Call for Papers 

32nd IEEE International Conference on High Performance Computing, Data, & Analytics

HiPC 2025 will be the 32nd edition of the IEEE International Conference on High Performance Computing, Data, Analytics, and Data Science. HiPC serves as a forum to present current work by researchers in the areas of high performance computing and data science. The meeting focuses on all aspects of high performance computing systems, and data science and analytics, and their scientific, engineering, and commercial applications.

Authors are invited to submit original unpublished research manuscripts that demonstrate current research in all areas of high performance computing, and data science and analytics, covering all traditional areas and emerging topics including machine learning and big data analytics. Each submission should be submitted under the two broad themes of High Performance Computing and Data Science.

Up to two best paper awards will be given for outstanding contributed papers.

Questions may be sent to: [email protected] 

Important dates:*

Abstract Submission: June 18, 2025 (Wednesday)

Paper Submission (double-blind): June 25, 2025  (Wednesday) 

Reviews to Authors: August 21, 2025   (Thursday) 

Rebuttal Period: August 21-26, 2025  (Thursday to Tuesday)  

Author Notification: September 12, 2025 (Friday)

Shepherded Paper Submission: September 26, 2025  (Friday) 

Final Author Notification: October 3, 2025  (Friday) 

*All deadlines are Anywhere On Earth (AOE)

 

High Performance Computing:

Topics for papers include, but are not limited to the topics given under the categories below.

Algorithms. This track invites papers that describe original research on developing new parallel and distributed computing algorithms, and related advances. Examples of topics that are of interest include (but not limited to):

  • New parallel and distributed algorithms and design techniques;
  • Advances in enhancing algorithmic properties or providing guarantees (e.g., concurrency, data locality, communication-avoiding, asynchronous, hybrid CPU-GPU algorithms, fault tolerance, resilience,);
  • Algorithmic techniques for resource allocation and optimization (e.g., scheduling, load balancing, resource management);
  • Provably efficient parallel and distributed algorithms for advanced scientific computing and irregular applications (e.g., numerical linear algebra, graph algorithms, computational biology);
  • Classical and emerging computation models (e.g., parallel/distributed models, quantum computing, neuromorphic and other bioinspired models).

Architecture. This track invites papers that describe original research on the design and evaluation of high performance computing architectures, and related advances. Examples of topics of interest include (but not limited to): 

  • High performance processing architectures (e.g., reconfigurable, system-on-chip, many cores, vector processors);
  • Networks for high performance computing platforms (e.g., interconnect topologies, network-on-chip);
  • Memory, cache and storage architectures (e.g., 3D, photonic, Processing-In-Memory, NVRAM, burst buffers, parallel I/O);
  • Approaches to improve architectural properties (e.g., energy/power efficiency, reconfigurable, resilience/fault tolerance, security/privacy);
  • Emerging computational architectures (e.g., quantum computing, neuromorphic and other bioinspired architectures). 

Applications. This track invites papers that describe original research on the design and implementation of scalable and high performance applications for execution on parallel, distributed and accelerated platforms, and related advances. Examples of topics of interest include (but not limited to):

  • Shared and distributed memory parallel applications (e.g., scientific computing, simulation and visualization applications, graph and irregular applications, data-intensive applications, science/engineering/industry applications, emerging applications in IoT and life sciences, etc.);
  • Methods, algorithms, and optimizations for scaling applications on peta- and exa-scale platforms (e.g., co-design of hardware and software, heterogeneous and hybrid programming);
  • Hardware acceleration of parallel applications (e.g., GPUs, FPGA, vector processors, manycore);
  • Application benchmarks and workloads for parallel and distributed platforms.

Systems Software. This track invites papers that describe original research on the design, implementation, and evaluation of systems software for high performance computing platforms, and related advances. Examples of topics of interest include (but not limited to):

  • Scalable systems and software architectures for high-performance computing (e.g., middleware, operating systems, I/O services); 
  • Techniques to enhance parallel performance (e.g., compiler/runtime optimization, learning from application traces, profiling); 
  • Techniques to enhance parallel application development and productivity (e.g., Domain-Specific Languages, programming environments, performance/correctness checking and debugging); 
  • Techniques to deal with uncertainties, hardware/software resilience, and fault tolerance; 
  • Software for cloud, data center, and exascale platforms (e.g., middleware tools, schedulers, resource allocation, data migration, load balancing); 
  • Software and programming paradigms for heterogeneous platforms (e.g., libraries for CPU/GPU, multi-GPU clusters, and other accelerator platforms).

Data Science and AI:

Topics for papers include, but are not limited to the topics given under the categories below.

Scalable Data Science: This track invites papers that describe original research on developing scalable algorithms, systems, and software for data analysis at scale, and related advances. Examples of topics of interest include (but not limited to):

  • New scalable algorithms, systems, and software for fundamental data analysis tasks. 
  • Scalable algorithms, systems, and software that are designed to address the characteristics of different data sources and settings (e.g., graphs, social networks, sequences, data streams); 
  • Scalable algorithms and techniques to reduce the complexity of large-scale data (e.g., streaming, sublinear data structures, summarization, compressive analytics); address requirements in different data-driven application domains (e.g., life sciences, business, agriculture), ensure the transparency and fairness of the analysis; 
  • Design of scalable system software to support various data-centric applications (e.g., recommendation systems, web search, crowdsourcing applications, streaming applications) 
  • Architectures and systems software to support various operations in large data frameworks (e.g., storage, retrieval, automated workflows, data organization, visualization, visual analytics, human-in-the-loop); 
  • Systems software for distributed data frameworks (e.g., distributed file system, data deduplication, virtualization, cloud services, resource optimization, scheduling); 
  • Case studies, experimental studies, and benchmarks for scalable algorithms and analytics;
  • Standards and protocols for enhancing various aspects of data analytics (e.g., open data standards, privacy-preserving, and secure schemes). 

AI/ML for Systems and Systems for AI/ML. This track invites papers that describe original research on using AI/ML for systems design or  systems design for AI/ML application and related advances. Examples of topics of interest include (but not limited to):

  • AI/ML methods for system design and optimization (e.g. efficient design space exploration, job scheduling, energy efficiency) in computing systems;
  • AI/ML methods that benefit HPC applications or HPC system management;
  • Scaling and accelerating machine learning, deep learning, natural language processing and computer vision applications;
  • Efficient model training, inference, and serving (includes specialized hardware design and SW techniques);
  • Fairness, interpretability, and explainability for AI/ML applications;
  • End-to-end machine learning pipeline optimization (data prep and data cleaning);
  • Compound AI systems and AI agent systems;
  • Machine learning benchmarks and datasets.

Abstracts of no more than 300 words must be submitted by the abstract submission deadline. The title and abstract submitted by this deadline should have sufficient detail and not just be a placeholder. Authors are strongly advised to submit their papers with the final list of authors, as changes may not be feasible at later stages.

Submitted manuscripts should be structured as technical papers and the full papers may not exceed ten (10) single-spaced double-column pages using 10-point size font on 8.5×11 inch pages (IEEE conference style), including figures, tables, and references. All submitted manuscripts will be reviewed by the Program Committee under a double-blind review process, so the submitted paper should NOT list any authors or their affiliations.  The author list at the time of submission is considered final – no co-authors can be added or removed after the submission deadline or upon acceptance (no exceptions). The author affiliation and order can be changed with notice to the PC chair before the camera-ready deadline if the paper is accepted.

The IEEE conference style templates for MS Word and LaTeX provided by IEEE eXpress Conference Publishing are available for download. See the latest versions here. Electronic submissions must be in the form of a readable PDF file.

Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date, exceeding the length limit, or not appropriately structured may also not be considered. Papers must be submitted under one of the technical tracks listed. The topics listed under each track are representative, but not exhaustive. A published proceeding will be available at the conference. At the time of publishing, authors of accepted papers may buy up to two pages in addition to the page limits specified above for their manuscript. Authors may contact the Program Chair at the email address above for further information or clarification.

No Show Policy: At least one author of each paper must be registered for the conference in order for the paper to be published in the proceedings. Accepted full papers will be presented in technical sessions and selected papers will be presented in a separate poster session.  Presentation of an accepted paper is a requirement for publication in the proceedings. Any paper not meeting requirements will not be included in the conference proceedings under IEEE Xplore.

Submit your paper: https://ssl.linklings.net/conferences/HiPC/

Questions may be sent to [email protected] 

A high-quality submission should articulate its contributions in multiple aspects:

Motivation. Clearly state the objective of the paper and provide strong support to motivate the specific problem the submission is solving.

Limitations of state-of-art approaches. Unambiguously discuss and distinguish from the most relevant and most recent prior works.

Key insights and contributions. Clearly articulate the major insights that enable the described approach or make it effective. Clearly specify the novelty of these insights and how they advance state-of-the-art. Provide a list of key contributions including flagship theoretical or experimental results and improvement over the prior art, as applicable.

Methodology. Clearly specify the key theoretical or experimental methodological details, as applicable. Support the chosen methodological choices (e.g., cite that most relevant and most recent prior works have evaluated their ideas using similar methodology). If new methodology is adopted or theoretical assumptions different from prior art are made, a detailed justification should be provided.

Limitations of the proposed approach. As applicable, articulate all the major limitations of the proposed approach and identify conclusions that are sensitive to specific assumptions made in the paper.

The Program Committee will be encouraged to assess the submissions in the above aspects. Therefore, the authors should consider making these aspects clear and easily identifiable, as much as possible, when articulating their contributions. We hope this will help improve both the review quality (author experience) and reviewing experience.

Use of AI-assisted text: HiPC will allow the use of tools like ChatGPT, Grammarly, or other AI assistants to help improve the submission text. We recommend that you use these services merely for language rectification. The authors should verify whether the results are accurate before submission. 

As required by IEEE, the use of any AI-generated text must be disclosed in the acknowledgments section. The sections of the paper that use AI-generated text shall have a citation to the AI system used to generate the text. 

If you use AI tools, you should include an acknowledgment section to disclose the AI assistance with appropriate references to the sections in the paper, but this acknowledgment section should still abide by the double-blind submission guideline (i.e., any funding or author-related information should not be included). 

ArXiv Submission Policy: Having an arXiv paper does not prohibit authors from submitting a paper to HiPC 2025. arXiv papers are not peer-reviewed and not considered as formal publications, hence do not count as prior work. Authors are not expected to compare against arXiv papers that have not formally appeared in previous conference or journal proceedings. If a submitted paper is already on arXiv, please continue to follow the double-blind submission guidelines. Authors are encouraged to use preventive measures to reduce the chances of accidental breach of anonymity (e.g., use a different title in the submission, not upload/revise the arXiv version during the review period after the submission deadline).

Inclusive Description of Research Contributions: Please consider making your research contribution description inclusive in nature. For example, consider using gender-neutral pronouns, consider using examples that are ethnicity/culture-rich, consider engaging users from diverse backgrounds if your research involves a survey, etc. Best efforts should be made to make the paper accessible to visually impaired or color-blind readers.

All submitted manuscripts will be reviewed by the Program Committee under a double-blind review process. Submissions will be judged on correctness, originality, technical strength, significance, potential impact, quality of presentation, and interest and relevance to the conference scope. Submitted manuscripts should NOT have appeared in or be under consideration for another conference, workshop, or journal.

The initial decision for the submission may be Accept, Reject or Shepherd. Papers that are recommended for shepherding will have to address the comments from the reviewers, and submit a revised article along with a summary of changes. The revised manuscript will be reviewed by the shepherd and the final decision will be communicated.

HiPC 2025 is the 32nd edition of the IEEE International Conference on High Performance Computing, Data, and Analytics. It will be an in-person event in Hyderabad, India, from December 17 to December 20, 2025. 

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Diversity and Inclusion

HiPC is committed to the promotion of diversity and inclusion in all professional activities. We encourage the diversity and welcome everyone regardless of age, gender identity, race, ethnicity, socioeconomic background, country of origin, religion, sexual orientation, physical ability, political views, education, and work experience. 

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