[hpc-announce] ACM HPDC 2018 Call For Papers

Song, Shuaiwen Shuaiwen.Song at pnnl.gov
Mon Oct 16 09:26:12 CDT 2017

                                      **** CALL FOR PAPERS ****

                             The 27th International ACM Symposium on

             High-Performance Parallel and Distributed Computing

                             Phoenix, AZ, United States - June 11-15, 2018


Sponsored by ACM SIGARCH

The ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC) is the premier annual conference for presenting the latest research on the design, implementation, evaluation, and the use of parallel and distributed systems for high-end computing. The 27th HPDC will take place in Tempe, AZ on June 11-15, 2018. 


Abstract due: January 17, 2018

Papers due: January 24, 2018

Author Notifications: March 29, 2018

Camera ready: April 12, 2018

Conference dates: June 11 - 15, 2018


Submissions are welcomed on high-performance parallel and distributed computing (HPDC) topics including but not limited to: clouds, clusters, grids, big data, massively multicore, and extreme-scale computing systems. Submissions that focus on the operating systems, runtime environments, architectures, and networks of high end computing systems are particularly encouraged. Experience reports of operational deployments that provide significantly novel insights for future research on HPDC applications and systems will also receive special consideration. All papers will be evaluated for their originality, technical depth and correctness, potential impact, relevance to the conference, and quality of presentation. Research papers must clearly demonstrate research contributions and novelty, while experience reports must clearly describe lessons learned and demonstrate impact.

In the context of high-performance parallel and distributed computing, the topics of interest include, but are not limited to:

·        Operating systems, networks, and architectures
·        High performance runtime environments
·        Massively multicore systems, including heterogeneous systems
·        Datacenter technology, resource virtualization
·        Programming languages, APIs, and system interoperation approaches
·        File and storage systems, I/O, and data management
·        Big data stacks and big data ecosystems
·        Resource management and scheduling, including energy-aware techniques
·        Performance modeling, analysis, and engineering
·        Fault tolerance, reliability, and availability
·        Operational guarantees, and risk assessment and management
·        Traditional and emerging applications and services that depend upon high- end computing


Note: The review process is not double-blinded; the authors can reveal their identities in the paper (It's also OK to conceal them if they so wish).

Authors are invited to submit technical papers of at most 12 pages in PDF format, including figures and references. Papers should be formatted in the ACM Proceedings Style and submitted via the conference web site. Accepted papers will appear in the conference proceedings, and will be incorporated into the ACM Digital Library. Submitted papers must be original work that has not appeared in and is not under consideration for another conference or a journal.

General Chair:

Ming Zhao
Arizona State University, USA

Technical Program Co-Chairs:

Abhishek Chandra
University of Minnesota, USA

Lavanya Ramakrishnan
Lawrence Berkeley National Lab, USA

Program Committee:

Adriana Iamnitchi                                University of South Florida, USA
Ali Butt                                               Virginia Tech, USA
Ana Lucia Varbanescu                          University of Amsterdam, The Netherlands
Andre Luckow                                     BMW IT Research Center, USA
Andrew A. Chien                                 University of Chicago and Argonne National Laboratory, USA
Arthur Maccabe                                  Oak Ridge National Laboratory, USA
Aydin Buluc                                        Lawrence Berkeley National Laboratory, USA
Bogdan Nicolae                                   IBM Research, Ireland
Christine Morin                                    INRIA, France
David Abramson                                 The University of Queensland, Australia
David Eyers                                        University of Otago, New Zealand
David Irwin                                        University of Massachusets at Amherst, USA
Dean Hildebrand                                 Google, USA
Dick Epema                                        Delft Unviersity of Technology, The Netherlands
Dilma Da Silva                                    Texas A&M University, USA
Douglas Thain                                    Notre Dame, USA
Evgenia Smirni                                   College of William and Mary, USA
Franck Cappello                                  Argonne National Laboratory, USA
Gabriel Antoniu                                  INRIA, Rennes, France
Hang Liu                                           University of Massachusets at Lowell, USA
Henri Bal                                           Vrije University, The Netherlands
Ian Foster                                         University of Chicago and Argonne National Lab, USA
Jay Lofstead                                      Sandia National Laboratories, USA
John (Jack) Lange                              University of Pittsburgh, USA
Jon Weissman                                    University of Minnesota, USA
Judy Qiu                                            Indiana University, USA
Kartik Gopalan                                   Binghamton University, USA
Kate Keahey                                      Argonne National Laboratory, USA
Kenjiro Taura                                     University of Tokyo, Japan
Liana Fong                                        IBM, USA
Manish Parashar                                Rutgers University, USA
Matei Ripeanu                                   University of British Columbia, Canada
Michela Becchi                                   North Carolina State University, USA
Michela Taufer                                   University of Delaware, USA
Narayanan Sundaram                         Intel, USA
Patrick Bridges                                  University of New Mexico, USA
Peter Dinda                                      Northwestern University, USA
Radu Prodan                                     University of Innsbruck, Austria
Renato Figueiredo                              University of Florida, USA
Samer Al-Kiswany                              University of Waterloo, Canada
Sangmi Pallickara                               Colorado State University, USA
Shantenu Jha                                    Rutgers University, USA
Shuaiwen Leon Song                          Pacific Northwest National Laboratory and William & Mary
Sriram Govindan                                Microsoft Research, USA
Sudharshan Vazhkudai                       Oak Ridge National Laboratory, USA
Xiaosong Ma                                     Qatar Computing Research Institute, Qatar
Yue Cheng                                        George Mason University, USA
Zizhong Chen                                    University of California, Riverside, USA

Shuaiwen Leon Song
Senior Staff Scientist
HPC Group, Advanced Computing, Mathematics, and Data Division,
Pacific Northwest National Lab (PNNL);
Adjunct Scholar, CS department, College of William and Mary

You’re only given a little spark of madness. If you lose that, you are nothing.
-- Robin Williams

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