PAISE 2022

4th Workshop on Parallel AI and Systems for the Edge

PAISE 2022 will be Virtually co-conducted with IPDPS 2022 on Friday, 3rd June 2022.

Past Editions:

2021 2020 2019


Industry Partners


Applications involving voluminous data require that the computing be performed as close to the data source as possible, due to communication constraints, privacy and sensitivity of data, latency and liveliness requirements, or costs of moving data. 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 computing platforms (hardware and software) are venturing farther away from the center and enabling computation closer to the physical world, often at the interface to the physical world. Such edge computing platforms greatly vary in computational resources, spanning from intelligent embedded devices like smart cameras, powerful on-premise systems.

The resulting diversity in edge-computing platforms in terms of capabilities, architectures, and programming models as well as the various runtime requirements and resource constraints of the various edge applications poses several new challenges. Some edge applications may need to run continuously, with pre-allocated resources, whereas others may run when particular events occur, with on-demand resource allocation. Due to the usually limited capacity at the edge in terms of computation, energy and network bandwidth, these applications need to be scheduled simultaneously and run concurrently. Consequently, a future with heterogeneous edge hardware and multiple applications sharing the underlying resources becomes imminent.

Furthermore, situations may warrant running applications in sandboxes for privacy and security. As we push more toward edge-enabled networks of devices, we inherit a setting where resources are deployed away from the safety of secure indoor spaces, often in the midst of a bustling urban canyon, and exposed to physical and cybersecurity threats. Deployed and interconnected predominantly over public networks, these systems have to be designed with cybersecurity as a first-class design citizen, rather than introduced as an afterthought, ensuring not only the integrity and confidentiality of the data, but also the correct and accountable processing of it.

Deploying and managing such applications with diverse properties at the edge in a concurrent manner requires considerations for multitenancy and presents a challenge that requires cooperation and coordination between the various components of the software stack. Mechanisms need to be devised that communicate both data and control with the applications in order to fine-tune their behavior and change their operational parameters. Realizing the computing continuum and coupling these edge applications with centrally located cloud and HPC resources and applications also opens up many research areas.

Another prominent and relevant advancement to this evolving landscape is the evolution of the last-mile wireless connectivity. The emergence of 5G and Wi-Fi 6, and the likely convergence, will initially provide a combination of bandwidth improvements, and latency reduction. Together with advancements in processor technology, this will enable us to deploy more advanced sensors, actuators and services than what is possible today. The next-generation wireless connectivity will also employ radio base stations more densely and with substantially higher computing capability for both core operations and as services for end users. The allocation and orchestration of these computing resources for various competing user needs and network functions will share many challenges currently encountered in edge-computing. Perhaps, the largest DevOps and management challenges in edge-computing at infrastructure level may be witnessed in this space.

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

  • processing — artificial intelligence, computer vision, machine learning, data reduction;
  • management — parallel and distributed programming models for resource-constrained and domain-specific hardware, containers, remote resource management, DevOps, runtime-system design, and cybersecurity; and
  • hardware — systems and devices conducive to use in resource-constrained (energy, space, etc.) and harsh edge-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 three broad topics including Edge AI/ML and Data, Edge Architecture and Practice. In particular, we welcome work and discussions on:

    • Adaptive Training Sampling
    • AI Enabled IoT Applications at the Edge
    • Collaborative Training at the Edge
    • Cyber-Security and Privacy Aspects of Edge Computing
    • DevOps for Deploying and Managing Applications at the Edge
    • Distributed Data and Storage Orchestration and Management
    • Distributed Inference
    • Edge driven HPC, and HPC steered Edge Computing
    • Enabling SDN NFV at the Edge
    • Energy Efficient Processors for Training and Inference
    • Hardware for Edge-computing and Machine Learning
    • Opportunities for Edge Computing driven by WiFi-Cellular (5G/WiFi6) Convergence
    • Programming Models for Edge Computing
    • Software and Hardware Multitenancy 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: Full research papers should describe original work and be 7-8 pages in length. The papers will be presented as 20 min talks.
  • Short Papers: Short research papers, 4-5 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. The papers will be presented as 15 min talks.
  • Concept Papers and Practitioner Reports: Short papers, reports and extended abstracts 2 pages in length. These papers can describe new concepts, emerging hardware and Software platforms, DevOps and Management of IoT/Edge. 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. The papers will be presented as 8-10 min lightning-talks.

Templates for MS Word and LaTeX provided by IEEE eXpress Conference Publishing are available for download. See the latest versions here.

Here is a link to the EasyChair CFP. Upload your submission to EasyChair submission server in PDF format. Accepted manuscripts will be included in the IPDPS workshop proceedings.

Important Dates:

  • February 7th AOE, February 25th AOE, 2022: Submission deadline extended!
  • March 7th, 2022, March 15th, 2022 : Notification of acceptance.
  • March 15th, 2022, March 21st, 2022 : Camera ready papers due.

Confirmed Program Committee

  • Utku Gunay Acer, Nokia Bell Labs
  • Paarijaat Aditya, Nokia Bell Labs
  • Marco Brocanelli, Wayne State University
  • Kevin Chan, Army Research Laboratory
  • Ruichuan Chen, Nokia Bell Labs
  • Lucy Cherkasova, ARM Research
  • Nicolas Erdody, Open Parallel
  • Nicola Ferrier, University of Chicago
  • Dhiraj Joshi, IBM Research
  • Takayuki Katsuki, IBM Research Tokyo
  • Hana Khamfroush, University of Kentucky
  • Dawei Li, Amazon Inc.
  • Eric Matson, Purdue University
  • Chulhong Min, Nokia Bell Labs
  • Alessandro Montanari, Nokia Bell Labs
  • Priya Panda, Yale University
  • Michael Papka, Northern Illinois University
  • Sekou Remy, IBM Research Africa
  • Koichi Shinoda, Tokyo Institute of Technology
  • Eric Van Hensbergen, ARM Research
  • Blesson Varghese, Queen's University,Belfast
  • Yuxiong Wang, University of Illinois
  • Wei Wang, The Hong Kong University of Science and Technology
  • Feng Yan, University of Nevada, Reno
  • Kazutomo Yoshii, Argonne National Laboratory

General Chairs

Workshop Organizers