Online Real-Time Task Scheduling in Heterogeneous Multicore System-on-a-Chip

Chen, Ya-Shu; Liao, Han Chiang; Tsai, Ting-Hao

doi:10.1109/tpds.2012.114

Cited by 31 publications

(16 citation statements)

References 72 publications

(72 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Chen and Liao [6] proposed a scheduling algorithm specif ically for the heterogeneous multicore SoCs. Named as Het erogeneous Dual-core Scheduling Algorithm (HDS), it works on a processor and a co-processor which have master-slave relationship.…”

Section: )mentioning

confidence: 99%

Simulations and performance evaluation of Real-Time Multi-core Systems

Sharma

Elmiligi

Gebali

2014

2014 9th International Conference on Computer Engineering &Amp; Systems (ICCES)

View full text Add to dashboard Cite

Ahstract-The development of broad range of multi-core processors in desktop and server systems has lead to a definite need of an overall performance evaluation tool. This paper presents a new tool to analyze the performance of multi-core systems at early design phases. The proposed tool helps developers test different design options and choose the best solution for multi-core applications. Different design factors can be considered and evaluated to get the best core utilization of multi-core systems while achieving the best response time for the real-time applications.The paper explores the implementation of different algo rithms at four different design stages: dependability analysis, task execution sequence, real-time scheduling and core mapping.As a proof of concept, a case study is presented to show the significance of changing one design parameter on the overall system performance. Experimental results show an increase of the CPU utilization by 31.25% when changing the number of cores from 3 to 2.

show abstract

Section: )mentioning

confidence: 99%

Simulations and performance evaluation of Real-Time Multi-core Systems

Sharma

Elmiligi

Gebali

2014

2014 9th International Conference on Computer Engineering &Amp; Systems (ICCES)

View full text Add to dashboard Cite

show abstract

“…• During overloaded condition, the algorithm switch to ACO algorithm calculates the total execution time and minimum time required for each process and the process which contain the minimum execution time is executed first [19,20]. Following are the steps to create and schedule the process:…”

Section: Working Of An Adaptive Algorithmmentioning

confidence: 99%

Aggregation of EDF and ACO for Enhancing Real Time System Performance

Nandanwar¹,

Shrawankar²

2013

IJCA

View full text Add to dashboard Cite

Time constraint is the main factor in real time operating system and it affects the deadline of the process. To achieve deadline, proper scheduling algorithm is required to schedule the task. In this paper an Adaptive scheduling algorithm is developed which is the combination of Earliest Deadline First (EDF) and Ant Colony Optimization (ACO). The EDF algorithm places the process in a priority queue and executed using the deadline. The priority of the processes depends upon the deadline and handles the under loaded condition. The limitation of EDF algorithm is that it cannot handle the overloaded condition. The execution of ACO algorithm is based on the execution time. Process which contains the minimum execution time is executed first. The limitation of ACO algorithm is, it takes more time for execution than EDF. Therefore, to remove the limitation of both the algorithms an Adaptive scheduling algorithm is developed. It increases performance of the system and decreases the system failure. Also the percentage of missing deadline is reduced. The advantage of an Adaptive scheduling algorithm is, it handles over-loaded and under-loaded condition simultaneously.The performance of an Adaptive scheduling algorithm is calculated in terms of Success Ratio that is the number of process scheduled and CPU Utilization. The result of execution time is compared with the EDF and ACO scheduling algorithm. The goal of an Adaptive scheduling algorithm is to show the switching between the scheduling algorithms and to decrease the system failure and increase the system performance.

show abstract

“…Heterogeneous multi-cores [5] with a combination of predictable and conventional processors offer an appealing hardware platform for deploying mixed-time critical applications. This is because HRT tasks can execute on predictable cores while SRT tasks on conventional cores.…”

Section: Introductionmentioning

confidence: 99%

A framework for scheduling DRAM memory accesses for multi-core mixed-time critical systems

Hassan

Patel

Pellizzoni

2015

21st IEEE Real-Time and Embedded Technology and Applications Symposium

View full text Add to dashboard Cite

Mixed-time critical systems are real-time systems that accommodate both hard real-time (HRT) and soft realtime (SRT) tasks. HRT tasks mandate a gurantee on the worstcase latency, while SRT tasks have average-case bandwidth (BW) demands. Memory requests in mixed-time critical systems usually have different transaction sizes based on whether the issuer task is HRT or SRT. For example, HRT tasks often issue requests with a cache line size. On the other side, SRT tasks may issue requests with a size of KBs. Requests from multimedia cores, cores controlling network interfaces and direct memory accesses (DMAs) are obvious examples of these large-size requests. Based on these observations, we promote in this work a new approach to schedule memory requests. This approach retains locality within large-size requests to minimize the worst-case latency, while maintaining the average-case BW as high as required. To achieve this target, we introduce a novel and compact time-division-multiplexing scheduler that is adequate for mixed-time critical systems. We also present a novel framework that constructs optimal offchip DRAM memory controller schedules for multi-core mixedtime critical systems. These schedules are loaded to the memory controller during boot-time. Based on the proposed schedule, we provide a detailed static analysis that guarantees predictability. We compare the proposed controller against state-of-the-art realtime memory controllers using synthetic experiments as well as a practical use-case from multimedia systems. 307 978-1-4799-8603-3/15/$31.00 ©2015 IEEE

show abstract

Online Real-Time Task Scheduling in Heterogeneous Multicore System-on-a-Chip

Cited by 31 publications

References 72 publications

Simulations and performance evaluation of Real-Time Multi-core Systems

Simulations and performance evaluation of Real-Time Multi-core Systems

Aggregation of EDF and ACO for Enhancing Real Time System Performance

A framework for scheduling DRAM memory accesses for multi-core mixed-time critical systems

Contact Info

Product

Resources

About