Heterogeneous multiprocessor scheduling and allocation using evolutionary algorithms

Reuter, Carsten; Schwiegershausen, M.; Pirsch, P.

doi:10.1109/asap.1997.606835

Cited by 6 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It has been tackled as a combinational optimization problem [Reuter et al 1997;Chou and Marculescu 2008;Srinivasan and Chatha 2005;Hoelzenspies et al 2008]. Given the task graphs of the applications under consideration, a cost function is defined based on the topology and capability of each processor cores.…”

Section: Related Workmentioning

confidence: 99%

“…Since the solution space of mapping each task node onto each processor core is very large, different optimization algorithms are derived to find a near-optimal solution. In Reuter et al [1997] a genetic algorithm is used to map an H.261 video encoder to multi-processor systems. In Chou and Marculescu [2008], integer linear programming formulation is used.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic task partition for video decoding on heterogeneous dual-core platforms

Tsai

Shen

Liao

2013

ACM Trans. Embed. Comput. Syst.

View full text Add to dashboard Cite

This article presents the design of a video decoder using dynamic task partition approach on a heterogeneous dual-core embedded platform. For such systems, static task partition between the two cores at design time is a typical approach for application development. In this article, we propose a runtime dynamic task partition model and implement an MPEG-4 Simple Profile video decoder using this approach on a TI OMAP 5912 platform. Comparing with a traditional mobile video decoder optimized for the same DSP core, the performance gain from dynamic task partition is 38.4% on average. More importantly, the gain is achieved with the design constraint that the implementation effort for the dynamic task partition decoder is about the same as the effort using design-time task partition model. Unlike common belief that the inter-processor communication overhead would be too high to justify intense cooperation between two heterogeneous cores, this paper shows that it is indeed beneficial to adopt dynamic task partition model on commercially available heterogeneous multi-core platforms.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Dynamic task partition for video decoding on heterogeneous dual-core platforms

Tsai

Shen

Liao

2013

ACM Trans. Embed. Comput. Syst.

View full text Add to dashboard Cite

show abstract

“…Such systems are promising for fast processing of computationally intensive applications with diverse computation needs. One of the challenges in heterogeneous computing is to develop scheduling algorithms that assign the tasks of applications to processors [17]. Therefore, researchers have proposed many static, dynamic and even hybrid algorithms to minimize execution time of applications running on a heterogeneous system; we can mention [6,8,16,20,22,24].…”

Section: Introductionmentioning

confidence: 99%

Energy aware DAG scheduling on heterogeneous systems

Baskiyar

Abdel-Kader

2010

Cluster Comput

View full text Add to dashboard Cite

We address the problem of scheduling directed a-cyclic task graph (DAG) on a heterogeneous distributed processor system with the twin objectives of minimizing finish time and energy consumption. Previous scheduling heuristics have assigned DAGs to processors to minimize overall run-time of the application. But applications on embedded systems, such as high performance DSP in image processing, multimedia, and wireless security, need schedules which use low energy too.We develop a new scheduling algorithm called Energy Aware DAG Scheduling (EADAGS) on heterogeneous processors that can run on discrete operating voltages. Such processors can scale down their voltages and slow down to reduce energy whenever they idle due to task dependencies. EADAGS combines dynamic voltage scaling (DVS) with Decisive Path Scheduling (DPS) to achieve the twin objectives. Using simulations we show average energy consumption reduction over DPS by 40%. Energy savings increased with increasing number of nodes or increasing Communication to Computation Ratios and decreased with increasing parallelism or increasing number of available processors. These results were based on a software simulation study over a large set of randomly generated graphs as well as graphs for real-world problems with various characteristics.

show abstract

“…The factors are the reliability, tasks' deadlines, and communication reduction or grouping problem. A search technique using genetic algorithms [4,10] is in progress to allow more investigation and evaluation of the proposed method.…”

Section: Discussionmentioning

confidence: 99%

An efficient method to schedule tandem of real-time tasks in cluster computing with possible processor failures

Amin

Ammar

Gokhale

Proceedings of the Eighth IEEE Symposium on Computers and Communications. ISCC 2003

View full text Add to dashboard Cite

Each computer system in operation today is certain to experience faults in its operational lifetime. There is more than one source, which can cause faults, for example environmental factors, communication, interaction with users, or hardware and software design flaws randomly build into the system. A reliable system is the one that would continue operation albeit in a degraded mode despite the presence of faults. In this paper, we introduce an efficient method to schedule a tandem of real-time tasks in cluster computing with possible processor failures. The method is based on developing an objective function that combines different scheduling goals. This objective function is used to guide the search algorithm to find an efficient solution. The proposed algorithm consists of three terms, reliability, deadline and tasks grouping to minimize remote communication among tasks. The proposed method creates a scheduling table based on the objective function then searches this table for a feasible solution. The method is efficient because it reduces communication between different tasks by grouping them together. This grouping process reduces application de-fragmentation as well.

show abstract

Heterogeneous multiprocessor scheduling and allocation using evolutionary algorithms

Cited by 6 publications

References 6 publications

Dynamic task partition for video decoding on heterogeneous dual-core platforms

Dynamic task partition for video decoding on heterogeneous dual-core platforms

Energy aware DAG scheduling on heterogeneous systems

An efficient method to schedule tandem of real-time tasks in cluster computing with possible processor failures

Contact Info

Product

Resources

About