scholarly journals Probabilistic Performance Modelling when Using Partial Reconfiguration to Accelerate Streaming Applications with Non-deterministic Task Scheduling

2019 ◽  
pp. 81-95
Author(s):  
Bruno da Silva ◽  
An Braeken ◽  
Abdellah Touhafi
Keyword(s):  
Task Scheduling ◽  
Partial Reconfiguration ◽  
Performance Modelling ◽  
Streaming Applications

DML: Dynamic Partial Reconfiguration with Scalable Task Scheduling for Multi-Applications on FPGAs

2021 ◽  
pp. 1-1
Author(s):  
Ashutosh Dhar ◽  
Edward Richter ◽  
Mang Yu ◽  
Wei Zuo ◽  
Xiaohao Wang ◽  
...  
Keyword(s):  
Task Scheduling ◽  
Partial Reconfiguration ◽  
Dynamic Partial Reconfiguration

scholarly journals Placing Multimode Streaming Applications on Dynamically Partially Reconfigurable Architectures

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
S. Wildermann ◽  
J. Angermeier ◽  
E. Sibirko ◽  
J. Teich
Keyword(s):  
System On Chip ◽  
Reconfigurable Architectures ◽  
Reconfigurable Systems ◽  
Partial Reconfiguration ◽  
Runtime Support ◽  
Streaming Application ◽  
Streaming Applications ◽  
On Chip ◽  
Novel Algorithm

By means of partial reconfiguration, parts of the hardware can be dynamically exchanged at runtime. This allows that streaming application running in different modes of the systems can share resources. In this paper, we discuss the architectural issues to design such reconfigurable systems. For being able to reduce reconfiguration time, this paper furthermore proposes a novel algorithm to aggregate several streaming applications into a single representation, called merge graph. The paper also proposes an algorithm to place streaming application at runtime which not only considers the placement and communication constraints, but also allows to place merge tasks. In a case study, we implement the proposed algorithm as runtime support on an FPGA-based system on chip. Furthermore, experiments show that reconfiguration time can be considerably reduced by applying our approach.

How does manipulation of secondary task scheduling affect human performance?

2006 ◽  
Author(s):  
Patrice D. Tremoulet ◽  
Kathleen M. Stibler ◽  
Patrick Craven ◽  
Joyce Barton ◽  
Adam Gifford ◽  
...  
Keyword(s):  
Task Scheduling ◽  
Secondary Task ◽  
Human Performance

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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