- 11/11Combining Software and Hardware LCS for Lightweight On-chip Learning. In: Autonomic Systems, 1, Volume 1, Organic Computing - A Paradigm Shift for Complex Systems, Part 3. Springer Verlag, 2012, Pages 253-265 more… BibTeX
- 10/11Autonomic System on Chip Platform. In: Autonomic Systems, 1, Volume 1, Organic Computing - A Paradigm Shift for Complex Systems, Part 4. Springer Verlag, 2012, Pages 413-425 more… BibTeX
- 9/11Applying ASoC to Multi-core Applications for Workload Management. In: Autonomic Systems, 1, Volume 1, Organic Computing - A Paradigm Shift for Complex Systems, Part 5. Springer Verlag, 2012, Pages 461-472 more… BibTeX
- 8/11Applying Autonomic Principles for Workload Management in Multi-Core Systems on Chip. International Conference on Autonomic Computing (ICAC), 2011 more… BibTeX
- 7/11Hardware Support to Exploit Parallelism in Homogeneous and Heterogeneous Multi-Core Systems on Chip. Springer Verlag, 2010 more… BibTeX
- 6/11Towards Scalability and Reliability of Autonomic Systems on Chip. Workshop on Self-Organizing Real-Time Systems, 2010 more… BibTeX
- 5/11Combining software and hardware LCS for lightweight on-chip learning. 3rd IFIP Conference on Biologically-Inspired Collaborative Computing, 2010 more… BibTeX
- 4/11Autonomic Workload Management for Multi-Core Processor Systems. International Conference on Architecture of Computing Systems (ARCS), 2010 more… BibTeX
- 3/11Hardware-Supported Learning Classifier Tables in Autonomic Systems on Chip. Organic Computing - Controlled Self-organization, 2008Dagstuhl Seminar more… BibTeX
- 2/11Learning Classifier Tables for Autonomic Systems on Chip. Lecture Notes in Informatics, Springer, Gesellschaft für Informatik, GI Jahrestagung, 2008, 771-778 more… BibTeX
- 1/11Power Estimation of Time Variant SoCs with TAPES. 10th EUROMICRO Conference on Digital System Design: Architectures, Methods, Tools (DSD 07), 2007 more… BibTeX
ASoC - Self-Optimization through Run-Time HW Learning
Motivation and Targets
The Autonomic System on Chip (ASoC) project aims to develop architecture for embedding autonomic/organic principles in SoCs.
Our Autonomic System on Chip (ASoC) project integrates self-organizing and self-optimizing decision systems that enable current and future SoC designs to dynamically balance their performance, power and reliability at run time. These decision systems will be based on learning classifiers, and will be integrated into an ASoC design methodology and architectural demonstrator. This includes the development of utilization and performance monitors, an organic-aware design space exploration, and an Autonomic Element interconnect that allows for individual sub-components to communicate and thereby perform system-wide optimizations.