## Workshop Chairs

- Prof. Jesus Carretero, University Carlos III of Madrid, Spain.
- Prof. Martin Schulz, Technical University of Munich, Germany.
- Prof. Estela Suarez, Juelich Supercomputing Centre, Forschungszentrum Juelich GmbH and University of Bonn, Germany.

## Motivation and Objectives

The current static usage model of HPC systems is becoming increasingly inefficient. This is driven by the continuously growing complexity and heterogeneity of system architectures, in combination with the increased usage of coupled applications, the need for strong scaling with extreme scale parallelism, and the increasing reliance on complex and dynamic workflows. As a consequence, we see a rise in research on dynamic resource management in HPC, including malleable systems, middleware software, and elastic applications, which are designed to adjust resource usage dynamically in order to extract the maximum efficiency of large-scale clusters. By providing an intelligent global coordination of resource usage, through runtime scheduling of computation, network usage and I/O across all components of the system architecture, malleable HPC systems can maximize the exploitation of the available resources, while at the same time minimizing the overall makespan of applications in many, if not most, cases. Of particular concern is the emerging class of data-intensive applications and their interactions with classic simulation workloads, driven by the growing need to process extremely large data sets. Further, by utilizing new scheduling paradigms for emerging multi-tier storage hierarchies, malleability allows to dynamically adjust the computation and storage needs of applications, on the one side, and the global system on the other.

Such malleable systems, however, face a series of fundamental research challenges, including: How do we capture the current status of systems and detect inefficient resource usage? Who initiates changes in resource availability or usage? How is it communicated? How to compute the optimal usage? How can applications cope with dynamically changing resources? What should malleable programming models and abstractions look like? How to design resource management frameworks for malleable systems? Which resources benefit from malleability and which (if any) should still be managed statically?

In order to address these challenges, the HPCMALL 2026 workshop will bring together researchers from diverse areas of HPC that are impacted or actively pursuing malleability concepts, from application developers to system architects, from programming models to system software researchers. In addition to high-quality, refereed publications and talks, the workshop will provide a lively discussion forum for researchers working in HPC and pursuing the concepts of and around malleability, to reflect on the advances achieved in the field since the previous editions of this workshop.

### Topics

We are looking for original high-quality research and position papers on applications, services, and system software for malleable high-performance computing systems. Topics of interest include, but are not limited to:

- System and system architecture considerations in designing malleable architectures.

- Emerging software designs to achieve malleability in high-performance computing.

- High-level parallel programming models and programmability techniques to improve applications malleability.

- Runtime techniques to provide malleable execution models for computation, communication and I/O.

- Resource management frameworks and interfaces supporting malleable scheduling, resource allocations and application execution.

- Computing and I/O scheduling algorithms providing and/or exploiting static or dynamic malleability.

- Interaction between state-of-the-art HPC systems and large-scale disaggregated resources, e.g., for AI or Quantum appliances, and their dynamic usage.

- Use of AI and ML techniques to steer malleability in systems and applications.

- Ad-hoc storage systems and I/O scheduling techniques helping I/O malleability.

- Support for malleable execution of applications in performance, debugging and correctness tools.

- Energy efficiency and malleability (applications, over-provisioned systems wrt. power/energy, storage systems, etc.).

- Experiences and use cases applying malleability to HPC applications.



## Publication

Papers will be published together with SCA/HPCAsia proceedings.

## Submission Guidelines

### Online Submission System

Authors submitting papers for HPCMALL 2026 must do so via the "EasyChair submission web page for HPCMALL2026" (https://easychair.org/conferences?conf=hpcmall2026). Authors are invited to submit technical papers of no more than 12 pages in PDF format, including figures and references. The papers should be formatted according to the ACM Proceedings Style and submitted through the Online Submission System.

Submitted papers must contain original work that has not appeared in and is not under consideration for another conference, journal, or workshop. The review process is double-blind. There will be no revision rebuttal process and the review will be one-pass.

### Submission Format

All authors should submit manuscripts for review in a single-column format. Manuscripts must be at most 12 pages in PDF format including figures and references, formatted according to the ACM Proceedings Style. The ACM templates for Word and LaTeX are shown below. Also, ACM has partnered with Overleaf and the ACM LaTeX template on Overleaf platform is available.

Please follow STEP 1 (Microsoft Word/LaTeX) at "2. The Workflow and Templates" in [https://www.acm.org/publications/authors/submissions](https://www.acm.org/publications/authors/submissions). Please note that there are two different instructions for Word and LaTeX template users.

## ACM Templates
* Word (docx) - [download](https://www.acm.org/binaries/content/assets/publications/taps/acm_submission_template.docx)
* LaTex (zip) [download](https://portalparts.acm.org/hippo/latex_templates/acmart-primary.zip)
use a "manuscript" format option (Please refer to sample/sample-manuscript.tex).
* Overleaf use a "manuscript" format option.