The authors have an opportunity to respond to the reviews, so please remember the author rebuttal period. The response will be taken into consideration by the PC members and they will have an opporutnity to update the scores.

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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