Judy Qiu is an assistant professor of Computer Science at Indiana University. Her general area of research is in data-intensive computing at the intersection of Cloud and HPC multicore technologies. This includes a specialization on programming models that support iterative computation, ranging from storage to analysis which can scalably execute data intensive applications. Her research has been funded by NSF, NIH, Microsoft, Google, and Indiana University. She is the recipient of a NSF CAREER Award in 2012, Indiana University Trustees Award for Teaching Excellence in 2013-2014, and Indiana University Outstanding Junior Faculty Award in 2015.
Steven Gottlieb is a Distinguished Professor of Physics at Indiana University. He works in Lattice QCD an area of theoretical high energy physics that relies large scale computing to understand the quantum field theory that describes the strong force. His research has been funded for many years by the US Department of Energy and National Science Foundation. He received an A.B. degree from Cornell University with majors in mathematics and physics, as well as Masters and Ph.D. degrees in physics from Princeton University. He was a DOE Outstanding Junior Investigator and Indiana University Outstanding Junior Faculty Award recipient.
The Indiana University Intel® Parallel Processing Center (Intel® PCC) is a multi-component interdisciplinary center. The initial activities involve Center Director Judy Qiu, an Assistant Professor in the School of Informatics and Computing, and Distinguished Professor of Physics Steven Gottlieb. Qiu will be researching novel parallel systems supporting data analytics and Gottlieb will be adapting the physics simulation code of the MILC Collaboration to the Intel Xeon Phi™ coprocessor.
More generally, the focus of the Center will be grand challenges in high performance simulation and data analytics with innovative applications, and software development using the Intel® architecture. Issues of programmer productivity and performance portability will be studied.
Steven Gottlieb is a founding member of the MILC Collaboration which studies Quantum Chromodynamics, one of nature's four fundamental forces. The open source MILC code is part of the SPEC benchmark and has been used as a performance benchmark for a number of supercomputer acquisitions. Gottlieb will be working on restructuring the MILC code to make optimal use of the SIMD vector units and many-core architecture of the Intel Xeon Phi™ coprocessor. These will be used in upcoming supercomputers at the National Energy Research Supercomputing Center (NERSC) and the Argonne Leadership Computing Center (ALCC). The MILC code currently is used for hundreds of millions of core-hours at NSF and DOE supercomputer centers.
Data analysis plays an important role in data-driven scientific discovery and commercial services. Judy Qiu's earlier research has shown that previous complicated versions of MapReduce can be replaced by Harp (a Hadoop plug-in) that offers both data abstractions useful for high performance iterative computation and MPI-quality communication that can drive libraries like Mahout, MLlib, and DAAL on HPC and Cloud systems. A subset of machine learning algorithms have been selected and will be implemented with optimal performance using Hadoop/Harp and Intel's library DAAL. The code will be tested on Intel Core™ and Intel Xeon Phi™ architectures.
- Kai ZheN, Mridul Birla, David Crandall, Bingjing Zhang, Judy Qiu, 3/15/2017, A Hybrid Supervised-unsupervised Method on Image Topic Visualization with Convolutional Neural Network and LDA, Indiana University
- Carleton DeTar, Douglas Doerfler, Steven Gottlieb, Ashish Jha, Balint Joo, Dhiraj Kalamkar, Ruizi Li, Doug Toussaint, 9/21/2016, MILC Staggered Conjugate Gradient Performance on Intel KNL, IXPUG
- Bingjing Zhang, Peng Bo, Judy Qiu, 6/26/2016, Model-Centric Computation Abstractions in Machine Learning Applications, Semantic Scholar
- Ruizi Li, Carleton DeTar, Douglas Doerfler, Steven Gottlieb, Ashish Jha, Dhiraj Kalamkar, Doug Toussaint, 11/3/2016, MILC staggered conjugate gradient performance on Intel KNL, Cornell University Library
- Bingjing Zhang, Peng Bo, Judy Qiu, 3/11/2016, Parallelizing Big Data Machine Learning Algorithms with Model Rotation, Semantic Scholar
- Carleton DeTar, Douglas Doerfler, Steven Gottlieb, Ashish Jha, Balint Joo, Dhiraj Kalamkar, Ruizi Li, Doug Toussaint, 9/19/2016, MILC Staggered Conjugate Gradient Intel KNL, Argonne National Labs
- Bingjing Zhang, Peng Bo, Judy Qiu, 9/1/2016, High Performance LDA through Collective Model Data Communication Optimization, Indiana University
- E. Gámiz, A. Bazavovb, C. Bernardc , C. DeTard , D. Due , A.X. El-Khadraf , E.D. Freelandg , Steven Gottliebh , U.M. Helleri , J. Komijanij , A.S. Kronfeldj,k , J. Laihoe , P.B. Mackenziek , E.T.Neill , T. Primerm, J.N. Simonek , R. Sugarn , D. Toussaintm, R.S. Van de Waterk , and Ran Zhou, 11/20/2016, Kaon semileptonic decays with Nf = 2+1+1 HISQ fermions and physical light-quark masses, Cornell University Library
- Ashish Jha, Vitali Morozov, Jack Deslippe, 9/19/2016, Vectorization Strategies for Intel's 2nd Generation Intel® Xeon Phi™ Architecture Codenamed Knights Landing,Argonne National Labs