Andelfinger, Philipp and Mittag, Jens and Hartenstein, Hannes (2011) GPU-Based Architectures and Their Benefit for Accurate and Efficient Wireless Network Simulations. In: IEEE 19th Annual International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2011), 25-27 Jul 2011, Singapore. Proceedings, published by IEEE Computer Society, Los Alamitos, CA, USA, pp. 421-424.
Full text not available from this repository.Abstract
In recent years, a trend towards the usage of physical layer models with increased accuracy can be observed within the wireless network community. This trend has several reasons. The consideration of signals - instead of packets - as the smallest unit of a wireless network simulation enables the ability to reflect complex radio propagation characteristics properly, and to study novel PHY/MAC/NET cross-layer optimizations that were not directly possible before, e.g. cognitive radio networks and interference cancellation. Yet, there is a price to pay for the increase of accuracy, namely a significant decrease of runtime performance due to computationally expensive signal processing. In this paper we study whether this price can be reduced - or even eliminated - if GPU-based signal processing is employed. In particular, we present and discuss four different architectures that can be used to exploit GPU-based signal processing in discrete event-based simulations. Our evaluation shows that the runtime costs can not be cut down completely, but significant speedups can be expected compared to a non GPU-based solution.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | ISSN: 1526-7539 |
