[hpc-announce] [CFP] IA^3 2025: 15th SC Workshop on Irregular Applications: Architectures and Algorithms

[Tumeo, Antonino]

IA^3 2025
15th Workshop on Irregular Applications: Architectures and Algorithms
https://urldefense.us/v3/__https://hpc.pnl.gov/IA3/__;!!G_uCfscf7eWS!a_58iIeDFteE1Lx1Nu0mOtj8yVuURRAE8PCtM58QYQn_EhqTjND4ns1yHoplZ3EWNgcIr1M2JPCixeqjNQJNSTFv5hWfGz8uEA$ 
November 16, 2025
St. Louis, MO
In conjunction with SC25

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CALL FOR PAPERS
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Emerging data-intensive, supercomputing applications are evolving towards a convergence of scientific simulations, data analytics, and learning algorithms. Components of these applications belong to both established and emerging fields, such as machine learning, social network analysis, bioinformatics, semantic graph databases, Computer Aided Design (CAD), and computer security. In processing massive volumes of unstructured data, components often perform many irregular, fine-grained accesses and synchronization events. Because current high-performance programming models, runtimes, and architectures rely on regular task graphs, bulk synchronous communications, and high temporal and spatial data locality to reduce latency, it is difficult to express irregular applications in current HPC programming models and scale performance on current supercomputing machines. Developing improved programming and execution models that address the problems of irregular applications is critical to solving the data challenges in large-scale science and data analytics.

This workshop explores solutions to support the efficient execution of irregular applications in the form of new features at the micro and system architecture, network, language and library, runtime, compiler, algorithm, and performance study levels.

Special Topic on Dynamic Networks: Similar to last year, the workshop will offer a special subtopic on dynamic network analysis. We invite papers on:
- Application of dynamic networks in different domains
- Algorithms and data structures for analyzing large dynamic networks
- Use of machine learning in dynamic graph analysis
- Position papers on advances and challenges in dynamic graph analysis

Topics of interest for the workshop  (not including the special topic), of both theoretical and practical significance, include but are not limited to those listed below. For the sake of simplicity, we have categorized them, but the submission track will be one.

Architectures and Systems for Irregular Workloads
- Computer micro- and system architectures: multi- and many-core design, heterogeneous processors, GPUs, vector processors, automata processors, AI and ML accelerators, reconfigurable architectures (CGRA, FPGAs), and custom processors.
- Interconnects and network architectures: high-radix networks, optical interconnects.
- Emerging memory architectures: including processor-in-memory designs.
- The impact of emerging computing paradigms: neuromorphic processors, quantum computing.
- Modeling, simulation, and evaluation of novel architectures for irregular workloads.

Programming Models, Languages, and Tools
- Programming models and languages designed for irregular computation.
- Libraries and runtime support for dynamic and irregular workloads.
- Compiler techniques and static/dynamic analysis for optimizing irregular applications.
- Parallelization techniques and data structures for irregular workloads.
- Data structures that combine regular and irregular computations (e.g., attributed graphs).

Algorithms and Computational Techniques
- Innovative algorithmic techniques for irregular workloads.
- Combinatorial algorithms: graph algorithms, sparse linear algebra, etc.
- Techniques for managing massive unstructured datasets, including streaming data.
- Integration of graph algorithms with machine learning techniques.

Applications and Use Cases
- Emerging applications that integrate scientific simulations, data analysis, and learning, and require efficient execution of irregular workloads.
- High-performance data analytics applications, including:
    - Graph databases and semantic web technologies, etc.
    - Bioinformatics: genome sequencing, protein interaction networks, etc.
    - CAD for microelectronics: irregular mesh processing, layout optimization, etc.
    - Cybersecurity: anomaly detection in dynamic networks, etc.
    - Social network analysis: community detection, influence propagation.
- AI and machine learning applications are impacted by irregularity:
    - Graph neural networks (GNNs).
    - Large language models (LLMs) with sparse attention or irregular data access.

The workshop welcomes regular paper submissions, papers describing work-in-progress or incomplete but solid work, and innovative ideas related to the workshop theme. The workshop solicits both 8-page regular papers and 4-page position papers. The authors of exciting but not mature enough regular papers may be offered the option of a short 4-page paper and an associated short presentation.

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IMPORTANT DATES
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Abstract Submission: July 25, 2025 (AoE)
Position or Regular Paper Submission: August 1, 2025 (AoE)
Notification: September 5, 2025
Camera-ready: September 29, 2025
Workshop: November 16, 2025

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SUBMISSIONS
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Submission site:  https://urldefense.us/v3/__https://submissions.supercomputing.org/?page=Submit&id=SCWorkshopIA3Abstract&site=sc25__;!!G_uCfscf7eWS!a_58iIeDFteE1Lx1Nu0mOtj8yVuURRAE8PCtM58QYQn_EhqTjND4ns1yHoplZ3EWNgcIr1M2JPCixeqjNQJNSTFv5hUlODnl5w$ 

Submitted manuscripts may not exceed eight (8) pages in length for regular papers and four (4) pages for position papers (excluding references).
Authors of regular papers will be able to provide up to one (1) additional pages for the Artifact Description (AD) appendix and, after paper acceptance, up to two (2) additional pages for the Artifact Evaluation (AE) appendix.

The templates are available at: https://urldefense.us/v3/__https://www.acm.org/publications/proceedings-template__;!!G_uCfscf7eWS!a_58iIeDFteE1Lx1Nu0mOtj8yVuURRAE8PCtM58QYQn_EhqTjND4ns1yHoplZ3EWNgcIr1M2JPCixeqjNQJNSTFv5hVKlmLd6A$ 


The proceedings of the workshop will be published in the ACM Digital Libray.

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GENERAL CO-CHAIRS
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Antonino Tumeo, PNNL, antonino.tumeo at pnnl.gov
Mahantesh Halappanavar, PNNL, mahantesh.halappanavar at pnnl.gov

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TECHINICAL PROGRAM CO-CHAIRS
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Giulia Guidi, Cornel University, gg434 at cornell.edu
Flavio Vella, University of Trento, flavio.vella at unitn.it

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SPECIAL TOPIC CO-CHAIRS
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Sanjukta Bhowmick, University of North Texas, sanjukta.bhowmick at unt.edu
Marco Minutoli, PNNL, marco.minutoli at pnnl.gov

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ARTIFACT EVALUATION CHAIR
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Biagio Cosenza, University of Salerno, bcosenza at unisa.it

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INCLUSIVITY CO-CHAIRS
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Vito Giovanni Castellana, PNNL, vitogiovanni.castellana at pnnl.gov
Nicolas Bohm Agostini, PNNL, nicolas.agostini at pnnl.gov

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