Abstract
Self-aware computing is a paradigm for structuring and simplifying the design and operation of computing systems that face unprecedented levels of system dynamics and thus require novel forms of adaptivity. The generality of the paradigm makes it applicable to many types of computing systems and, previously, researchers started to introduce concepts of self-awareness to multicore architectures. In our work we build on a recent reference architectural framework as a model for self-aware computing and instantiate it for an FPGA-based heterogeneous multicore running the ReconOS reconfigurable architecture and operating system. After presenting the model for self-aware computing and ReconOS, we demonstrate with a case study how a multicore application built on the principle of self-awareness, autonomously adapts to changes in the workload and system state. Our work shows that the reference architectural framework as a model for self-aware computing can be practically applied and allows us to structure and simplify the design process, which is essential for designing complex future computing systems.
- A. Agarwal, J. Miller, J. Eastep, D. Wentziaff, and H. Kasture. 2009. Self-aware computing. Final Tech. Rep. AFRL-RI-RS-TR-2009-161, 81.Google Scholar
- A. Agne, M. Platzner, and E. Lubbers. 2011. Memory virtualization for multithreaded reconfigurable hardware. In Proceedings of the International Conference on Field Programmable Logic and Applications. IEEE. Google ScholarDigital Library
- D. B. Bartolini, F. Sironi, M. Maggio, R. Cattaneo, D. Sciuto, and M. D. Santambrogio. 2012. A framework for thermal and performance management. In Proceedings of the Workshop on Managing Systems Automatically and Dynamically.Google Scholar
- T. Becker, A. Agne, P. R. Lewis, R. Bahsoon, F. Faniyi, L. Esterle, A. Keller, A. Chandra, A. R. Jensenius, and S. C. Stilkerich. 2012. EPiCS: Engineering proprioception in computing systems. In Proceedings of the Conference on Embedded and Ubiquitous Computing. IEEE.Google Scholar
- T. Becker, Q. Jin, W. Luk, and S. Weston. 2011. Dynamic constant reconfiguration for explicit finite difference option pricing. In Proceedings of the International Conference on Reconfigurable Computing and FPGAs. IEEE, 176--181. Google ScholarDigital Library
- S. Borkar. 2005. Designing reliable systems from unreliable components: The challenges of transistor variability and degradation. IEEE Micro, 10--16. Google ScholarDigital Library
- J. Chen and L. K. John. 2009. Efficient program scheduling for heterogeneous multi-core processors. In Proceedings of the Design Automation Conference. ACM. Google ScholarDigital Library
- A. K. Coskun, T. S. Rosing, K. A. Whisnant, and K. C. Gross. 2008. Static and dynamic temperature-aware scheduling for multiprocessor SoCs. IEEE Trans. VLSI Syst. 16, 9, 1127--1140. Google ScholarDigital Library
- J.-P. Diguet, Y. Eustache, and G. Gogniat. 2011. Closed-loop--based self-adaptive hardware/software-embedded systems: Design methodology and smart cam case study. ACM Trans. Embed. Comput. Syst. 10, 3, 1--28. Google ScholarDigital Library
- S. Duval and R. A. Wicklund. 1972. A Theory of Objective Self Awareness. Academic Press.Google Scholar
- T. Ebi, M. A. A. Faruque, and J. Henkel. 2009. TAPE: Thermal-aware agent-based power economy for multi/many-core architectures. In Proceedings of the International Conference on Computer-Aided Design. Google ScholarDigital Library
- L. Esterle, P. Lewis, M. Bogdanski, B. Rinner, and X. Yao. 2011. A Socio-economic approach to online vision graph generation and handover in distributed smart camera networks. In Proceedings of the International Conference on Distributed Smart Cameras.Google Scholar
- European Commission. 2013. Self-awareness in autonomic systems.Google Scholar
- C. Goukens, S. Dewitte, and L. Warlop. 2007. Me, Myself, And My Choices: The Influence of Private Self-Awareness on Preference-Behavior Consistency. Open Access Publication, Katholieke Universiteit Leuven.Google Scholar
- M. Happe, A. Agne, and C. Plessl. 2011. Measuring and predicting temperature distributions on FPGAs at run-time. In Proceedings of the International Conference on Reconfigurable Computing and FPGAs. IEEE. Google ScholarDigital Library
- M. Happe, H. Hangmann, A. Agne, and C. Plessl. 2012. Eight Ways to put your FPGA on Fire: A Systematic Study of Heat Generators. In Proceedings of the International Conference on Reconfigurable Computing and FPGAs. IEEE.Google Scholar
- H. Hoffmann, J. Eastep, M. D. Santambrogio, J. E. Miller, and A. Agarwal. 2010. Application heartbeats: A generic interface for specifying program performance and goals in autonomous computing environments. In Proceedings of the International Conference on Autonomic Computing. Google ScholarDigital Library
- H. Hoffmann, J. Holt, and G. Kurian. et al. 2012. Self-aware computing in the angstrom processor. In Proceedings of the Design Automation Conference. Google ScholarDigital Library
- IBM. 2003. An architectural blueprint for autonomic computing. Tech. rep.Google Scholar
- P. Jones, Y. Cho, and J. Lockwood. 2007. Dynamically optimizing FPGA applications by monitoring temperature and workloads. In Proceedings of the International Conference on VLSI Design. IEEE. Google ScholarDigital Library
- W. Leland, M. Taqqu, W. Willinger, and D. WILSON. 1994. On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Trans. Networking 2, 1, 1--15. Google ScholarDigital Library
- P. R. Lewis, A. Chandra, S. Parsons, E. Robinson, K. Glette, R. Bahsoon, J. Torresen, and X. Yao. 2011. A survey of self-awareness and its application in computing systems. In Proceedings of the International Conference on Self-Adaptive and Self-Organizing Systems Workshops. Google ScholarDigital Library
- E. Lübbers and M. Platzner. 2009. ReconOS: Multithreaded programming for reconfigurable computers ACM Trans. Embed. Comput. Syst. 9. Google ScholarDigital Library
- F. Mulas, D. Atienza, A. Acquaviva, S. Carta, L. Benini, and G. Demicheli. 2009. Thermal balancing policy for multiprocessor stream computing platforms. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 28, 12, 1870--1882. Google ScholarDigital Library
- X. Y. Niu, K. H. Tsoi, and W. Luk. 2011. Reconfiguring distributed applications in FPGA accelerated cluster with wireless networking. In Proceedings of the International Conference on Field Programmable Logic and Applications. IEEE. Google ScholarDigital Library
- L. Paulson. 2003. DARPA creating self-aware computing. IEEE Computer 36, 3, 24. Google ScholarDigital Library
- RECONOS. 2013. A programming model and OS for reconfigurable hardware.Google Scholar
- M. D. Santambrogio, H. Hoffmann, J. Eastep, and A. Agarwal. 2010. Enabling Technologies for Self-aware Adaptive Systems. In Proceedings of the Conference on Adaptive Hardware and Systems. IEEE.Google Scholar
- H. Schmeck, C. Müller-Schloer, E. Cakar, M. Mnif, and U. Richter. 2011. Adaptivity and self-organisation in organic computing systems. In Organic Computing: A Paradigm Shift for Complex Systems Autonomic Systems, Vol. 1, Springer Basel, 5--37.Google Scholar
- G. D. M. Serugendo, M.-P. Gleizes, and A. Karageorgos. 2011. Self-Organizing Software: From Natural to Artificial Adaptation. Springer. Google ScholarDigital Library
- F. Sironi, D. B. Bartolini, S. Campanoni, F. Cancare, H. Hoffmann, D. Sciuto, and M. D. Santambrogio. 2012. Metronome: Operating system level performance management via self-adaptive computing. In Proceedings of the Design Automation Conference. ACM. Google ScholarDigital Library
- F. Sironi, A. Cuoccio, H. Hoffmann, M. Maggio, and M. Santambrogio. 2011. Evolvable systems on reconfigurable architecture via self-aware adaptive applications. In Proceedings of the NASA/ESA Conference on Adaptive Hardware and Systems.Google Scholar
- F. Sironi, A. Cuoccio, H. Hoffmann, M. Maggio, and M. Santambrogio. 2010. Self-aware adaptation in FPGA-based systems. In Proceedings of the International Conference on Field Programmable Logic and Applications. IEEE. Google ScholarDigital Library
- R. Sterritt and M. Hinchey. 2010. SPAACE IV: Self-Properties for an autonomous and autonomic computing environment - Part IV A newish hope. In Proceedings of the IEEE International Conference and Workshops on Engineering of Autonomic and Autonomous Systems. Google ScholarDigital Library
- V. Strassen. 1969. Gaussian elimination is not optimal. Numerische Mathematik 13:354--356. Google ScholarDigital Library
- M. J. Wooldridge. 2009. An Introduction to MultiAgent Systems 2nd Ed. Wiley. Google ScholarDigital Library
- J. Zeppenfeld, A. Bouajila, W. Stechele, A. Bernauer, O. Bringmann, W. Rosenstiel, and A. Herkersdorf. 2011. Applying ASoC to multi-core applications for workload management. In Organic Computing: A Paradigm Shift for Complex Systems, C. Müller-Schloer, H. Schmeck, and T. Ungerer, Eds., Autonomic Systems Series, vol. 1. Springer, 461--472.Google Scholar
Index Terms
- Self-Awareness as a Model for Designing and Operating Heterogeneous Multicores
Recommendations
Enhancing multithreaded performance of asymmetric multicores with SIMD offloading
DATE '20: Proceedings of the 23rd Conference on Design, Automation and Test in EuropeAsymmetric multicore architectures with single-ISA can accelerate multithreaded applications by running code that does not execute concurrently (i.e., the serial region) on a big core and the parallel region on a larger number of smaller cores. ...
A Tradeoff Analysis of FPGAs, GPUs, and Multicores for Sliding-Window Applications
The increasing usage of hardware accelerators such as Field-Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) has significantly increased application design complexity. Such complexity results from a larger design space created by ...
A performance and energy comparison of FPGAs, GPUs, and multicores for sliding-window applications
FPGA '12: Proceedings of the ACM/SIGDA international symposium on Field Programmable Gate ArraysWith the emergence of accelerator devices such as multicores, graphics-processing units (GPUs), and field-programmable gate arrays (FPGAs), application designers are confronted with the problem of searching a huge design space that has been shown to ...
Comments