IISWC-2018 September 30 - October 2, 2018  Raleigh, North Carolina, USA

Abstracts Submission : May 11, 2018 (11:59:59PM EST)

Paper Submission : May 18, 2018 (11:59:59PM EST)

Acceptance Notification : July 27, 2018

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 including

• Memory, storage, and file systems
• Cyber-physical systems, pervasive computation and Internet of Things (IoT)
• 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
• 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.
• 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

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