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Icl-2014-Report.Pdf EDITED BY Sam Crawford DESIGNED BY David Rogers ©2014 Innovative Computing Laboratory. All rights reserved. Any trademarks or registered trademarks that appear in this document are the property of their respective owners. EEO/TITLE IX/AA/SECTION 504 STATEMENT All qualified applicants will receive equal consideration for employment and admissions without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, or covered veteran status. Eligibility and other terms and conditions of employment benefits at The University of Tennessee are governed by laws and regulations of the State of Tennessee, and this non-discrimination statement is intended to be consistent with those laws and regulations. In accordance with the requirements of Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and the Americans with Disabilities Act of 1990, The University of Tennessee affirmatively states that it does not discriminate on the basis of race, sex, or disability in its education programs and activities, and this policy extends to employment by the University. Inquiries and charges of violation of Title VI (race, color, national origin), Title IX (sex), Section 504 (disability), ADA (disability), Age Discrimination in Employment Act (age), sexual orientation, or veteran status should be directed to the Office of Equity and Diversity (OED), 1840 Melrose Avenue, Knoxville, TN 37996-3560, telephone (865) 974-2498 (V/TTY available) or 974-2440. Requests for accommodation of a disability should be directed to the ADA Coordinator at the Office of Equity and Diversity. FROM THE DIRECTOR 2 INTRODUCTION 4 2014 HIGHLIGHTS 6 RESEARCH 8 2014 PUBLICATIONS 20 2014 EVENTS 22 COMPUTATIONAL RESOURCES 24 PARTNERSHIPS 26 LEADERSHIP 28 PEOPLE 30 VISITORS 33 ALUMNI 34 ACKNOWLEDGMENTS 36 FROM THE DIRECTOR This year we are celebrating the types of digital data, means that 25th anniversary of the Innovative computational science now confronts Computing Laboratory. When I an operational landscape that is reflect on two and a half decades full of opportunity to those who of leading ICL, which has gone by can conquer its extraordinary new all too quickly, I find it has been a challenges. period full of remarkable changes on If I feel confident that we are every side. Most obviously, the rapid ready for these challenges, it is evolution and growing impact of high because I know we are cultivating performance computing technology fertile ground that has been well has been truly astonishing. In the prepared by those who have come past 25 years we have seen Gigascale before. Over the past 25 years, we systems, with tens of processors, have developed robust research turn into Terascale systems with programs, attracted some of the thousands of processors, and then best and brightest students and Jack Dongarra into Petascale systems with hundreds DIRECTOR, ICL researchers, and created leading- of thousands, even millions of edge research programs. A look at processing elements, or “cores.” It is the timeline with which we begin clear in less than a decade we will be this report, which lines up the tenure at Exascale computing, with billions of some exceptional ICL alumni with of threads, and incorporating a host the lifespan of major ICL projects, of revolutionary new innovations. reminds us that we are drawing “Going to Exascale” will require on the rich legacy left to us by the utterly unprecedented increases many creative and energetic people in parallelism, fault tolerance, who have come through ICL over and energy efficiency; and these the years. The names of the projects requirements will in turn demand that they have helped lead—PVM, equally radical changes to computing MPI, LAPACK, ScaLAPACK, BLAS, architecture, software, and ATLAS, Netlib, NHSE, TOP500, PAPI, algorithms. At the same time, we NetSolve, Open-MPI, FT-MPI, the know that the recent dawn of the era HPC Challenge, LINPACK, and the of “Big Data,” with explosive growth HPCG benchmark—are familiar to in the amount, the sources, and the HPC users around the world. And the 2 FROM THE DIRECTOR software that they have produced and optimization of scheduling balance between global optimization now provides critical research strategies. By providing such and local control that Exascale infrastructure for hundreds of support for hardware accelerators, capable applications will require. thousands, if not millions, of users. RaPyDLI should increase available So the stage is set for what computational power by more than This past year saw the growth of promises to be a very exciting and an order of magnitude, and thereby projects that will undoubtedly add to rewarding anniversary year for ICL, enable far more sophisticated and this estimable list. Especially notable both in its main areas of research and powerful neural networks. RaPyDLI are major efforts that address either in its work to grow and strengthen now joins the SciDB project—a the “Big Data” dimension, or the UTK and its broader community. collaboration between MIT and the “Going to Exascale” dimension of During these exciting times, I am Intel Parallel Computing Laboratory the current research landscape. In grateful to our sponsors for their begun in 2013—as the second prong the case of the former, this year continued support of our efforts. My in ICL’s Big Data strategy. the National Science Foundation special thanks and congratulations funded the Rapid Python Deep Our progress on the scientific go to the ICL staff and students for Learning Infrastructure (RaPyDLI) communities’ journey to Exascale their skill, dedication, and tireless project—a collaboration between computing also continued with the efforts to make ICL one of the best ICL, Indiana University, and Stanford official launch of the ARGO project. centers in the world for scientific University. RaPyDLI will increase ARGO represents a major effort computing technologies. the productivity and performance of DOE to develop a new Exascale of Deep Learning research by the Operating System and Runtime community through the combination (OS/R). Designed from the ground of high level Python, C/C++, and up to run future HPC applications Java environments with carefully at extreme scales, it is clear that designed libraries supporting GPU achieving this goal will require accelerators and MIC coprocessors ARGO to leverage disruptive new (Intel Xeon Phi). Deep Learning computing technologies, such (DL)—a form of machine learning as 3D memory, ultra-low-power that relies on training massive neural cores, and embedded network networks—has made major impacts controllers, which will change the in areas like speech recognition, scientific computing landscape. ICL’s drug discovery, and computer PaRSEC team will help lead in the vision. ICL’s contribution will focus development of a new, agile modular on efficient GPU kernel execution architecture that supports the 3 Now in its 25th year, the Innovative Computing Laboratory (ICL) is a INTRODUCTION large Computer Science research and development group situated in the heart of the University of Tennessee’s Knoxville campus. ICL’s mission is to establish and maintain the University of Tennessee as a world leader in advanced scientific and high performance computing through research, education, and collaboration. 4 ICL’s founder, Dr. Jack Dongarra, established the lab in 1989 when he received a dual appointment as a Distinguished Professor at UTK and as a Distinguished Scientist at Oak Ridge National Laboratory. Since then, ICL has grown into an internationally recognized research laboratory, specializing in Numerical Linear Algebra, Distributed Computing, and Performance Evaluation and Benchmarking. The lab now employs nearly forty researchers, students, and staff, and has earned many accolades, including four R&D100 awards. 1989 5 2014 HIGHLIGHTS For ICL, 2014 marks the 25th year of conducting innovative research in high performance computing and cyberinfrastructure, and the lab made significant contributions to the HPC community during the past year. The sections below illustrate ICL’s commitment to excellence, and set the bar for continued progress in our areas of research. For years, ICL has been recognized by industry as a leader in information technology research. Vendors like NVIDIA and Intel regularly collaborate INDUSTRY EXCELLENCE with the lab’s research scientists, exchanging hardware and expertise, in an effort to improve both the hardware and software used in their products. These collaborations have led to very close working relationships and recognition of ICL’s efforts among vendors. The Intel Parallel Computing Center (IPCC) program is comprised of universities, institutions, and labs that are leaders in their field, focusing on modernizing applications to increase parallelism and scalability through optimizations that leverage cores, caches, threads, and vector capabilities of microprocessors and coprocessors. The objective of the Innovative Computing Laboratory’s IPCC is the development and optimization of numerical linear algebra libraries and technologies for applications, while tackling current challenges in heterogeneous Intel® Xeon Phi™ coprocessor- based High Performance Computing. In collaboration with Intel’s MKL team, the IPCC at ICL will modernize the popular LAPACK and ScaLAPACK libraries to run efficiently on current and future manycore architectures, and
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