[hpc-announce] CFP: JSSPP 2020 - 23rd Workshop on Job Scheduling Strategies for Parallel Processing (in conjunction with IEEE IPDPS'20)

Dalibor Klusáček klusacek at cesnet.cz
Fri Nov 22 07:17:41 CST 2019

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 2, 2020
Paper notification: March 10, 2020
Workshop date: May 22, 2020
Website: http://jsspp.org
e-mail: jssppw at gmail.com


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, 
* 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 

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 

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: 
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.

Dalibor Klusacek, CESNET a.l.e., (chair)
Walfredo Cirne, Google, (co-chair)
Narayan Desai, Google, (co-chair)

Program Committee
Ashvin Agrawal, Microsoft
Julita Corbalan, Technical University of Catalonia
Stratos Dimopoulos, Apple
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

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