Paper Info
Title
Heterogeneous reconfigurable system for adaptive particle filters in real-time applications
Abstract
This paper presents a heterogeneous reconfigurable system for real-time applications applying particle filters. The system consists of an FPGA and a multi-threaded CPU. We propose a method to adapt the number of particles dynamically and utilise the run-time reconfigurability of the FPGA for reduced power and energy consumption. An application is developed which involves simultaneous mobile robot localisation and people tracking. It shows that the proposed adaptive particle filter can reduce up to 99% of computation time. Using run-time reconfiguration, we achieve 34% reduction in idle power and save 26-34% of system energy. Our proposed system is up to 7.39 times faster and 3.65 times more energy efficient than the Intel Xeon X5650 CPU with 12 threads, and 1.3 times faster and 2.13 times more energy efficient than an NVIDIA Tesla C2070 GPU.
Year
DOI
Venue
2013
10.1007/978-3-642-36812-7_1
ARC
Keywords
Field
DocType
proposed adaptive particle filter,intel xeon x5650 cpu,energy consumption,system energy,reduced power,proposed system,multi-threaded cpu,real-time application,particle filter,idle power,heterogeneous reconfigurable system,mobile robot,energy efficient
Reconfigurability,Efficient energy use,Computer science,Parallel computing,Particle filter,Field-programmable gate array,Thread (computing),Real-time computing,Xeon,Energy consumption,Control reconfiguration,Embedded system
Conference
Volume
ISSN
Citations 
7806
0302-9743
9
PageRank 
References 
Authors
0.63
8
6
Name
Order
Citations
PageRank
Thomas C. P. Chau1536.81
Xinyu Niu213523.16
Alison Eele3202.36
Wayne Luk43752438.09
Peter Y. K. Cheung51720208.45
Jan Maciejowski6172.64