the optimal operation of HPC systems, including the scientific computer programs that run on them. XDMoD is designed to meet the following objectives: (1) provide the user community with a tool to optimize their use of HPC resources, (2) provide operational staff with the ability to monitor, diagnose, and tune system performance as well as measure the performance of all applications running on their system, (3) provide software developers with the ability to easily obtain detailed analysis of application performance to aid in optimizing code performance, (4) provide stakeholders with a diagnostic tool to facilitate HPC planning and analysis, and (5) provide metrics to help measure scientific impact.  XDMoD is used by academic, industrial, and government HPC centers worldwide, as well as by the NSF XSEDE program which oversees the largest collection of supercomputers in the world.  It is available for download at http://ubmod.sourceforge.net/.


Research on the application of Green Technologies to reduce HPC center operational costs.

Our research interests lie in the implementation of state-of-the-art green technologies to reduce operational costs in high performance computing centers. An initial phase (CCR Green IT) focuses on server efficiencies while subsequent phases are focused on more efficient cooling technologies as well as a implementation of a data center monitoring system to dynamically control the data center environment to optimize energy efficiency.


Molecular electronic structure theory, algorithms for parallel computers, molecular cluster chemistry.

Our research interests are in the development and application of computational methods which can be utilized to study structure and reactivity in molecular systems. Areas of interest are as follows:

  • The application of combined quantum mechanical and molecular mechanical (QM/MM) methods to solve important problems in diverse areas of molecular biology such as biological activity of protein active sites, interaction between proteins and DNA, drug metabolism in proteins, and drug discovery related to cancer treatment.  Dr. Furlani's research group has carried out combined QM/MM simulations on important biochemical systems, such as cytochrome P450, myoglobin, soluable guanylate cylase, vitaimin B12, bacteriorhodopsin, and DNA. This work is carried out in collaboration with Dr. Jing Kong from Q-Chem.
  • The development of parallel algorithms for distributed and shared memory parallel computers which can be used to solve Grand Challenge class problems in computational chemistry. Thus far this research has been directed toward the development of Hartree-Fock and DFT based codes for high performance computers, including large linux clusters. This work is carried out in close collaboration with Q-Chem, Inc., a Pittsburgh based company, which develops and markets the commercial electronic structure program, Q-Chem.
  • Quantum mechanical study of the reactions occurring within gas-phase molecular clusters. By concentrating on the chemistry within these cluster systems, it is possible to learn how the behavior of the system changes from that of a gas-phase bimolecular ion-molecule reaction to a typical chemical process within solution. Thus, the study of reactive processes in clusters may be used as a conceptual bridge between the gas-phase "bimolecular" world and the "solvated multimolecular" world of chemical reactions in solution. This work is carried out in collaboration with Professor James Garvey in the Department of Chemistry.

Recent Publications:

  • S. J. Guercio, A. E. Bruno, M. D. Jones, and T. R. Furlani, Implementing Green Technologies and Practices in a High Performance Computing Center, submitted to IGCC'12, June 2012, San Jose CA USA.
  • T. R. Furlani, M. D. Jones, S. M. Gallo, A. E. Bruno, C.-D. Lu, A. Ghadersohi, R. J. Gentner, A. Patra, R. L. DeLeon, G. von Lazewski, L. Wang and A. Zimmerman, Performance Metrics and Auditing Framework Using Applications Kernels for High Performance Computer Systems. submitted Concurrency and Computation: Practice and Experience (2012).
  • C.-D. Lu, M. D. Jones, T. R. Furlani, Automatically Mining Program Build Information via Signature Matching. submitted TeraGrid 11 Workshop, Salt Lake City, UT, July 18-21, (2011).
  • F. Liu, Z. Gan, Y. Shao, C. Hsu, A. Dreuw, M. Head-Gordon, B. T. Miller, B. R. Brooks, J. Yu, T. R. Furlani and J. Kong, A parallel implementation of the analytic nuclear gradient for time-dependent density functional theory within the Tamm-Dancoff approximation. Journal of Molecular Physics, 108, 2791-2800 (2010).
  • L. Wang , G. von Laszewski, J. Dayal and T. R. Furlani, Thermal Aware Workload Scheduling with BackFilling for Green Data Centers., IEEE IPCCC (2009).
  • L. Wang, G. von Laszewski, J. Dayal, X. He, A. J. Younge and T. R. Furlani, Towards Thermal Aware Workload Scheduling in a Data Center. Accepted by the 10th International Symposium on Pervasive Systems. (i-SPAN'09), Algorithms and Networks, Taiwan, Dec. 14-16 (2009).
  • C.T. Chiang, K. S. Shores, M. Freindorf, T. R. Furlani, R. L. DeLeon, J. F. Garvey Size-Restricted Proton Transfer within Toluene-Methanol Cluster Ions. J. Phys. Chem. A, 112, 11559 (2008)
  • J. Kong, Z. Gan, E. Proynov, M. Freindorf, T. R. Furlani, Efficient Computation of the Dispersion Interaction with Density Functional Theory. Phys. Rev. A 79, 042510 (2009).
  • M. Freindorf, Y. Shao, J. Kong, T.R. Furlani, Combined QM/MM Calculations of Active-Site Vibrations in Binding Process of P450cam to Putidaredoxin. Accepted in J. Inorg. Biochem. (2007).
  • M. Freindorf, Y. Shao, J. Kong, T.R. Furlani, Large-Scale QM/MM Calculations of Electronic Excitations in Yellow Protein, Toward Petascale Level of Protein Calculations. Proceedings of the 7th International Conference on Bioinformatics and Bioengineering, Harvard Medical School, Boston, MA, USA, 614 (2007).
  • C.-T. Chiang, M. Freindorf, T.R. Furlani, R.L. DeLeon, J.P. Richard, J.F. Garvey, Enhancement of a Lewis Acid-Base Interaction via Solvation: Ammonia Molecules and the Benzene Radical Cation. J. Phys. Chem. A. 111, 6068 (2007).
  • M. Freindorf, Y. Shao, J. Kong, T.R. Furlani, Combined QM/MM Studies of Binding Effect of Cytochrome p450cam to Putidaredoxin. Proceedings of the 2006 International Conference on Bioinformatics and Computational Biology, Las Vegas, NV, USA, 391 (2006).
  • Y. Shao, L. Fusti-Molnar, Y. Jung, J. Kussmann, C. Ochsenfeld, S. T. Brown, A. T. B. Gilbert, L. V. Slipchenko,S. V. Levchenko, D. P. O'Neill, R. A. Distasio Jr., R. C. Lochan, T. Wang, G. J. O. Beran, N. A. Besley, J. M., Herbert, C. Y. Lin, T. Van Voorhis, S. H. Chien, A. Sodt, R. P. Steele, V. A. Rassolov, P. E. Maslen, P. P. Korambath, R. D. Adamson, B. Austin, J. Baker, E. F. C. Byrd, H. Dachsel, R. J. Doerksen, A. Dreuw, B. D. Dunietz, A. D. Dutoi, T. R. Furlani, S. R. Gwaltney, A. Heyden, S. Hirata, C.-P. Hsu, G. Kedziora, R. Z. Khalliulin, P. Klunzinger, A. M. Lee, M. S. Lee, W. Liang, I. Lotan, N. Nair, B. Peters, E. I. Proynov, P. A. Pieniazek, Y. M. Rhee, J. Ritchie, E. Rosta, C. D. Sherrill, A. C. Simmonett, J. E. Subotnik, H. L. Woodcock III, W. Zhang, A. T. Bell, A. K. Chakraborty, D. M. Chipman, F. J. Keil, A. Warshel, W. J. Hehre, H. F. Schaefer III, J. Kong, A. I. Krylov, P. M. W. Gill, M. Head-Gordon, Advances in methods and algorithms in a modern quantum chemistry program package, Phys. Chem. Chem. Phys., 8, 3172 - 3191 (2006).
  • M. Freindorf, Y. Shao, J. Kong, T.R. Furlani, A Combined Density Functional Theory and Molecular Mechanics (QM/MM) Study of FeCO Vibrations in Carbonmonoxy Myoglobin. Chem. Phys. Letters. 419, 563 (2006).
  • D.N. Shin, M. Freindorf, T.R. Furlani, R.L. DeLeon, J.F. Garvey Nitrosamide, (H2NNO), Formation within [ (NO)m(NH3)n ]+ Clusters: Theory & Experiment. I. J. Mass Spectrum. 255-256, 28 (2006).
  • M. Freindorf, Y. Shao, T.R. Furlani, J. Kong, Lennard-Jones parameters for combined QM/MM method using B3LYP/6-31+G*/AMBER potential J. Comput. Chem. 26, 1270 (2005).
VDW
  • T.R. Furlani, J. Kong, and P.M.W. Gill, Parallelization of SCF calculations within Q-Chem", invited paper in special issue of Computer Physics Communications, 128, 170-177 (2000).
  • Kong, Jing; White, Christopher A.; Krylov, Anna I.; Sherrill, David; Adamson, Ross D.; Furlani, Thomas R.; Lee, Michael S.; Lee, Aaron M.; Gwaltney, Steven R.; Adams, Terry R.; Ochsenfeld, Christian; Gilbert, Andrew T. B.; Kedziora, Gary S.; Rassolov, Vitaly A.; Maurice, David R.; Nair, Nikhil; Shao, Yihan; Besley, Nicholas A.; Maslen, Paul E.; Dombroski, Jeremy P.; Daschel, Holger; Zhang, Weimin; Korambath, Prakashan P.; Baker, Jon; Byrd, Edward F. C.; Van Voorhis, Troy; Oumi, Manabu; Hirata, So; Hsu, Chao-Ping; Ishikawa, Naoto; Florian, Jan; Warshel, Arieh; Johnson, Benny G.; Gill, Peter M. W.; Head-Gordon, Martin; Pople, John A. Q-Chem 2.0: a high-performance ab initio electronic structure program package. Journal of Computational Chemistry, 21(16), 1532-1548 (2000).
  • T.R. Furlani and H.F. King, A parallel direct SCF method for large molecular systems, in Quantum Mechanical Simulation Methods for Studying Biological Systems, Ed. D. Biscout and M. Field, (Springer, France, 1996), pp. 271-274.
  • T.R. Furlani and H.F. King, Implementation of a parallel direct SCF algorithm on distributed memory computers, J. Comp. Chem., 16, 91-104 (1995).