Energy efficiency of heterogeneous multicore system based on the enhanced Amdahl's law

2018 ◽  
Vol 12 (3) ◽  
pp. 261
Author(s):  
Myoung Seo Kim ◽  
Jean Luc Gaudiot ◽  
Naixue Xiong ◽  
Songwen Pei ◽  
Junge Zhang
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Multicore ◽  
Amdahl’S Law ◽  
Multicore System

Energy efficiency of heterogeneous multicore system based on the enhanced Amdahl's law

2018 ◽  
Vol 12 (3) ◽  
pp. 261 ◽  
Author(s):  
Songwen Pei ◽  
Junge Zhang ◽  
Naixue Xiong ◽  
Myoung Seo Kim ◽  
Jean Luc Gaudiot
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Multicore ◽  
Amdahl’S Law ◽  
Multicore System

scholarly journals A Heterogeneous Multicore System on Chip for Energy Efficient Brain Inspired Computing

2018 ◽  
Vol 65 (8) ◽  
pp. 1094-1098 ◽  
Author(s):  
Antonio Pullini ◽  
Francesco Conti ◽  
Davide Rossi ◽  
Igor Loi ◽  
Michael Gautschi ◽  
...  
Keyword(s):  
Energy Efficient ◽  
System On Chip ◽  
Heterogeneous Multicore ◽  
Multicore System ◽  
On Chip

scholarly journals Process Scheduling in Heterogeneous Multicore System using Agent based Graph Coloring Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 8449-8452
Keyword(s):  
Graph Coloring ◽  
Arrival Time ◽  
Process Scheduling ◽  
Agent Based ◽  
Heterogeneous Multicore ◽  
Agent Scheduling ◽  
Multicore System ◽  
Tremendous Amount ◽  
On Chip ◽  
Automated Software

In any heterogeneous multicore system, there are numerous amount of processors with different platform and all the processing units are fabricated on a common single unit preferably on a System on Chip. As there is a tremendous amount of parallelism encompassed in a multicore system, proper utilization of the cores is a big challenge in the current era. Hence a more automated software approach is required like an agent based graph coloring algorithm to find the free processor and schedule the tasks on the respective cores. Predominantly the entire process of scheduling the tasks on multicore system is based on arrival time of process. This paper incorporates the scheduling on the linux 2.6.11 kernel and GEMS simulator for multicore implementation. The core utilization in this type of agent scheduling is 50% more than the existing scheduling mechanism

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