High Performance Heterogeneous Multicore Architectures

2019 ◽  
Author(s):  
Igla Hoxha ◽  
Michael Opoku Agyeman
Keyword(s):  
High Performance ◽  
Multicore Architectures ◽  
Heterogeneous Multicore

scholarly journals Power-Aware Job Scheduling on Heterogeneous Multicore Architectures

2015 ◽  
Vol 26 (3) ◽  
pp. 868-877 ◽  
Author(s):  
Matteo Chiesi ◽  
Luca Vanzolini ◽  
Claudio Mucci ◽  
Eleonora Franchi Scarselli ◽  
Roberto Guerrieri
Keyword(s):  
Job Scheduling ◽  
Multicore Architectures ◽  
Heterogeneous Multicore

A Novel Approach in Scheduling Of the Real- Time Tasks In Heterogeneous Multicore Processor with Fuzzy Logic Technique For Micro-grid Power Management

2018 ◽  
Vol 9 (1) ◽  
pp. 80
Author(s):  
Lavanya Dhanesh ◽  
P. Murugesan
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Power Management ◽  
Execution Time ◽  
High Performance ◽  
Scheduling Algorithm ◽  
Multicore Processor ◽  
Heterogeneous Multicore ◽  
Micro Grid ◽  
Low Performance

Scheduling of tasks based on real time requirement is a major issue in the heterogeneous multicore systemsfor micro-grid power management . Heterogeneous multicore processor schedules the serial tasks in the high performance core and parallel tasks are executed on the low performance cores. The aim of this paper is to implement a scheduling algorithm based on fuzzy logic for heterogeneous multicore processor for effective micro-grid application. Real – time tasks generally have different execution time and dead line. The main idea is to use two fuzzy logic based scheduling algorithm, first is to assign priority based on execution time and deadline of the task. Second , the task which has assigned higher priority get allotted for execution in high performance core and remaining tasks which are assigned low priority get allotted in low performance cores. The main objective of this scheduling algorithm is to increase the throughput and to improve CPU utilization there by reducing the overall power consumption of the micro-grid power management systems. Test cases with different task execution time and deadline were generated to evaluate the algorithms using  MATLAB software.

JParEnt: Parallel entropy decoding for JPEG decompression on heterogeneous multicore architectures

2017 ◽  
Vol 29 (15) ◽  
pp. e4111 ◽  
Author(s):  
Wasuwee Sodsong ◽  
Minyoung Jung ◽  
Jinwoo Park ◽  
Bernd Burgstaller
Keyword(s):  
Multicore Architectures ◽  
Heterogeneous Multicore

scholarly journals Heterogeneous Multicore Parallel Programming for Graphics Processing Units

2009 ◽  
Vol 17 (4) ◽  
pp. 325-336 ◽  
Author(s):  
Francois Bodin ◽  
Stephane Bihan
Keyword(s):  
Parallel Programming ◽  
Graphics Processing Units ◽  
Peak Performance ◽  
Hardware Accelerators ◽  
Multicore Architectures ◽  
Computing Power ◽  
Heterogeneous Multicore ◽  
Product Group ◽  
Legacy Code ◽  
Graphics Processing

Hybrid parallel multicore architectures based on graphics processing units (GPUs) can provide tremendous computing power. Current NVIDIA and AMD Graphics Product Group hardware display a peak performance of hundreds of gigaflops. However, exploiting GPUs from existing applications is a difficult task that requires non-portable rewriting of the code. In this paper, we present HMPP, a Heterogeneous Multicore Parallel Programming workbench with compilers, developed by CAPS entreprise, that allows the integration of heterogeneous hardware accelerators in a unintrusive manner while preserving the legacy code.

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