The 3rd Industry/University Joint International Workshop on Data-Center Automation, Analytics, and Control (DAAC)
The 3rd Industry/University Joint International Workshop on Data-Center Automation, Analytics, and Control (DAAC) to be hosted at the 2019 ACM/IEEE Supercomputing Conference (SC19) is an outcome of intensive discussions from academia, industry, and national laboratory researchers that led to successful previous instances hosted at SC’18 and UCC’17. Looking at the last year’s attendance at SC’18, DAAC has attracted up to ~80 attendees and had 50.6 attendees on average. DAAC’18 featured an industry panel, 3 invited talks from both academia and industry, and 10 paper talks from academia, national labs, and industry, selected through a rigorous review process (at least three reviews for each paper). DAAC’17 featured three invited speakers from industry and a panel of five experts and different stakeholders in addition to presentations from peer-reviewed papers.
This new instance of the DAAC workshop at SC remains a unique workshop that promotes collaboration among academia, industry, and national labs and remains jointly organized by academic and industry researchers. The objective is to promote and stimulate community’s interactions to address some of most critical challenges in automation, analytics, and control specifically aimed for the needs of large-scale data centers in high-performance/high-end computing. DAAC’19 will provide a valuable addition to main conference programs. Taking advantage of the opportune match to the SC19 audience, DAAC’19 expects to attract a larger number of attendees from academia, industry, and government labs who are interested in data center automated management, operation, and maintenance.
The DAAC-2019 workshop program details can be found from this link https://sc19.supercomputing.org/presentation/?id=wksp137&sess=sess133.
Introduction - The 3rd Industry/University Joint International Workshop on Data-Center Automation, Analytics, and Control (DAAC)
- Organizers: Yong Chen, Dong Dai, Tim Cockerill, Alan Sill
- Submission Deadline: September 17, 2019
- Author Notification: October 10 , 2019
- Camera-ready Submission: October 31, 2019
- Workshop Date: Friday, 22 November 2019, 9 am - 12:30 pm.
- Workshop Location: at the SuperComputing 2019 conference, Colorado Convention Center, 704-706.
This workshop will provide a forum to discuss fundamental issues on real-time operation of highly automated data centers, including methods to provision, debug, analyze and control data center equipment and to improve how machines are operated, monitored, and used. Topics to be covered will include how software stacks are deployed and provisioned, how data is processed and transferred in real time from the data center to the cloud as well as challenges in design and implementation of novel automated data center architectures and systems. New methods, techniques, hardware, software, and standards for data center automation and control will be discussed and in scope.
- Design and implementation of hardware for large-scale data center operation
- Artificial intelligence methods to detect and respond to shifting workloads
- Integration of cloud software stack design and data center operations
- Real-time monitoring architectures and systems
- Data analytics infrastructures for data centers
- Data movement within and between large-scale data center implementations
- Debugging operational issues in multi-level data centers
- Data collection, analytics, security and management for data centers
- Techniques for on-demand virtual machine image or container provisioning
- Mining sensor data collected from large-scale sensing deployments
- Big data analytics in large data center sensor networks
- Sensor systems for remote and real-time monitoring of data center equipment
- Scheduling for distributed systems within and among data centers
- Optimizing energy use in multi-tenant data center deployments
- Emergency response methods for automated protection of equipment
- Control software frameworks for handling large numbers of machines
- Custom design of software and hardware to optimize operation in data centers
Manuscript submissions must be received by the announced submission deadline. All manuscripts will be reviewed by the Program Committee and evaluated on originality, relevance of the problem to the conference theme, technical strength, rigour in analysis, quality of results, and organization and clarity of presentation of the paper. All accepted papers will be published by IEEE TCHPC.
Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Further details on the publication instructions and registration information will be published on the DAAC website.
- Authors are requested to submit papers electronically.
- Submissions are limited to 6 pages using 10 pt fonts in the IEEE format (https://www.ieee.org/conferences/publishing/templates.html).
- The 6-page limit includes figures, tables, references and appendices.
- Short talks covering recently breaking topics may be submitted for presentation only.
- Journal publication will not be guaranteed for these talks if accepted, but slides will be accepted to be made available online.
- Submit an abstract and up to one-page description using the templates linked above and the submission link below.
Panel Participation and Topics:
- Submit a proposal for a panel topic, or volunteer to participate on a panel, using the submission link below.
- Prepare an abstract and up to one-page description using the templates linked above and the submission link below, or contact the organizers for additional information.
- All topics related to the main theme of the workshop are in scope.
Submissions should be made on the submissions.supercomputing.org web site.
To submit your paper, please use the following link, or click on the DAAC link on the "submission Forms" tab there, after logging in to that site:
- Alan Sill (Texas Tech University)
- Yong Chen (Texas Tech University)
- Jon Hass (Dell)
- Jeff Hilland (HPE)
- Dong Dai (University of North Carolina at Charlotte)
- Tim Cockerill (Texas Advanced Computing Center)
- Elham Hojati (Texas Tech University)
- Misha Ahmadian (Texas Tech University)
- Mai Zheng (Iowa State University)