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The CSR program seeks proposals focused on compelling research problems with potential to advance the state-of-the-art on how to improve the design, use, behavior and stability of computer and software systems within and across the following systems areas: distributed and Internet scale computing, massively parallel and data intensive computing, real-time and embedded systems, and pervasive and ubiquitous computing.

Broad categories of research interest within CSR include, but are not limited to:

  • Scalable and robust systems and software architectures, models and programming abstractions to support changing trends and emerging technologies, such as sizes or speeds of processors, advances in access memory and storage, and massively scalable computing capabilities provided as a service, and virtualization at scale,

  • New directions and innovative approaches for the design, implementation, access and management of modern storage and file systems, including access-anywhere and personal storage, energy-efficient and self-managing storage, , massive data and metadata access and management, caching, replication and data consistency,

  • Fundamental and system-level research on power management and energy-aware architectures and design methodologies, including better understanding of the tradeoffs between performance and power consumption, and new scalable, context- and energy-aware approaches for efficient systems services, improved system manageability, operational sustainability, usability and performance,

  • Frameworks, methodologies and tools for quantitative and qualitative evaluation, monitoring and prediction of complex computer systems and application behavior and performance,

  • Novel parallel programming models and abstractions, compiler and dynamic run-time support for parallel programming and coordination languages, and application and system level methodologies and tools that exploit the characteristics of the hardware and execution environment to achieve high-level parallelism and efficient resource management,

  • Innovative energy-efficient, fault-tolerant run-time execution environments, service architectures and coordination frameworks to enable automatic parallelization, synchronization and concurrency control, across heterogeneous, data- and compute-intensive environments.

  • Power and energy-aware compilation and runtime optimization techniques for parallel computing, including dynamic and adaptive compilation, automatic code generation, program characterization and phase analysis techniques for optimized performance, and computation steering for reliability, scalability and improved performance,

  • Scalable scheduling algorithms for resource and data intensive parallel systems, multi-criteria scheduling frameworks and algorithms, tools and environments for workflow scheduling in parallel systems, and adaptive and dynamic load balancing algorithms and tools,

  • New paradigms, methodologies, algorithms and tools to enable robust and highly reliable real-time systems, across diverse computing and software platforms, capable of operating in widely distributed and highly interactive and uncertain environments.

  • New paradigms, mechanisms and tools for real-time resource management that address and integrates multiple resource constraints and performance requirements, such as power, clock frequency and thermal gain, hardware reconfigurability, task dependence and real-time guarantees.