SciData staff at SC26
7Events
5Days
Nov 15, 2026 – Nov 20, 2026Program window
Sunday, November 15
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Workshop
Cross-Fabric Policy Reasoning for Hybrid InfiniBand/Ethernet HPC Systems
Full description
SC26 has not supplied a description for this event.
- Presenters
- Anna GiannakouLawrence Berkeley National Laboratory
Monday, November 16
-
Workshop
RSE-HPC Panel: Meeting RSE Challenges
Full description
Hannah Cohoon, Lawrence Berkeley National Laboratory Thomas Flynn, Durham University Helen Kershaw, National Center for Atmospheric Research (NCAR)- Participants listed in source description
- Hannah CohoonLawrence Berkeley National Laboratory
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Workshop
Stress-Testing Exascale Scientific Data Output - ADIOS2 Configuration Strategies for WarpX under Extreme Load Imbalance
Full description
Spatially imbalanced, temporally irregular simulation output challenges I/O configurations tuned for balanced workloads. This work evaluates ADIOS2 BP5 configurations through openPMD-api using WarpX on Frontier at ORNL and Perlmutter at NERSC, contrasting balanced 3D Cartesian output with boosted-frame back-transformed diagnostics (BTD). BTD combines rank-level output skew with snapshot contributions spanning multiple simulation steps. Balanced output reaches 3.64~TB/s without compression on 2,048 Frontier nodes and over 1~TB/s on 512 Perlmutter nodes; lossless Blosc2 compression achieves approximately 7~TB/s application-level effective throughput on Frontier. In the tested BTD configurations, SPAN combined with asynchronous writing provides the highest throughput on Frontier, FlattenSteps supports assembly of complete lab-frame snapshots for checkpointing without reader modification and with negligible write-time overhead and no penalty on read performance, and DataSizeBased aggregation improves throughput when subfile counts are constrained. These results identify complementary mechanisms for handling irregular output and provide configuration guidance for these workloads and systems.- Author/Presenters
- Junmin GuLawrence Berkeley National Laboratory
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Demo
AIDRIN: The Data Readiness Infrastructure
Full description
AIDRIN is open-source infrastructure for quantitatively assessing and improving the readiness of scientific datasets for intelligent learning systems. AIDRIN helps users to prepare, transform, and remediate to ready the datasets. AIDRIN offers multiple interfaces, including a command-line interface (CLI), web-based service, and MCP server with agentic interface.- Speakers
- Jean Luca BezLBNL
- Suren BynaLBNL
Tuesday, November 17
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Birds of a Feather
Data Readiness for AI in HPC: Building a Community Around Dimensions, Metrics, and Tools
Full description
AI now drives discovery across HPC science, yet models are only as trustworthy as the data they use. Many teams still lack a shared way to judge whether their data is ready for AI. This BoF brings together the HPC and scientific communities to define data readiness for AI using seven practical dimensions: quality, understandability, fair and unbiased representation, structure and organization, feature importance, governance covering ethics, security and privacy, and AI-specific needs such as labels and distributions. Through short talks and open discussion, we will compare practices, identify gaps, and begin building shared metrics, tools, and benchmarks.- Session Leader
- Suren BynaOhio State University; Lawrence Berkeley National Laboratory (LBNL)
- Additional Session Leaders
- Jean Luca BezLawrence Berkeley National Laboratory (LBNL)
- Shreyas CholiaLawrence Berkeley National Laboratory (LBNL)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
- W — Workshop Reg Pass
- TUT — Tutorial Reg Pass
- XO/EX — Exhibits Reg Pass
Wednesday, November 18
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Birds of a Feather
IO500: The High-Performance Storage Community
Full description
The IO500 is the de facto benchmark standard for HPC storage. Official IO500 lists have been released at ISC and SC events since SC17 and now have over 300 entries. The purpose is to foster the high-performance storage community and ensure forward progress towards the common goals of creating, sharing, and benefiting from a large corpus of shared storage data. IO500 also serves as the largest repository of detailed HPC storage information for researchers and system designers to analyze and evaluate over time. A key BoF highlight is the presentation of the latest IO500 Production and Research lists.- Additional Session Leaders
- Jean Luca BezLawrence Berkeley National Laboratory (LBNL)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
- W — Workshop Reg Pass
- TUT — Tutorial Reg Pass
- XO/EX — Exhibits Reg Pass
Friday, November 20
-
Workshop
On preprocessing heterogeneous HPC telemetry for use in foundation models and digital twins
Full description
HPC facilities publish telemetry supporting foundation-model training and digital-twin replay but lack common fields, units, and privacy conventions. We extend REDI and AIDRIN to HPC telemetry via a new domain processor and agentic telemetry skill, and apply SetGo, forming an end-to-end pipeline that transforms heterogeneous telemetry into AI-ready and digital-twin-ready datasets. For digital twins, we demonstrate cross-facility replay fidelity: naively replaying Marconi100 telemetry through a Frontier twin violates its physical power envelope on 10.23% of samples; renormalization reduces this to 0.0042%. The pipeline supports representative replay and targeted emulation. For foundation models, we find static scheduler metadata alone gives no signal for predicting job-level details; however, ExaFM predicts job runtime with R2 = 0.960 when conditioned on a pre-anonymization identity embedding; without it, transferring that head to Marconi100, unseen during pretraining, reaches R2 = 0.716. We close with actionable recommendations for publishing AI- and digital-twin-ready telemetry toward future pretraining corpora.- Author/Presenters
- Jean Luca BezLawrence Berkeley National Laboratory
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Source: SC26 Conference Program. Program details may change.
Last edited: November 9, 2026
