As the push for parallelism continues to increase the number of cores on a chip, system design has become incredibly complex; optimizing for performance and power efficiency is now nearly impossible for the application programmer. To assist the programmer, a variety of techniques for optimizing performance and power at runtime have been developed, but many employ the use of speculative threads or performance counters. These approaches result in stolen cycles, or the use of an extra core, and such expensive penalties can greatly reduce the potential gains.
Within this context imagine a revolutionary computing system that can observe its own execution and optimize its behavior around a user's or application's needs. Imagine a programming capability by which users can specify their desired goals rather than how to perform a task, along with constraints in terms of an energy budget, a time constraint, or simply a preference for an approximate answer over an exact answer.
Imagine further a computing system that performs better according to a user's preferred goal the longer it runs an application. Such an architecture will enable, for example, a handheld radio or a cell phone that can run cooler the longer the connection time. Or, a system that can perform reliably and continuously in a range of environments by tolerating hard and transient failures through self healing.
Self-aware computer systems are the key technology to succeed in doing this. They will be able to configure, heal, optimize, improve interaction and protect themselves without the need for human intervention, exploiting abilities that allow them to automatically find the best way to accomplish a given goal with the resources at hand. Within this context, imagine a revolutionary computing system that can observe its own execution and optimize its behavior around the external environment, user's and application's needs. The Self-Aware computing research leverages the new balance of resources to improve performance, utilization, reliability and programmability.
Within this context, the proposed workshop is intended to present innovative works describing:
- Self-aware Operating Systems
- Autonomous self-aware computer architecture
- Adaptive algorithm and distributed self-training algorithms
- Biologically inspired systems
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