Call for Abstracts

To promote advancements in modeling and simulation (ModSim) research, we are soliciting input in the form of abstracts. If accepted, author(s) will be invited to host a short presentation and/or poster at the annual gathering of our community, the Workshop on Modeling & Simulation of Systems and Applications (ModSim 2025).

This year’s workshop theme is Modeling and Simulation for Extreme Computing in the AI Era. The emphasis will be on emerging and revolutionary new technologies and architectures for computing of AI workloads. ModSim for processors and system architectures design and optimization that scale and perform at the pace of AI, including novel AI-driven methodologies for ModSim, as well as tools, best practices, and new directions will be showcased and discussed throughout the workshop. As always, projects and initiatives that address computing challenges in the AI Era and aim to advance the state-of-the-art in modeling performance, power, and reliability of extreme computing will be represented. Specific areas of interest are further defined in the Topic Areas subsection of this call.

Submissions related to this year’s workshop theme, imparting lessons learned from specific projects, methods, tools, and use cases, are highly encouraged.

Topic Areas

Abstract contributions should relate to the workshop theme Modeling and Simulation for Extreme Computing in the AI Era. Within the overall theme, subcategories of interest include:

• Artificial Intelligence and Machine Learning Workloads and Systems. AI, in general, and Machine Learning (ML), in particular, are important drivers to all forms of computing, including large-scale data- and numerically intensive high-performance computing (HPC). Consequently, systems designed for AI/ML workloads are critically important. Abstracts in this category should offer novel approaches for AI and ML workloads, ModSim for AI/ML architectures, and other approaches (e.g., intelligent computational steering driven by dynamic and offline learning).
  
  
• Methodologies and Tools. AI and ML are not only revolutionizing applications, but these techniques also have the potential to revolutionize the way that HPC systems are designed. This abstract category solicits submissions that adopt AI/ML techniques in system design, such as predictive models of performance, power, or cost; approaches that intelligently explore and recommend designs; and techniques that optimize individual subsystems, across system layers, or the whole system with AI/ML. Abstracts should highlight how to advance the state of the art, as well as expectations for impacting future directions in this area.
  
  
• Recent Advances in ModSim Implementation. The rapidly increasing complexity of systems and application workloads – along with the blending of compute, memory devices, storage, and interconnect then further combined with application software – translates into unprecedented challenges within the ModSim field. Submissions in this category, not necessarily related to AI/ML, are expected to highlight recent developments that can help overcome these significant challenges. Possible topics include, but are not limited to, novel ModSim methodologies, emerging areas of R&D, new projects or advances in existing projects, and new applications of ModSim tools to real-life problems.
  

Abstract Submission Guidelines

There is no set word limit for abstract submissions. However, please limit the submission to one page (letter or A4 size) with no smaller than 11-point font type. The abstract should provide an overview that adequately summarizes the topic(s) presented and any proposed impact on ModSim research or techniques, especially any relevant to the workshop theme.

The following details a proposed abstract layout and points to consider, all within the workshop’s theme:

• Abstract Title
• Primary research area:
  • Artificial Intelligence and Machine Learning Workloads and Systems
  • Methodologies and Tools
  • Recent Advances in ModSim Implementation

The abstract should include specific aspects of the work and answer questions, such as:

• What is being modeled (e.g., performance, reliability, power, other)?
• What is the target application?
• What modeling techniques are being used?
• What is novel about the approach versus current state of the art?
• Are preliminary results or any notable lessons learned available?

Dr. Sudhakar Yalamanchili Award

The Dr. Sudhakar Yalamanchili Award will be presented to the researcher who demonstrates an “outstanding contribution to ModSim” as derived from a Contributed Abstract and Presentation/Poster Session hosted during the ModSim 2025 Workshop. ModSim 2025 Workshop Organizing Committee members will evaluate the abstracts/presentations/posters and make the final selection. To qualify, a person must be a graduate student or postdoctoral researcher within six years of her/his/their highest awarded degree at the time of the ModSim conference. All submissions that satisfy these criteria are eligible for the award. Learn more