The 2nd WORKSHOP ON HIGH PERFORMANCE SERVERLESS COMPUTING (2022)

Held in conjunction with ACM HPDC 2022
Minneapolis, Minnesota, United States. 30th June 2022

WORKSHOP OVERVIEW

Serverless computing represents the next significant leap forward with respect to abstracting commoditized computing resources. The main principle of serverless computing is that compute providers deploy and manage the entire compute environment---from hardware through to runtime in which an application executes; users therefore think entirely at the level of their application without regard for the underlying computing environment. For example, the function as a service (FaaS) model allows users to first register a programming function (e.g., in Python) and then they may invoke that function many times with different input arguments.

Serverless computing is poised to become not only the face of cloud computing in the commercial world, but also a model for remote and distributed computing more broadly. The workshop on High Performance Serverless Computing will provide the high performance and distributed computing community with a dedicated forum for discussing foundational research in serverless computing in both industry and academia. The workshop will bring together these communities and provide a forum for innovation in both the high performance and distributed systems that underlie serverless computing platforms and also the use of serverless models for abstracting traditional high performance and distributed computing systems.

TOPICS

We invite the submission of original work that is related to the topics outlined below.

  • Developing high performance serverless computing platforms
  • Federation of serverless computing platforms
  • Container management and scheduling
  • Programming paradigms for serverless computing
  • Data management for serverless computing
  • Applications of serverless computing
  • Benchmarking and performance of serverless computing
  • On-demand and event-based computation
  • Serverless economics and billing models
  • Fault tolerance and reliability
  • Data-intensive workloads and tools
  • Productivity tools (Debugging, Profiling, Logging, etc)
  • Stream and events processing
  • Security in serverless
  • Heterogeneous computing (GPU, Accelerators, exotic architectures)

SUBMISSION

Important Dates

  • Papers due: April 8, 2022 AoE April 15, 2021 AoE
  • Notifications: May 02, 2022
  • Camera ready: May 09, 2022
  • Workshop date: June 30, 2022

Paper Categories

Authors are invited to submit:
  • Full 8-page papers
  • Short/work-in-progress 4-page papers

Submission

Authors are invited to submit papers describing unpublished, original research. All submitted manuscripts should be formatted using the ACM Master Template with sigconf format (please be sure to use the current version). All necessary documentation can be found at: https://www.acm.org/publications/proceedings-template.

Papers may be either full (8 pages) or short (4 pages) including all text, figures, and references. Papers will be peer-reviewed (single blind), and accepted papers will be published in the workshop proceedings as part of the ACM Digital Library.

Papers conforming to these guidelines should be submitted through EasyChair

ORGANIZATION

General Chairs

To contact the chairs, please use the email addresses listed above.

Program Committee Members

  • Istemi Ekin Akkus (Nokia Bell Labs)
  • Yue Cheng (George Mason University)
  • Stephen Fink (Facebook)
  • Geoffrey C. Fox (University of Virginia, Charlottesville, VA)
  • Rohan Gard (Nutanix Inc)
  • Volker Hilt (Nokia Bell Labs)
  • Dan Katz (National Center for Supercomputing Applications)
  • Jay F. Lofstead II (Sandia National Laboratories)
  • Peter Pietzuch (Imperial College London)
  • Tyler Skluzacek (University of Chicago)
  • Douglas Thain (University of Notre Dame)
  • Devesh Tiwari (Northeastern University)
  • Wei Wang (The Hong Kong University of Science and Technology)
  • Rich Wolski (University of California, Santa Barbara)
  • Justin Wozniak (Argonne National Laboratory)
  • Guoyao Xu (Alibaba Group)
  • Hong Zhang (The Hong Kong University of Science and Technology)
  • Laiping Zhao (Tianjin University)
  • Zhi Zhou (Sun Yat-sen University)