FTXS 2025

News & Announcements

• [July 10, 2025] FTXS 2025 CANCELLED.  We have made the very difficult decision to cancel the workshop this year.

• [June 13, 2025] The submission deadline has been extended to June 26, 2025

• [May 23, 2025] Submission details have been added below

• [May 7, 2025] The submission dates and the date of the workshop have been added below.

• [April 5, 2025] Our proposal was accepted!  FTXS 2025 will be held in conjunction with ICPP 2025 in San Diego.  🎉🎉🎉

FTXS is broadly interested in research on characterizing and mitigating the impart of faults on HPC systems.   We are particularly interested in papers that address issues related to the following developments in extreme-scale systems:

• Artificial Intelligence and Machine Learning (AI/ML) Significant research has recently been published (including at SC23) on how AI/ML can be leveraged to improve the performance of extreme-scale systems. In the context of fault tolerance and resilience, AI/ML applications have the potential to exhibit novel failure modes during both training and inference. Additionally, AI/ML may help to mitigate failures by either: predicting when and where failures may occur, or by reducing the impact of failures that do occur. Our understanding of AI/ML along these two dimensions of fault tolerance is developing rapidly and is an important area of research.

• System Heterogeneity: Modern HPC systems increasingly include GPUs, FPGAs, and other types of accelerators. New networking devices like Data Processing Units (DPUs) and SmartNICs are also starting to be deployed. However, there are many resilience and fault tolerance issues associated with these devices that still need to be resolved. Papers at prominent recent conferences (including SC20, ICS 2019, and IEEE Cluster 2018) demonstrate that understanding the fault tolerance implications of heterogeneous compute devices is an important and active area of research.

• Computing Paradigms: Novel non-von Neumann computing paradigms, including quantum and neuromorphic computing, have attracted significant research interest. Recent publications demonstrate that understanding the fault tolerance implications of these computing paradigms is also an area of active research.

• Machine Learning: Algorithms that rely on elements of machine learning are becoming more and more prevalent on HPC systems.  Understanding how these algorithms react and respond to the frequency and variety of faults that occur on HPC systems is critical to ensuring that they continue to provide accurate and timely answers.

Additional topics of interest include, but are not limited to: 

• Techniques for both addressing faults in AI/ML applications and using AI/ML to mitigate faults

• Algorithmic-Based Fault Tolerance (ABFT) techniques to address undetected (silent) errors

• Silent data corruption (SDC) detection / correction techniques

• Novel fault-tolerance techniques and implementations

• Failure data analysis and field studies

• Power, performance, resilience (PPR) assessments / tradeoffs

• Emerging hardware and software technology for resilience

• Advances in reliability monitoring, analysis, and control of highly complex systems

• Failure prediction, error preemption, and recovery techniques

• Fault-tolerant programming models

• Models for software and hardware reliability

• Metrics and standards for measuring, improving, and enforcing effective fault-tolerance

• Scalable Byzantine fault-tolerance and security from single-fault and fail-silent violations

• Atmospheric evaluations relevant to HPC systems (terrestrial neutrons, temperature, voltage, etc.)

• Near-threshold-voltage implications and evaluations for reliability

• Benchmarks and experimental environments including fault injection

• Frameworks and APIs for fault-tolerance and fault management

Submissions are solicited in the following categories:

• Regular papers presenting innovative ideas improving the state of the art or discussing the issues seen on existing extreme-scale systems, including some form of analysis and evaluation.   Regular papers should not exceed eleven (10) pages, not including references.  Accepted regular papers that meet these requirements will be published. 

• Extended abstracts presenting preliminary results, proposing disruptive ideas, or challenging assumptions in the field.  The inclusion of some form of preliminary results is encouraged.  Extended abstract papers should not exceed four (4) pages, not including references.  Extended abstracts will be evaluated separately and given shorter oral presentations.

Submissions shall be submitted to  https://ssl.linklings.net/conferences/icpp/  and must conform to the requirements established by IEEE at: https://www.ieee.org/conferences/publishing/templates.html.  LaTeX and MS Word templates are also available at this link.

Program Committee

Rizwan A. Ashraf Pacific Northwest National Laboratory

Aurelien Bouteiller University of Tennessee

Jon Calhoun Clemson University

Chris Cantwell Imperial College, London

Zizhong Chen University of California, Riverside

James Elliott Sandia National Laboratories

Christian Engelmann Oak Ridge National Laboratory

Claudia Fohry University of Kassel

Qiang Guan Kent State University

Hemanth Kolla Sandia National Laboratories

Zhiling Lan University of Illinois Chicago

Nicolas Morales Sandia National Laboratories

Thomas Naughton Oak Ridge National Laboratory

Bogdan Nicolae Argonne National Laboratory, Illinois Institute of Technology

Yves Robert ENS Lyon, University of Tennessee

Thomas Ropars Grenoble Alpes University, France

Lipeng Wan Georgia State University