[Ieee_vis] CFP for ISAV: In Situ AI, Analysis and Visualization at #SC25

[Matthew Larsen]

https://isav-workshop.github.io/2025/

*Participation/Call for Papers:*
In its 11th year ISAV is expanding in scope and technical focus, and now
invites full paper submissions up to 10 pages (including references) and
works on in situ AI/ML training or inference. ISAV also continues to invite
short papers (5 page + 1 page references) and lightning talk abstracts (1
page).

Full papers should present research results, identity opportunities or
challenges, or present case studies/best practices for in situ methods.
Short papers may also document late breaking ideas & early progress on
novel concepts. Lightning talks are encouraged to present preliminary works
or ideas to foster discussion with the community. Full and short papers
will appear in the workshop proceedings and authors will be invited to give
an oral presentation at the workshop; lightning talks will be invited to
give brief oral presentations at the workshop.

Submissions of all types may identify opportunities, challenges and best
practices for in situ AI/ML, in situ analysis and in situ visualization.
They may propose new methods and techniques, provide positions, or
experience reports on in situ analysis, learning and visualization. Areas
of interest for ISAV include, but are not limited to:

Methods, Algorithms and Synthesis between HPC & ML: In situ analysis
(feature detection, data reduction/compression, data summarization, ML
training) and scientific visualization using data-driven,
surrogate-assisted, statistical, temporal, geometric, or time-varying
methods.
Applications and Workflows: Applications (simulations, data processing,
scientific user facilities) and integrations into digital twins. Workflows
for supporting complex in situ processing pipelines (incl. enabling
accelerated post-processing and elasticity), their resilience (error
detection, data congestion, fault recovery) and reproducibility.
Scalability Requirements: Scalability, resource utilization, data flow, and
simplified access to extreme heterogeneous resources. Real-time coupling of
data (modeled or measured), surrogates and algorithms.
Case Studies, Data Sources and Best Practices & Usability: Examples/case
studies of solving a specific science challenge with in situ
methods/infrastructure. In situ methods/systems applied to data from
simulations, and/or observations/experiments. Deployments & software
engineering.
Software Evolution & Standardization: In situ libraries from research
prototypes to production quality. Challenges, opportunities, gaps in
existing capabilities. API designs and development of community standards.
Enabling Hardware & Emerging Architectures: Hardware & emerging system
architectures that provide opportunities for in situ processing. Efficient
use of hardware accelerators and heterogeneous architectures, incl. HPC,
Data Center or Edge.

*Workshop Theme:*
As HPC platforms and applications increase significantly in size,
complexity, and heterogeneity, one major challenge is the widening gap
between computation and our ability to gain insight from extreme-scale data
and make timely, data-driven decisions. A well-known, yet challenging,
approach is in situ processing – performing as much analysis as possible
while computed data is still resident in memory.

This is the 11th year of the In Situ Infrastructures for Enabling
Extreme-scale Analysis and Visualization (ISAV) workshop. We celebrate that
in situ processing has evolved from research efforts to a central component
in supercomputer, cloud and edge applications. In situ methods are in high
demand: in system-scale 3D visualization for the latest Exascale
supercomputers, in cloud products providing responsive user experiences, in
tightly coupled digital twins, and in computational sciences. Each one of
these examples has a different set of requirements in response time, data
throughput and complexity of data pipelines, and more exploration in the in
situ space is needed to address multifaceted goals: (1) to preserve
important elements of simulations, (2) to significantly reduce the data
needed to preserve these elements, (3) to offer as much flexibility as
possible for post-processing exploration, and (4) to accelerate the
gathering of insights to be fast enough to make timely decisions based on
it.

ISAV is a community of in situ developers, practitioners, researchers, and
users of in situ methods and infrastructure, connecting industry,
government laboratories, and academia across all career levels. Through
presentations and discussions of research findings, lessons learned, and
early ideas, ISAV illuminates new requirements and gaps driven by science
and engineering applications, and fosters the community members and
knowledge base around the development and application of in situ methods
with its peer-reviewed proceedings.


*Timeline/Important Dates*
*08 Aug 2025* Paper submission deadline
*05 Sep 2025* Author notification
*29 Sep 2025* Camera ready copy due (note: this deadline is FIRM)
*Nov 2025* ISAV’25 workshop at SC25
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