High Performance Computing and Computational Science at AHPCC

1. High Performance Computing and Computational Science at AHPCC Brian T. Smith Professor, Department of Computer Science Director, Albuquerque High Performance Computing Center (AHPCC)

2. High Performance Computing Education & Research Center UNM strategic center to initiate and focus activities in high performance computing technology, research, and education Mission accomplished through two centers Established in 1994 as a training and resource center for MHPCC; now a national supercomputing Center within the NSF National Computational Science Alliance, serving as an academic center of excellence for research and education in computational science. Established in 1994 under the auspices of the DoD Modernization Program, through a Cooperative Agreement between the University of New Mexico and the Air Force Research Laboratory. Provides production computing cycles for DoD researchers.

3. High Performance Computing, Education & Research Center Frank L. Gilfeather Brian T. Smith John S. Sobolewski Ernest D. Herrera Maui High Performance Computing Center DIRECTOR ASSOCIATE DIRECTORS Eugene Bal Gary Jensen Steve Karwoski Margaret Lewis EXECUTIVE DIRECTOR CO-DIRECTOR CO-DIRECTOR ASSOCIATE DIRECTOR Albuquerque High Performance Computing Center DIRECTOR ASSOCIATE DIRECTORS Brian T. Smith Susan R. Atlas Robert A. Ballance Ernest D. Herrera

4. Supercomputing Capabilities AHPCC • Ranks in the top 5 US academic institutions in supercomputing power (effective 5/00) • A member of the NSF Alliance and a node on the National Technology Grid • 60 associated faculty, staff, postdocs and students • Computing systems • 512 processor IBM PIII Linux Supercluster (5/00) • 128 processor Alta PII Linux Supercluster • 32 processor VA Linux PIII Cluster • Vista Azul - advanced IBM hybrid system • 8 node SGI Origin 2000 • 16 processor Alta PII Linux development cluster • Visualization laboratory • 0ver 500 academic, industry, and government users MHPCC • One of the top 30 supercomputingcenters in the world • A DoD Shared Center—a node on the National Technology Grid • 65 staff members • Computing systems • 699 node IBM SP • 400 GFLOPS computing power • 167 GB total memory • 2.1 TB internal disk storage • 1.3 external disk storage • 20 TB mass storage • Visualization laboratory • 0ver 1,100 government, industry, and academic users Both centers support a significant number of users in academia and government, particularly the DoD and NSF, and are key players in the national supercomputer community.

5. LosLobos & Roadrunner Superclusters

6. Research Environment at the AHPCC • 38 Graduate Research Assistants • 16 Associated Faculty (Physics & Astronomy, Chemistry, Biology, Mechanical Engineering, Computer Science, EECE) • 6 Permanent Research Staff • 6 Visiting Scientists, Postdoctoral Fellows • Undergraduate Workstudy Students; NSF REU • Research Facilities: Supercomputers, High Performance Clusters, Workstations, Workshop Area, Seminar Room and Access Grid Studio • Educational Programs: SEC Program, Workshops, AHPCC Seminar Series, Alliance Activities, Native American Outreach, NSF AMO Summer School, UNM Course Laboratories

7. Computer Systems Research To anticipate, develop, deploy, and support high-performance computing technology and systems • Superclusters • Open computing tools • Grid-Based Computing • Visualization

8. Superclusters: Beyond Beowulf • System design and integration • Off-the-shelf symmetric multiprocessor subsystems • High-speed interconnects • Terabyte hierarchical mass storage systems • Research Areas • Networking– Portals • Hybrid (SMP) programming models • Cluster Management– Maui Scheduler, PBS • Condor high-throughput computing

9. Grid-Based Computing: Sharing Resources Across the Matrix • Computational Grid: People to Machines, Machines to Machines • Globus • Virtual Machine Room (VMR) • Wireless networking • Access Grid: People to People and Machines • Telemedicine • Visualization • Human Factors • Production Studio Deployment • Education & Training

10. TOUCH Telehealth Virtual CollaboratoryDr. Dale Alverson (UNM), Dr. Richard Friedman (UH) Access Grid multi-group Internet video conferencing for distance education Virtual Reality training environment 3D image/model manipulation and simulation environment using large, remote datasets Problem-based learning Figure: A user and their “avatar” in the BioSIMMER environment (brain injury patient). A user and their “avatar” in the BioSIMMER environment - brain injury patient

11. Scientific Visualization & Computational Environments • Visualization Laboratory – Homunculus Project • “Flatland” Virtual Reality Environment • Vista Azul Scalable Graphics Engine – parallel rendering • CoMeT Computational Mechanics Toolkit • Scientific Visualization Research

12. Science and Engineering Research Development of advanced algorithms and parallel software for application of high-performance computing technology to problems at the forefront of science and engineering • Optics and Imaging • Computational Physics • Computational Fluid Dynamics • Ecological Modeling • Chemistry and Materials • Computational Biology

13. Quantum Optics • Optics & Imaging • Image Processing and Astrophysical Observation Techniques for Astronomy and Space Surveillance Applications (D. Tyler, S. Prasad, W. Junor, R. Plemmons, T. Schulz, J. Green, J. Seldin, P. Alsing) • Quantum Computing and Quantum Optics (I. Deutsch, C. Caves, P. Alsing, G. Brennan, J. Grondalski, S. Ghose, P. Jessen) • Optical Pulse Interactions with Nonlinear Materials (P. Bennett)

14. Quantum Computing Quantum Optical Lattices By shining counter-propagating laser beams, “crystals of light” can be formed (egg crate structures) which can be used to trap neutral atoms, e.g. cesium. By changing the phase of the light, atoms can be brought together (shift the egg crate minima) and made to interact by an additional catalysis laser. The interacting atoms form qubits and the shifting egg crate potentials act as a computer bus. Prof. Ivan Deutsch, and Prof. Carl Caves (Physics and Astronomy); Dr. Paul Alsing (AHPCC);

15. Chemistry & Materials • Defect Centers in a-SiO2 Using Computational Chemistry Techniques (S.P. Karna, A.C. Pineda) • Defects in Al and Cu ULSI Interconnects — Materials/Solid State Physics (S.R. Atlas, S.M. Valone, L.A. Cano) • Electron Transfer in Dendrimers (T.S. Elicker, D.G. Evans) • Dynamics at Metal Surfaces (D. Xie, H. Guo) • Molecular Dynamics of Proteins in Solution (P. Alsing, E. Coutsias) • Atom-Ion Collisions (P. Alsing, M. Riley, A. Hira)

16. Vgate source Vdrain a-SiO2 n-Si n-Si p-Si Vbias Defects in SiO2 Dr. Andrew Pineda, AHPCC Dr. Shashi Karna, AFRL • Defects are detected experimentally via EPR. • Quantum mechanical (Hartree-Fock) calculations provide detailed information candidate structure and formation mechanisms. • Same computational techniques are used to model active sites of biological molecules in rational drug design. • Computations involve hundreds of electrons and dozens of atoms: 100’s of CPU hours on 8–32 processors of a supercomputer. a-SiO2 is the dielectric (insulator) material used in today’s semiconductor devices. Defect centers are created in manufacture and by irradiation. They are believed to be the primary charge traps in semiconductors; degrading current/voltage performance and sometimes destroying them.

17. Molecular Dynamics simulation of the role of water in protein folding Dr. Paul M. Alsing (AHPCC); Prof. Evangelos Coutsias (Mathematics & Statistics); Prof. Jack McIver (Physics and Astronomy)

18. Visualization of large data sets from molecular dynamics simulations in Flatland

19. Computational Genomics • Systems design and management • Storage and manipulation of large microarray and patient datasets • Database/annotation design • Firewall to protect patient privacy • Customized hierarchical mass storage system • Visualization • Mathematical and computational analysis • Molecular classification: clustering and neighborhood analysis • Identification of genetic correlations in microarray data • Collaboration between biologists, medical scientists, mathematicians, computational scientists will be essential

20. Computer Science Research • Parallel Algorithms and Numerical Mathematics (D.A. Bader, P. Bennett, P. Alsing, B. Minhas) • Condor Flocking and Turing Cluster — High Throughput Computing (Z. Chen, B.T. Smith, X. Wang, M. Livny, C.D. Maestas) • Scalable Systems Lab (A.B. Maccabe) • Research Clusters: Black Bear, Vista Azul, Roadrunner (R. Ballance, P. Kovatch, J.R. Barnes, C. Maestas) — Programming Paradigms for SMP Architectures; Code Development and Optimization; Cluster Management

21. Research • High Performance Computing • Visualization • Modeling and Simulation • Image Processing • Computational Mechanics • Computational Physics • Computational Chemistry • Computational Biology Providing, Developing and Implementing Services • Computing and visualization • Distributed computing scheduling • Collaborative interactive environments for researchers and training • Education and Outreach • Graduate-level certificate program for students and professionals at the federal labs • Native American education and training • Hawaiian schools • NCSA activities—educational toolkits • Training in High Performance Computing and Applications • Regional industry users • Federal lab users • Students and faculty—local and national Activities

22. Area Visualization Clusters Networking Collaboration Computational Modeling Cluster Management R&D Projects Project Flatland SMP Programming Portals, NGIO Access Grid Tools CoMeT Maui Scheduler

23. Production Systems • Condor • Distributed Workstations • Remote Job Submission and Management • Roadrunner • Alliance Shared Computational Resource • Production Linux Cluster from Alta Technology Corporation • 64 Nodes, 128 Processors, Myrinet Networking

24. Research Systems • Black Bear • Linux Cluster Provided by VA Linux Systems • 16 Nodes, 32 Processors, Myrinet Network • Vista Azul • Hybrid IBM Linux/SP with in situ Graphics • Linux: 8 Nodes, 32 Processors, Graphics-Enabled • SP: 8 Nodes, 32 Processors • 360 GB Storage, Shared Graphics Framebuffer