David Gleich, Ahmed Sameh, Ananth Grama, et al. High Performance Computing: Enabling Complex Decisions Making in the Information Era David Gleich, Ahmed Sameh, Ananth Grama, et al.

Overview High Performance Computing Research@Purdue Scalable Analytics Science of Information Multidisciplinary Education Programs Computational Science and Engineering Computational Life Sciences Data Sciences (forthcoming)

HPC Research@Purdue From platforms to applications and services Purdue has among the largest academic supercomputing installations (Conte with 78K cores and close to 1.3 PF peak) These and other clusters (Carter and others) are available to researchers on campus, as well as for other projects.

HPC Systems Research Systems research focuses on programming models, language support, runtime systems, fault tolerance, performance monitoring and optimization, and power consumption. Among the largest and most active programming languages group, worldwide, investigating issues of language support, transactions, asynchrony, etc. Systems research spanning multiple schools focusing on issues of resource utilization, fault tolerance, application performance, and power considerations.

HPC Applications

HPC@Purdue: Simulation and Design PRISM: Prediction of Reliability, Integrity, and Survivability of Microsystems. An NNSA Center of the Department of Emergy

HPC@Purdue: Integrating Simulations and Experiments George E Brown Jr. Network for Earthquake Engineering Simulation

HPC@Purdue: Simulation Hubs Network for Computational Nanotechnology

HPC@Purdue: Sensing and Control Modeling and real-time control of wind turbines.

HPC@Purdue: Structural Health Monitoring Testing and simulation of large structures.

HPC@Purdue: Predictive Design Purdue Advanced Reactor Core Simulator 

HPC@Purdue: From Simulation to Validation Nanoscale Systems and Devices

HPC Algorithms and Software

Solvers and Preconditioners

Spike Performance Significantly more scalable than state of the art Excellent FLOP counts on conventional deep memory hierarchies Polyalgorithm that accomodates a variety of communication and processor granularities Available as open-source software.

Atomistic Modeling: PuReMD Purdue Reactive MD software is a unique open-source software package for ReaxFF simulations. Integrates a number of novel data structures, sparse solvers, and numerical optimizations. Available for CPU, GPU, clusters, and GPU clusters. Is currently used at over 200 labs worldwide to simulate systems ranging from lipid bilayers to RDX.

Comparison with LAMMPS-Reax Qeq solver performance Time per time-step comparison Qeq solver performance Memory foot-print different QEq formulations similar results LAMMPS: CG / no preconditioner

Bulk Water: 6540 atoms in a 40x40x40 A3 box / core PuReMD: Weak Scaling Bulk Water: 6540 atoms in a 40x40x40 A3 box / core

Si/Ge/Si Nanoscale bar Simulations Key Result: When Ge section is roughly square shaped, it has almost uniaxial strain! W = 20.09 nm Si Ge average transverse Ge strain average strains for Si&Ge in each dimension Simple strain model derived from MD results

Water-Silica Interface Motivation a-SiO2: widely used in nano-electronic devices also used in devices for in-vivo screening understanding interaction with water: critical for reliability of devices A Reactive Simulation of the Silica-Water Interface Fogarty et al., Journal of Chemical Physics 132, 174704 (2010)

Water-Silica Interface Key Result Silica surface hydroxylation as evidenced by experiments is observed. Proposed reaction: H2O + 2Si + O  2SiOH Silica Water Si O H

Education Programs: The Computational Science and Engineering Program CSE is one of the top-ranked academic programs at Purdue Initiated in 1994, it has grown significantly over the past 20 years!

CSE@Purdue One of the largest programs world-wide with over 150 affiliated faculty and 160 graduate students CSE faculty contribute in leadership roles to some of the largest research efforts on campus (DoE PRISM, CSoI NSF STC, NEES), along with many other interdisciplinary efforts CSE faculty have been supported by two US Department of Education GAANN grants over the past eight years. CSE students provide critical expertise to a broad set of projects

Education Programs: Data Science To be initiated in Fall 2014, this program is patterned after the CSE program. It is a multidisciplinary program that requires students to take two “bridge” courses and two disciplinary courses focused on data science. Other requirements include seminar/ independent study, multidisciplinary PhD committee.

Related Centers: Center for Science of Information. http://www.soihub.org A Science and Technology Center of the National Science Foundation.

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