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Runtime thermal management of many-core systems

Runtime thermal management of many-core systems

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Chapter Contents:

  • 9.1 Thermal management of many-core embedded systems
  • 9.1.1 Uncertainty in workload estimation
  • 9.1.2 Learning-based uncertainty characterization
  • 9.1.2.1 Multinomial logistic regression model
  • 9.1.2.2 Maximum likelihood estimation
  • 9.1.2.3 Uncertainty interpretation
  • 9.1.3 Overall design flow
  • 9.1.4 Early evaluation of the approach
  • 9.1.4.1 Impact of workload uncertainty: H. 264 case study
  • 9.1.4.2 Thermal improvement considering workload uncertainty
  • 9.2 Thermal management of 3D many-core systems
  • 9.2.1 Recent advances on 3D thermal management
  • 9.2.2 Preliminaries
  • 9.2.2.1 Application model
  • 9.2.2.2 Multiprocessor platform model
  • 9.2.2.3 3D IC model
  • 9.2.3 Thermal-aware mapping
  • 9.2.3.1 Thermal profiling
  • 9.2.3.2 Runtime
  • 9.2.3.3 Application merging
  • 9.2.3.4 Resource allocation
  • 9.2.3.5 Throughput computation
  • 9.2.3.6 Utilization minimization
  • 9.2.4 Experimental results
  • 9.2.4.1 Benchmark applications
  • 9.2.4.2 Target 3D many-core system
  • 9.2.4.3 Temperature simulation
  • 9.2.4.4 Interconnect energy computation
  • 9.2.4.5 Thermal profiling results
  • 9.2.4.6 Benchmark application results
  • 9.2.4.7 Case-study for real-life applications
  • 9.3 Conclusions and future directions
  • References

Inspec keywords: thermal management (packaging); multiprocessing systems; parallel processing

Other keywords: submicron technology nodes; high-performance computing; leakage power; many-core systems; system-on-chip; thermal management

Subjects: Product packaging; Multiprocessing systems

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