Accelerated HPC in the Cloud edge Continuum (AHPC3)
AHPC3 website: http://ahpc3.di.unipi.it/2026/
Aims and Scope
The Accelerated HPC in the Cloud-Edge Continuum (AHPC3) workshop is a leading forum for presenting the latest advances in the convergence of high-performance computing (HPC) with cloud-edge continuum architectures. AHPC3 focuses on innovative solutions for sustainable, energy-efficient, and intelligent execution of data-intensive and AI-driven workloads across heterogeneous infrastructures, promoting dynamic orchestration, network-aware optimizations, and federated learning across distributed environments.
This 3rd edition will be held in conjunction with PDP 2026, providing an excellent opportunity to share research findings and foster collaborations in this rapidly evolving field.
Topics of interest include (not limited to) the following:
- Cloud-Edge Architectures & Virtualization: Design and evaluation of novel architectures and lightweight execution environments (e.g., microservices, unikernels, WebAssembly, microVMs) to enable scalable and efficient HPC in the Cloud-Edge continuum.
- Orchestration & Resource Management: Techniques for orchestration, deployment, and scheduling of HPC workflows across federated Cloud-Edge infrastructures; methodologies for heterogeneous resource management and efficient workload allocation.
- Programming Paradigms & Data Management: New programming models and paradigms for Cloud-Edge HPC; advanced mechanisms for communication, data handling, and workflow management in distributed environments.
- Reliability, Security & Sustainability: Fault-tolerance, reliability, and security in Cloud-Edge HPC systems; strategies for sustainable, energy-efficient, and environmentally aware distributed computing.
- Accelerated & Data-Intensive Computing: Exploiting GPUs, FPGAs, and specialized accelerators for HPC in Cloud-Edge environments; support for data-intensive workloads, data stream processing, and benchmarking at scale.
- AI/ML & Federated Approaches: Integration of AI/ML techniques for optimization, orchestration, and performance tuning; federated resource sharing and federated learning across hybrid Cloud-Edge HPC environments.
Important dates
Abstract submission: October 30, 2025 November 27, 2025 (EXTENDED)
Full paper submission: November 11, 2025 December 4, 2025 (EXTENDED)
Author notification: December 16, 2025 January 6, 2026 (EXTENDED)
Camera ready: January 20, 2026
Submission guidelines
The workshop welcomes research papers and experience papers; nevertheless, papers describing novel research contributions and innovative applications are of particular interest. The workshop welcomes research papers and experience papers. Nevertheless, papers describing novel research contributions and innovative applications are of particular interest. Contributions can be:
- Regular papers (maximum 8 pages) should present innovative works whose claims are supported by solid justifications;
- Short papers (maximum 4 pages) should target position papers.
Authors should submit papers in the IEEE Conference Proceedings Format (double-column, 10pt size fonts) and follow format guidelines found at https://www.ieee.org/conferences/publishing/templates.html.
For submission, please refer to the Easychair submission system as indicated in the Main Conference webpage, and make sure that you select the “Accelerated HPC in the Cloud edge Continuum (AHPC3)” track.
All submissions will be peer-reviewed by at least three members of the program committee.
Reviews will be double-blind, so authors should ensure that their identity is not revealed in the paper.
Chairs
Luca Ferrucci – University of Pisa, Italy (contact: luca.ferrucci@unipi.it)
Stefano Forti – University of Pisa, Italy
Valerio Besozzi – University of Pisa, Italy
Jacopo Massa – University of Pisa, Italy
Matteo Della Bartola – University of Pisa, Italy
Program Committee
Jörn Altmann, Seoul National University, South Korea
Hojjat Baghban, Chang Gung University, Taiwan
Roberto Casadei, University of Bologna, Italy
Emanuele Carlini, ISTI-CNR, Italy
Massimo Coppola, ISTI-CNR, Italy
Patrizio Dazzi, University of Pisa, Italy
Karim Djemame, University of Leeds, UK
SongHee Kang, Tech University of Korea, South Korea
Ioannis Kontopoulos, ICCS-NTUA, Greece
Isaac Lera, University of Balearic Islands, Spain
Andrea Michienzi, University of Pisa, Italy
Matteo Mordacchini, IIT-CNR, Italy
Paolo Palazzari, ENEA, Italy
Gabriele Russo Russo, Università degli Studi di Roma “Tor Vergata”, Italy
Nishant Shaurab, University of Utrecht, Netherlands
José Luis Vázquez-Poletti, Universidad Complutense de Madrid, Spain