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Self-aware Compute Nodes

  • Andreas Agne
  • Markus Happe
  • Achim Löosch
  • Christian Plessl
  • Marco Platzner
Chapter
Part of the Natural Computing Series book series (NCS)

Abstract

Many modern compute nodes are heterogeneous multi-cores that integrate several CPU cores with fixed function or reconfigurable hardware cores. Such systems need to adapt task scheduling and mapping to optimise for performance and energy under varying workloads and, increasingly important, for thermal and fault management and are thus relevant targets for self-aware computing. In this chapter, we take up the generic reference architecture for designing self-aware and self-expressive computing systems and refine it for heterogeneous multi-cores. We present ReconOS, an architecture, programming model and execution environment for heterogeneous multi-cores, and show how the components of the reference architecture can be implemented on top of ReconOS. In particular, the unique feature of dynamic partial reconfiguration supports self-expression through starting and terminating reconfigurable hardware cores. We detail a case study that runs two applications on an architecture with one CPU and 12 reconfigurable hardware cores and present self-expression strategies for adapting under performance, temperature and even conflicting constraints. The case study demonstrates that the reference architecture as a model for self-aware computing is highly useful as it allows us to structure and simplify the design process, which will be essential for designing complex future compute nodes. Furthermore, ReconOS is used as a base technology for flexible protocol stacks in Chapter 10, an approach for self-aware computing at the networking level.

Keywords

Performance Constraint Reference Architecture Thermal Constraint Hardware Thread Meta Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Andreas Agne
    • 1
  • Markus Happe
    • 2
  • Achim Löosch
    • 1
  • Christian Plessl
    • 1
  • Marco Platzner
    • 1
  1. 1.Paderborn UniversityPaderbornGermany
  2. 2.ETH ZurichZurichSwitzerland

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