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

[Matthew Larsen]

If you are short on time and interested in submitting, we accept
lightning talks and short papers.

Submissions due 08/08-2025

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