IISWC 2020 : Call for Paper: 2020 IEEE International Symposium on Workload Characterization (IISWC)

in Conferences   Posted on June 1, 2020 

Conference Information

Submission Deadline Friday 10 Jul 2020 Proceedings indexed by :
Conference Dates Oct 27, 2020 - Oct 29, 2020
Conference Address Online, Online
Conference & Submission Link http://www.iiswc.org/iiswc2020/index.html
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Impact Score 2.97
#Contributing Top Scientists 19
#Papers published by Top Scientists 24
Google Scholar H5-index 18
Guide2Research Overall Ranking: 264
Category Rankings
Machine Learning & Artificial Intelligence 76
Proceedings https://ieeexplore.ieee.org/xpl/conhome/1000819/all-proceedings

Conference Call for Papers

IISWC invites manuscripts that present original unpublished research in all areas related to characterization and analysis of computing system workloads, including translational research related to production-oriented commercial systems. Work focusing on emerging technologies and interdisciplinary work are especially welcome. Topics of interest include (but are not limited to): Characterization of applications in traditional and emerging domains, characterization of system software and middleware, implications of workloads in system design, benchmarking methodologies and suites, and tools for computer systems. A detailed list of the topics can be found at the end of this CFP.




Submission Deadline: July 10, 2020

Decision Notification: Aug 24, 2020

Camera-ready deadline: Sep 15, 2020


New in 2020:


This year, submissions to IISWC can be made in one of the following two categories: (1) regular papers (2) tool and benchmark papers. The primary focus of “regular papers” should be to describe new research ideas supported by experimental implementation and evaluation of the proposed research ideas. The primary focus of “tool and benchmarks papers” should be to describe the design, development, and evaluation of new open-source tools / benchmarks suites.

Authors are required to indicate the category of the paper as a part of the submitted manuscript’s title. The last line of the title should indicate the paper type by using one of the two phrases (1) Paper Type: Regular, or (2) Paper Type: Tool/Benchmark.

The paper categories primarily differ in terms of their focus (new research idea vs. new open-source benchmark-suite / tool) and length (regular papers can be up to 10 pages long excluding references; tool and benchmark papers can be up to 6 pages long excluding references). But, the submissions in both the categories will be evaluated to the same standards in terms of novelty, scientific value, demonstrated usefulness, and potential impact on the field. Submissions in the “regular papers” category are also welcome to open-source their software or hardware artifacts. But, the chosen category at the time of the submission can not be changed after the submission deadline.

Double-blind submission guidelines apply to the submissions in both the categories.

Open-source benchmarks and tools that have not been previously published (but may have been open-sourced) are eligible for submission in the “tool and benchmark papers” category. Even in cases where the benchmarks suite / tool is already being used in the community, the authors should demonstrate good faith effort to adhere to the double-blind submission guidelines. All submitted papers should have obtained the legal permission (if applicable) to open-source the benchmark-suite / tool at the time of submission.


Topics of Interest


*Characterization of applications in domains including

Life sciences, bioinformatics, scientific computing, finance, forecasting

Machine learning, data analytics, data mining

Cyber-physical systems, pervasive computation and Internet of Things (IoT)

Security and privacy-preserving computing

Quantum computing

High performance computing

Cloud and edge computing

Mobile computing

User behavior and system-user interaction

Search engines, e-commerce, web services, and databases

Embedded, multimedia, real-time, 3D-graphics, gaming

Blockchain services

*Emerging workloads and architectures, such as

Quantum computations and communication

Serverless computing

Near-threshold computing

Non-volatile memory

Near data processing architectures

Neuromorphic and brain-inspired computing

Artificial intelligence and transactional memory workloads

*Characterization of OS, Virtual Machine, middleware and library behavior, including

Virtual machines, .NET, Java VM, databases

Graphics libraries, scientific libraries

Operating system and hypervisor effects and overheads

*Implications of workloads in system design, such as

Power management, reliability, security, privacy, performance

Processors, memory hierarchy, I/O, and networks

Design of accelerators, FPGAs, GPUs, CGRAs, etc.

Large-scale computing infrastructures and facilities

*Benchmark methodologies and suites, including

Representative benchmarks for emerging workloads,

Benchmark cloning methods,

Profiling, trace collection, synthetic traces

Validation of benchmarks

*Measurement tools and techniques, including

Instrumentation methodologies for workload verification and characterization

Techniques for accurate analysis/measurement of production systems

Analytical and abstract modeling of program behavior and systems

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