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Programming models and runtimes

Programming models and runtimes

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Ultrascale Computing Systems — Recommend this title to your library

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Several millions of execution flows will be executed in ultrascale computing systems (UCS), and the task for the programmer to understand their coherency and for the runtime to coordinate them is unfathomable. Moreover, related to UCS large scale and their impact on reliability, the current static point of view is not more sufficient. A runtime cannot consider to restart an application because of the failure of a single node as statically several nodes will fail every day. Classical management of these failures by the programmers using checkpoint restart is also too limited due to the overhead at such a scale. The article explores programming models and runtimes required to facilitate the task of scaling and extracting performance on continuously evolving platforms, while providing resilience and fault-tolerant mechanisms to tackle the increasing probability of failures throughout the whole software stack.

Chapter Contents:

  • 2.1 Using performance and energy models for ultrascale computing applications
  • 2.1.1 Terminology
  • 2.1.2 Performance models of computation
  • 2.1.3 Performance models of communications
  • 2.1.4 Power and energy models of computation
  • 2.1.5 Holistic approaches to optimization for performance and energy
  • 2.2 Impact of workflow enactment modes on scheduling and workflow performance
  • 2.2.1 Scientific workflow model
  • 2.2.2 Workflow enactment
  • 2.2.3 Workflow scheduling
  • 2.2.4 Manycore workflow runtime engine
  • 2.2.5 Impact of incomplete WEP on full-ahead scheduling
  • 2.2.6 Methodology
  • 2.2.6.1 Random workflow generation
  • 2.2.6.2 Experimental setup
  • 2.2.7 Experimental results
  • 2.2.8 Conclusion
  • 2.3 Toward general-purpose computations at the edge
  • 2.3.1 Motivation
  • 2.3.2 Edge computing opportunities
  • 2.3.3 Enabling technologies for the edge
  • 2.3.4 Runtime for edge scenarios
  • 2.3.5 Future directions
  • 2.4 Spectral graph partitioning for process placement on heterogeneous platforms
  • 2.4.1 Graphs and matrices: examples
  • 2.4.2 Laplacian and partitions
  • 2.4.3 Laplacian with potential of vertex weights
  • 2.4.4 Mesh graph
  • 2.4.5 Numerical experiment
  • 2.4.6 Conclusions
  • 2.5 Summary

Inspec keywords: checkpointing; software fault tolerance; distributed programming

Other keywords: failure management; software stack; checkpoint restart; fault-tolerant mechanisms; runtimes; ultrascale computing systems; programming models

Subjects: Diagnostic, testing, debugging and evaluating systems; Parallel programming; Distributed systems software

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