[hpc-announce] PAISE-2020 Call for Paper: 2nd Workshop on Parallel AI and Systems for the Edge (Co-located with IPDPS-2020), New Orleans, USA.

Rajesh Sankaran rajesh at anl.gov
Mon Dec 9 11:06:53 CST 2019


  PAISE 2020: 2nd Workshop on Parallel AI and Systems for the Edge

  Held in conjunction with IPDPS 2020
  Friday, 22 May 2020,
  New Orleans, USA


  Applications involving voluminous data but needing low-latency computation and
  local feedback require that the computing be performed as close to the data
  source as possible --- often at the interface to the physical world. Communication
  constraints and the need for privacy-preserving approaches also dictate the need
  for computing at the edge. Given the growth in such application scenarios and
  the recent advances in algorithms and techniques, machine learning and inference
  at the edge are unfolding and growing at a rapid pace. In support of these
  applications, a wide range of hardware (CPUs, GPUs, FPGAs, ASICs) is venturing
  farther away from the center, closer to the physical world. The resulting diversity
  in edge-computing hardware in terms of capabilities, architectures, and programming
  models poses several new challenges.

  The goal of this workshop is to gather the community working in three broad areas:

  1. processing -- artificial intelligence, computer vision, machine learning
  2. management -- parallel and distributed programming models for
  resource-constrained and domain-specific hardware, containers, remote
  resource management, runtime-system design, and cybersecurity and
  3. hardware -- systems and devices conducive to use in resource-constrained
  (energy, space, etc.) applications.

  The workshop will provide a critically needed opportunity to discuss the current
  trends and issues, to share visions, and to present solutions.


  For this workshop we welcome original work covering different aspects of:

     - Edge Inference
     - Hardware for Edge-computing and Machine Learning
     - Energy Efficient Processors for Training and Inference
     - Computer Vision at the Edge
     - Cyber Security for Edge Computing
     - Software and Hardware Multitenancy at the Edge
     - Machine Learning Hardware
     - On device machine learning algorithms
     - Real-time computer vision and speech processing
     - Learning-enabled IoT applications
     - Distributed inferencing and learning
     - 5G for Science and Edge Computing
     - Programming Models for Edge Computing
     - Coupling HPC to Edge Applications
     - Communication and Control Strategies for Deploying and Managing Applications at the Edge

  Paper Submission, Paper Style, and Proceedings:

  All papers must be original and not simultaneously submitted to another journal
  or conference. The papers submitted to the workshop will be peer reviewed by a
  minimum of 3 reviewers.

  The following paper categories are welcome:

* Full Papers: Research papers should describe original work and be 8 or 10
  pages in length.

* Short Papers: Short research papers, 4 pages in length, should contain
  enough information for the program committee to understand the scope of the
  project and evaluate the novelty of the problem or approach.

* Emerging Platforms and Practitioner Reports: Short reports, 3-6 pages in
  length, describing novel hardware and Software platforms, including initial
  proof-of-concept design and implementation are welcome. Reports may also focus
  on a particular aspect of technology usage in practice, or describe broad
  project experiences. They may describe a particular design idea, or experience
  with a particular piece of technology.

  Here is a link to the EasyChair CFP with additional details-


  Upload your submission to EasyChair submission server in PDF format. Accepted
  manuscripts will be included in the IPDPS workshop proceedings.

  Important Dates:

    * February 3rd, 2020: Submission deadline.
    * March 9th, 2020: Notification of acceptance.
    * May 22nd, 2020: Workshop

  Program Committee:

     Chris Adeniyi-Jones, ARM Research, USA
     Anish Arora, The Ohio State University, USA
     Cristiana Bentes, Universidade do Estado do Rio de Janeiro (UERJ), Brazil
     Sergio Armando Gutierrez Betancur, Universidad de Medellin, Colombia
     Marco Brocanelli, Wayne State University, USA
     Lucy Cherkasova, ARM Research, USA
     Charlie Catlett, Argonne National Laboratory, USA
     Nicolas Erdody, Open Parallel, New Zealand
     Felipe M. G. Franca, Universidade Federal do Rio de Janeiro (UFRJ), Brazil
     Nicola Ferrier, University of Chicago, USA
     Dennis Gannon, Indiana University Bloomington, USA
     Eric Van Hensbergen, ARM Research, USA
     Sandip Kundu, University of Massachusetts Amherst, USA
     Priscila Machado Vieira Lima, Universidade Federal do Rio de Janeiro, Brazil
     Leandro Marzulo, Google LLC, USA
     Alan Mainwaring, Intel Corporation, USA
     Eric Matson, Purdue University, USA
     Michael Papka, Northern Illinois University, USA
     Dhrubojyoti Roy, The Ohio State University, USA
     Mina Sartipi, University of Tennessee at Chattanooga, USA
     Koichi Shinoda, Tokyo Institute of Technology, Japan
     German Sanchez Torres, Universidad del Magdalena, Colombia
     Jerry Trahan, Louisiana State University, USA
     Sean Shahkarami, University of Chicago, USA
     Weisong Shi, Wayne State University, USA
     Ramachandran Vaidyanathan, Louisiana State University, USA
     Kazutomo Yoshii, Argonne National Laboratory, USA

  Workshop Organizers:

* Peter Beckman, Mathematics and Computer Science Division, Argonne National
  Laboratory, USA, E-mail: beckman at mcs.anl.gov

* Rajesh Sankaran, Mathematics and Computer Science Division, Argonne National
  Laboratory, USA, E-mail: rajesh at mcs.anl.gov

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