May 18, 2018
May 25, 2018
IEEE International Symposium on Workload Characterization (IISWC)
Sep 30 – Oct 2, 2018
Abstracts Submission: May 18,2018
Paper Submission: May 25, 2018
Acceptance Notification: July 27, 2018
The 2018 IEEE International Symposium on Workload Characterization will be held in Raleigh, North Carolina, between September 30th and October 2nd, 2018. We solicit papers in all areas related to understanding and characterization of computing system workloads. Topics of interest include (but are not limited to):
– Characterization of applications in domains including memory, storage and file systems, cyber physical systems, pervasive computation and Internet of Things (IoTs), search engines, e-commerce, web services, databases, file/application servers, embedded, mobile, multimedia, real time, 3D-graphics, gaming, Blockchain, life sciences, bioinformatics, scientific computing, finance, forecasting, machine learning, analytics, data mining, security, reliability, biometrics, cloud and edge computing, user behavior and system user interaction.
– Emerging workloads and architectures such as Transactional memory workloads, workloads for multi/many core systems, Stream based computing workloads, web/internet workloads, cyber-physical workloads, Near data processing architectures, Quantum computations and communication, Near-threshold computation and Non-volatile memory.
– Implications of workloads in design issues such as Power management, reliability, security, performance, Processors, memory hierarchy, I/O, and networks, Design of accelerators, FPGAs, GPUs, CGRAs, etc and Novel architectures (non Von Neumann).
– Benchmark creation and evaluation, including Multithreaded benchmarks, benchmark cloning, Profiling, trace collection, synthetic traces, Validation of benchmarks.
– 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.
– 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.
Drew Hilton, Duke University
Brian Rogers, IBM Research
Carole-Jean Wu, Arizona State University