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Heterogeneity in Computing Workshop (HCW) 2018

8:45 – 9:00: Opening Remarks
Behrooz Shirazi (Washington State University, USA), Steering Committee Chair HCW
9:00 – 10:00: Morning Keynote
Managing Heterogeneity at Extreme Scales: A Data Perspective
Manish Parashar (Rutgers, The State University of New Jersey University)
10:00 – 10:30: Coffee Break
10:30 – 12:00: Session 1: Reconfigurable and Cloud Systems
(Session Chair: Loris Marchal, Ecole Normale Supérieure de Lyon)
Leslie Barron and Tarek Abdelrahman. User-Transparent Translation of Machine Instructions to Programmable Hardware
Yves Caniou, Eddy Caron, Aurélie Kong Win Chang and Yves Robert. Budget-aware scheduling algorithms for scientific workflows with stochastic task weights on IaaS \cloud platforms
Zheming Jin and Hal Finkel. Optimizing Parallel Reduction on OpenCL FPGA Platform – a Case Study of Frequent Pattern Compression
12:00 – 1:30: Lunch Break
1:30 – 3:30: Session 2: Workload Scheduling and Architecture Analysis
(Session Chair: Hal Finkel, Argonne National Laboratory)
Massinissa Ait Aba, Lilia Zaourar and Alix Munier. Approximation algorithm for scheduling applications on hybrid multi-core machines with communications delays
Sean Pennefather, Karen Bradshaw and Barry Irwin. Exploration and Design of a Synchronous Message Passing Framework for a CPU-NPU Heterogeneous Architecture
Fei Lei, Lei Yu, Bing Shao, Fei Teng and Bo Zhou. Large Scale Data Centers Simulation based on Baseline Test Model
Anke Kreuzer, Norbert Eicker, Jorge Amaya and Estela Suarez. Application performance on a Cluster-Booster system
3:30 – 4:00: Coffee Break
4:00 – 5:00: Closing Keynote
Challenges and Opportunities in Heterogenous Computing – Applications Perspective
Umit Catalyurek (Georgia Institute of Technology) 


Managing Heterogeneity at Extreme Scales: A Data Perspective

Manish Parashar
Distinguished Professor of Computer Science
Rutgers, The State University of New Jersey University


Data-related challenges are dominating computational and data-enabled sciences and are limiting the potential impact of scientific application workflows enabled by extreme scale computing environments. While data staging and in-situ/in-transit data processing have emerged as attractive approaches for supporting these extreme scale workflows, the increasing heterogeneity of the storage hierarchy, coupled with increasing data volumes and complex and dynamic data access/exchange patterns, are impacting the effectiveness of this approach. In this talk I will discuss these challenges and explore how autonomic runtime techniques are being explored to address them. I will then present autonomic policies as well as cross layer mechanisms that are part of DataSpaces, an extreme scale data staging service. This research is part of the DataSpaces project at the Rutgers Discovery Informatics Institute.

About the speaker:

Manish Parashar is Distinguished Professor of Computer Science at Rutgers University. He is also the founding Director of the Rutgers Discovery Informatics Institute (RDI2). He is currently on an IPA appointment at the National Science Foundation. His research interests are in the broad areas of Parallel and Distributed Computing and Computational and Data-Enabled Science and Engineering. Manish is the founding chair of the IEEE Technical Consortium on High Performance Computing (TCHPC), Editor-in-Chief of the IEEE Transactions on Parallel and Distributed Systems. He has received a number of awards for his research and leadership, and is Fellow of AAAS, Fellow of IEEE/IEEE Computer Society and ACM Distinguished Scientist. For more information please visit

Challenges and Opportunities in Heterogeneous Computing – Applications Perspective

Umit Catalyurek
Professor and Associate Chair of the School of Computational Science and Engineering, Georgia Institute of Technology


Heterogeneity in computing has been with us for a long time, and it is here to stay for a foreseeable future too. In this talk, with some diverse set of application examples, ranging from histopathology image analysis to graph analytics, we will discuss the challenges of application developers for developing efficient, scalable and maintainable applications for heterogeneous systems, and associated opportunities for systems researchers in this field.

About the speaker:

Ümit V. Çatalyürek is currently a Professor and the Associate Chair of the School of Computational Science and Engineering in the College of Computing at the Georgia Institute of Technology. He received his Ph.D., M.S. and B.S. in Computer Engineering and Information Science from Bilkent University, Turkey, in 2000, 1994 and 1992, respectively. Dr. Çatalyürek is a Fellow of IEEE, member of ACM and SIAM, and the elected Chair for IEEE TCPP for 2016-2019, and Vice-Chair for ACM SIGBio for 2015-2018 term. Dr. Çatalyürek currently serves as the Editor-in-Chief for Parallel Computing, and as an editorial board member for IEEE Transactions on Parallel and Distributed Computing. He also serves on the program committees and organizing committees of numerous international conferences. Dr. Çatalyürek is a recipient of an NSF CAREER award and is the primary investigator of several awards from the NSF, DTRA, DoE, and NIH.  He has co-authored more than 200 peer-reviewed articles, invited book chapters and papers. His main research areas are in parallel computing, combinatorial scientific computing and biomedical informatics. More information about Dr. Çatalyürek and his research group can be found at


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