scholarly journals Code generation for energy‐efficient execution of dynamic streaming task graphs on parallel and heterogeneous platforms

2020 ◽  
Author(s):  
Sebastian Litzinger ◽  
Jörg Keller
Keyword(s):  
Code Generation ◽  
Energy Efficient ◽  
Heterogeneous Platforms ◽  
Task Graphs ◽  
Efficient Execution

Cross-architecture prediction based scheduling for energy efficient execution on single-ISA heterogeneous chip-multiprocessors

2015 ◽  
Vol 39 (4-5) ◽  
pp. 271-285 ◽  
Author(s):  
Ying Zhang ◽  
Lide Duan ◽  
Bin Li ◽  
Lu Peng ◽  
Srinivasan Sadagopan
Keyword(s):  
Energy Efficient ◽  
Chip Multiprocessors ◽  
Efficient Execution

scholarly journals Data-driven framework for energy-efficient smart cities

2020 ◽  
Vol 17 (1) ◽  
pp. 41-63 ◽  
Author(s):  
Nenad Petrovic ◽  
Djordje Kocic
Keyword(s):  
Deep Learning ◽  
Energy Distribution ◽  
Code Generation ◽  
Energy Efficient ◽  
Cost Reduction ◽  
Smart Cities ◽  
Autonomous Vehicle ◽  
Linear Optimization ◽  
Data Driven ◽  
Distribution Cost

Energy management is one of the greatest challenges in smart cities. Moreover, the presence of autonomous vehicles makes this task even more complex. In this paper, we propose a data-driven smart grid framework which aims to make smart cities energy-efficient focusing on two aspects: energy trading and autonomous vehicle charging. The framework leverages deep learning, linear optimization, semantic technology, domain-specific modelling notation, simulation and elements of relay protection. The evaluation of deep learning module together with code generation time and energy distribution cost reduction performed within the simulation environment also presented in this paper are given. According to the results, the achieved energy distribution cost reduction varies and depends from case to case.

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