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Wireless cognitive radio (CR) is a newly emerging paradigm that attempts to opportunistically transmit in licensed frequencies , without affecting the pre-assigned users of these bands. To enable this functionality, such a radio must predict its operational parameters, such as transmit power and spectrum. These tasks, collectively called spectrum management(More)
Trace-driven simulation is commonly used by the computer architecture research community to pursue answers to a wide variety of architectural design issues. Traces taken from benchmark execution have been extensively studied to optimize the design of pipelines, branch predictors, and especially cache memories. Today's computer designs have been optimized(More)
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving large-scale instances of classic multi-agent problems. We apply our techniques to the predator-prey pursuit problem. We first demonstrate that Kanerva Coding applied within a reinforcement learner(More)
Cognitive Radio Ad Hoc Networks (CRAHNs) must identify the best operational characteristics based on the local spectrum availability , reachability with other nodes, choice of spectrum, while maintaining an acceptable end-to-end performance. The distributed nature of the operation forces each node to act autonomously, and yet has a goal of optimizing the(More)
With the growing popularity of DSPs and their associated applications, cost-effective software development has become a major issue. High-level language compilers are becoming more commonplace in the DSP world. While these compilers can generate correct code for DSP architectures, there remains considerable room for performance improvements. This paper(More)
—We present the parallel, MPI-based implementation of the SDFMM computer code using a thirty two-node Intel Pentium-based Beowulf cluster. The SDFMM is a fast algorithm that is a hybridization of the method of moments (MoMs), the fast multipole method (FMM), and the steepest descent integration path (SDP), which is used to solve large-scale linear systems(More)
The combination of hardware acceleration and flexibility make FPGAs important to image processing applications. There is also a need for efficient, flexible hardware/software codesign environments that can balance the benefits and costs of using FPGAs. Image processing applications often consist of a pipeline of components where each component applies a(More)
<italic>Since there is generally insufficient instruction level parallelism within a single basic block, higher performance is achieved by speculatively scheduling operations in superblocks. This is difficult in general because each branch competes for the processor's limited resources. Previous work manages the performance tradeoffs that exist between(More)
Cloud computing nowadays becomes quite popular among a community of cloud users by offering a variety of resources. However, burstiness in user demands often dramatically degrades the application performance. In order to satisfy peak user demands and meet Service Level Agreement (SLA), efficient resource allocation schemes are highly demanded in the cloud.(More)