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IISWC 2017 : IEEE International Symposium on Workload CharacterizationConference Series : IEEE International Symposium on Workload Characterization | |||||||||||||||
Link: http://www.iiswc.org/iiswc2017/index.html | |||||||||||||||
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Call For Papers | |||||||||||||||
IISWC-2017
October 1-3, 2017 Seattle, Washington, USA This symposium is dedicated to the understanding and characterization of workloads that run on all types of computing systems. New applications and programming paradigms continue to emerge rapidly as the diversity and performance of computers increase. On one hand, improvements in computing technology are usually based on a solid understanding and analysis of existing workloads. On the other hand, computing workloads evolve and change with advances in microarchitecture, compilers, programming languages, and networking communication technologies. Whether they are smart phones and deeply embedded systems at the low end or massively parallel systems at the high end, the design of future computing machines can be significantly improved if we understand the characteristics of the workloads that are expected to run on them. This symposium, sponsored by IEEE Computer Society and the Technical Committee on Computer Architecture, will focus on characterizing and understanding emerging applications in consumer, commercial and scientific computing. Announcements: Call for Papers coming soon. Abstract deadline: May 26th, 2017. Paper deadline: June 2nd, 2017. Notification deadline: August 1st, 2017. Conference Dates have been set. IISWC-2017 will be held October 1-3, 2017 in Seattle, Washington. Topics of Interest We solicit papers in all areas related to characterization of computing system workloads. Topics of interest include (but are not limited to): Characterization of applications in domains such as o Search engines, e-commerce, web services, databases, file/application servers o Embedded, mobile, multimedia, real-time, 3D-Graphics, gaming, telepresence o Life sciences, bioinformatics, scientific computing, finance, forecasting o Machine Learning, Analytics, Data mining o Security, reliability, biometrics o Grid and Cloud computing o User behavior and system-user interaction Characterization of OS, Virtual Machine, middleware and library behavior o Virtual machines, Websphere, .NET, Java VM, databases o Graphics libraries, scientific libraries o Operating system and hypervisor effects and overheads Implications of workloads in design issues, such as o Power management, reliability, security, performance o Processors, memory hierarchy, I/O, and networks o Design of accelerators, FPGA’s, GPU’s, etc. o Novel architectures (non-Von-Neumann) Benchmark creation and evaluation, including o Multithreaded benchmarks, benchmark cloning o Profiling, trace collection, synthetic traces o Validation of benchmarks Measurement tools and techniques, including o Instrumentation methodologies for workload verification and characterization o Techniques for accurate analysis/measurement of production systems o Analytical and abstract modeling of program behavior and systems Emerging workloads and architectures, such as o Transactional memory workloads; workloads for multi/many-core systems o Stream-based computing workloads; web2.0/internet workloads; cyber-physical workloads o Near data processing architectures |
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