ACM 5th International Workshop on System and Network Telemetry and Analytics (SNTA'22)

SNTA archive

In conjunction with HPDC 2022, June 27 - July 1, 20221, Minneapolis, Minnesota, USA

Workshop Program

Meeting Room: Ski-U-Mah, McNamara Alumni Center, University of Minnesota
2pm, June 30, 2022, GMT
7am, June 30, 2022, PDT (USA)
9am, June 30, 2022, CDT (USA)
10am, June 30, 2022, EDT (USA)
3pm, June 30, 2022 (England)
4pm, June 30, 2022 (Italy, France, Sweden, Switzerland)
10pm, June 30, 2022 (Taiwan)
11pm, June 30, 2022 (Korea)
Zoom downloads
Meeting ID: 973 1552 7020
* Zoom session is password protected, and only available during the session.
* All SNTA/HPDC registered participants will receive the zoom access information.
* This zoom session is only for SNTA workshop 2022.
* HPDC may have a separate zoom session info.

Thanks for your participation!
All video presentations will be available on YouTube SNTA Workshop channel, if available.

Registration: Please register using HPDC registration.
Zoom connection details will be sent to the list of registered attendees.

The Q&A session for papers is done through Slack ( channel (#snta22).
This channel will remain open, and you can join the SNTA slack channel through this invitation link:

Program order subject to change.
SNTA 2022 Co-Chairs: Massimo Cafaro, Jerry Chou, Jinon Kim, Alex Sim

Session 1
Chair: Jinoh Kim
9am CDT

    Jinoh Kim

Keynote Presentation
    Dr. Suren Byna, Lawrence Berkeley National Laboratory
    Title: Understanding Parallel I/O Performance and Tuning
    Abstract: Parallel I/O is critical for large-scale applications to store and access data from parallel file systems on high-performance computing (HPC) systems. The parallel I/O stack includes several layers of software libraries – high-level I/O libraries such as HDF5, middleware (MPI-IO), and low-level I/O libraries (POSIX, STD-IO). Each of these layers have complex interdependencies that impact the I/O performance significantly. In this brief abstract, we describe parallel I/O basics, I/O monitoring using various profiling tools, analysis of logs collected on production class supercomputers to identify performance bottlenecks and application of performance tuning options. We will also cover numerous application use cases and performance improvements.

Bio: Dr. Suren Byna is a Senior Scientist in the Scientific Data Management (SDM) Group at Lawrence Berkeley National Laboratory. His research interests are in scalable scientific data management. More specifically, he works on optimizing parallel I/O performance, developing systems for managing scientific data, and supporting scientists to find data of their interest efficiently. He is an author or co-author of more than 150 publications in the high-performance computing area. He is the PI of the ECP funded ExaIO project, and ASCR funded object-centric data management systems (Proactive Data Containers - PDC) and experimental and observational data management (EOD-HDF5) projects.     

Session 2

Chair: Massimo Cafaro
10:20am CDT


Redfish-Nagios: A Scalable Out-of-Band Data Center Monitoring Framework Based on Redfish Telemetry Model
    Ghazanfar Ali (Texas Tech University), Jon Hass (Dell EMC, Inc.), Alan Sill, Elham Hojati, Tommy Dang, Yong Chen (Texas Tech University)

Predicting Slow Network Transfers in Scientific Computing
    Robin Shao (Univeresity of California, Berkeley), Jinoh Kim (Texas A&M University, Commerce), Alex Sim, Kesheng Wu (Lawrence Berkeley National Laboratory)

Access Trends of In-network Cache for Scientific Data
    Ruize Han (University of California, Berkeley), Alex Sim, Kesheng Wu (Lawrence Berkeley National Laboratory), Inder Monga, Chin Guok (Energy Sciences Network), Frank Wurthwein, Diego Davila (University of California, San Diego), Justas Balcas, Harvey Newman (California Institute of Technology)

Janus: Lightweight Container Orchestration for High-performance Data Sharing
    Ezra Kissel (Energy Sciences Network)

Session 3

Chair: Eric Chan-Tin
1:30pm CDT


Predicting Phishing Victimization: Roles of Protective and Vulnerable Strategies and Decision-Making Styles
    Eric Chan-Tin, Loretta Stalans, Spencer Johnston, Daisy Reyes (Loyola University Chicago), Shelia Kennison (Oklahoma State University)

Studying Scientific Data Lifecycle in On-demand Distributed Storage Caches
    Julian Bellavita (University of California, Berkeley), Alex Sim, Kesheng Wu (Lawrence Berkeley National Laboratory), Inder Monga, Chin Guok (Energy Sciences Network), Frank Wurthwein, Diego Davila (University of California, San Diego)

The Variable-Weight MADM Algorithm for Wireless Network
    Ning Li, Xin Yuan (Harbin Institute of Technology), Joser Fernan Martinez (Universidad Politécnica de Madrid), Zhaoxin Zhang (Harbin Institute of Technology)

Session 4: Social

3:30pm - 4:30pm CDT

Zoom info:
Meeting ID: 973 1552 7020
Passcode: only available during the session