JSSPP 2020 : 23rd Workshop on Job Scheduling Strategies for Parallel Processing (in conjunction with IEEE IPDPS'20)
Conference Series : Job Scheduling Strategies for Parallel Processing
Call For Papers
Call for Papers
23rd Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP 2020)
In Conjunction with IPDPS 2020, New Orleans, Louisiana USA,
Paper submission deadline: February 24 (extended), 2020
Paper notification: March 17, 2020
Workshop date: May 22, 2020
Keynote speaker: prof. Alexandru Iosup (VU University Amsterdam)
The JSSPP workshop addresses all scheduling aspects of parallel processing, including cloud, grid, HPC & HTC as well as "mixed/hybrid" or otherwise specific systems.
Large parallel systems have been in production for 30 years, creating the need of scheduling for such systems. JSSPP focus both on traditional parallel cluster/HPC/HTC systems as well as more recent cloud-based systems.
Nowadays, parallel processing is much more dynamic and connected. Many workloads are interactive and make use of variable resources over time. Complex parallel infrastructures can now be built on the fly, using resources from different sources, provided with different prices and quality of services. Capacity planning became more proactive, where resources are acquired continuously, with the goal of staying ahead of demand. The interaction model between job and resource manager is shifting to one of negotiation, where they agree on resources, price, and quality of service. Also, "hybrid" systems are often used, where the (virtualized) infrastructure is hosting a mix of competing workloads/applications, each having its own resource manager that must be somehow co-scheduled. These are just a few examples of the open issues facing our field.
From its very beginning, JSSPP has strived to balance practice and theory in its program. This combination provides a rich environment for technical debate about scheduling approaches including both academic researchers as well as participants from industry.
Building on this tradition, JSSPP welcomes both regular papers as well as descriptions of Open Scheduling Problems (OSP) in large scale scheduling (see bellow). Lack of real-world data often substantially hampers the ability of the research community to engage with scheduling problems in a way that has real world impact. Our goal in the OSP venue is to build a bridge between the production and research worlds, in order to facilitate direct collaborations and impact.
Call for Regular Papers
JSSPP solicits papers that address any of the challenges in parallel scheduling, including:
* Design and evaluation of new scheduling approaches.
* Performance evaluation of scheduling approaches, including methodology, benchmarks, and metrics.
* Workloads, including characterization, classification, and modeling.
* Consideration of additional constraints in scheduling systems, like job priorities, price, accounting, load estimation, and quality of service guarantees.
* Impact of scheduling strategies on system utilization, application performance, user friendliness, cost efficiency, and energy efficiency.
* Scaling and composition of very large scheduling systems.
* Cloud provider issues: capacity planning, service level assurance, reliability.
* Interaction between schedulers on different levels, like processor level as well as whole single- or even multi-owner systems
* Interaction between applications/workloads, e.g., efficient batch job and container/VM co-scheduling within a single system, etc.
* Experience reports from production systems or large scale compute campaigns.
For further information concerning paper formatting instructions please visit http://jsspp.org
Call for Open Scheduling Problems (OSP)
JSSPP welcomes descriptions of open problems in large scale scheduling. We believe that clearly described real-world scheduling problems will help both the production and the scientific community to bridge the gap that often prevents adoption of newly proposed scheduling techniques in practice.
Effective scheduling approaches are predicated on three things:
* A concise understanding of scheduling goals, and how they relate to one another.
* Details of the workload (job arrival times, sizes, shareability, deadlines, etc.)
* Details of the system being managed (size, break/fix lifecycle, allocation constraints)
Submissions must include concise description of the key metrics of the system and how they are calculated, as well as anonymized data publication of the system workload and production schedule. Detailed descriptions of operational considerations (maintenance, failure patterns, fault domains) are also important. Ideally, anonymized operational logs would also be published, though we understand this might be more difficult.
We envision that these papers will provide sufficiently detailed information to be able to develop new scheduling approaches, which can be robustly compared with the schedules used in production facilities, and other approaches to solve the same problems.
Paper formatting requirements for OSP-related submissions are the same as for regular papers.
Paper Formatting & Proceedings
Papers should be no longer than 20 single-spaced pages, 10pt font, including figures and references. All submissions must follow the LNCS format, see the instructions at Springer's web site: http://www.springer.com/lncs
Files must be submitted electronically in PDF format and must be formatted for 8.5×11 inch paper. All papers in scope will be reviewed by at least three members of the program committee.
Interim proceedings containing a collection of the papers presented will be distributed at the workshop in electronic form.
It is planned to also publish a post-workshop proceedings in the Springer "Lecture Notes on Computer Science" series, as was done in previous years.
Papers are submitted through EasyChair at: https://easychair.org/conferences/?conf=jsspp2020
Dalibor Klusacek, CESNET a.l.e., (chair)
Walfredo Cirne, Google, (co-chair)
Narayan Desai, Google, (co-chair)
Ashvin Agrawal, Microsoft
Julita Corbalan, Technical University of Catalonia
Stratos Dimopoulos, Apple
Hyeonsang Eom, Seoul National University
Dror Feitelson, Hebrew University
Liana Fong, IBM T. J. Watson Research
Eitan Frachtenberg, Facebook
Alfredo Goldman, University of Sao Paulo
Allan Gottlieb, New York University
Alexandru Iosup, Vrije Universiteit Amsterdam and TU Delft, the Netherlands
Zhiling Lan, Illinois Institute of Technology
Bill Nitzberg, Altair
P-O Ostberg, Umea University
Gonzalo P. Rodrigo, Apple
Larry Rudolph, Two Sigma
Uwe Schwiegelshohn, TU Dortmund University
Yingchong Situ, Google
Leonel Sousa, Universidade de Lisboa
Ramin Yahyapour, GWDG University of Goettingen