Enabling Fast Exploration and Validation of Thermal Dissipation Requirements for Heterogeneous SoCs

@article{hrling2021EnablingFE,
  title={Enabling Fast Exploration and Validation of Thermal Dissipation Requirements for Heterogeneous SoCs},
  author={Joel {\"O}hrling and Dragos Truscan and S{\'e}bastien Lafond},
  journal={2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)},
  year={2021},
  pages={114-123}
}
  • Joel Öhrling, D. Truscan, S. Lafond
  • Published 1 April 2021
  • Computer Science
  • 2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
The management of the energy consumption and thermal dissipation of multi-core heterogeneous platforms is becoming increasingly important as it can have direct impact on the platform performance. This paper discusses an approach that enables fast exploration and validation of heterogeneous system on chips (SoCs) platform configurations with respect to their thermal dissipation. Such platforms can be configured to find the optimal trade-off between performance and power consumption. This… 

References

SHOWING 1-10 OF 35 REFERENCES
N4SID and MOESP subspace identification methods
TLDR
The weighting factor α, used in online identification is obtained from trial and error and particle swarm optimization (PSO), and the value of α is determined in the online identification and a more accurate result with lower computation time is obtained.
An Open-Source System Identification Package for Multivariable Processes
TLDR
An open-source System Identification Package for PYthon (SIPPY 1), which implements different methods to identify linear discrete-time multi-input multi-output systems, in input-output transfer function or state space form, shows effectiveness and computational efficiency in comparison with state-of-art proprietary system identification software.
Automatic exploratory performance testing using a discriminator neural network
TLDR
A novel exploratory performance testing algorithm that uses supervised learning to optimize the test suite generation process to generate test suites that contain a large number of positive tests, revealing performance defects or other issues of interest in the system under test.
Modeling and simulation of power consumption and execution times for real-time tasks on embedded heterogeneous architectures
In this work, we introduce a power-consumption model for heterogeneous multicore architectures that captures the variability of energy consumption based on processing workload type, in addition to
Evaluating Sustainable Interaction Design of Digital Services: The Case of YouTube
TLDR
It is shown how a Digital Service Provider (DSP) might incorporate SID into their design process and quantitatively evaluate a specific SID intervention by combining user analytics data with environmental life cycle assessment, and how SID can contribute to corporate greenhouse gas (GHG) reduction strategies.
Investigation of a computer CPU heat sink under laminar forced convection using a structural stability method
Chapter 5 – Multiprocessor Architectures
Heat Dissipation in a Computer
TLDR
Results show that computers dissipate a lot of heat; in the order of hundreds of joules per second; the heat dissipation was found to increase with an increase in the processor workload.
Thermal Prediction for Immersion Cooling Data Centers Based on Recurrent Neural Networks
TLDR
This paper successfully obtained a predictive thermal model using a neural network architecture based on a Gated Recurrent Unit, accurate enough to keep the temperature of the cooling system within the maximum efficiency region, under real workload conditions.
...
...