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Compiler-Assisted Energy Optimization For Clustered VLIW Processors
(2010-04-13)
Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by ...
Simulation Based Algorithms For Markov Decision Process And Stochastic Optimization
(2010-08-06)
In Chapter 2, we propose several two-timescale simulation-based actor-critic algorithms for solution of infinite horizon Markov Decision Processes (MDPs) with finite state-space under the average cost criterion. On the ...
Recovery From DoS Attacks In MIPv6 : Modelling And Validation
(2010-07-26)
Denial-of-Service (DoS) attacks form a very important category of security threats that are possible in MIPv6 (Mobile Internet Protocol version 6). This thesis proposes a scheme for participants (Mobile Node, Home Agent, ...
Computational Protein Structure Analysis : Kernel And Spectral Methods
(2010-08-24)
The focus of this thesis is to develop computational techniques for analysis of protein structures. We model protein structures as points in 3-dimensional space which in turn are modeled as weighted graphs. The problem of ...
Using Explicit State Space Enumeration For Specification Based Regression Testing
(2010-07-08)
Regression testing of an evolving software system may involve significant challenges. While, there would be a requirement of maximising the probability of finding out if the latest changes to the system has broken some ...
Compiler Assisted Energy Management For Sensor Network Nodes
(2010-08-16)
Emerging low power, embedded, wireless sensor devices are useful for wide range of applications, yet have very limited processing storage and especially energy resources. Sensor networks have a wide variety of applications ...
Learning Algorithms Using Chance-Constrained Programs
(2010-07-08)
This thesis explores Chance-Constrained Programming (CCP) in the context of learning. It is shown that chance-constraint approaches lead to improved algorithms for three important learning problems — classification with ...
Efficient Frequent Closed Itemset Algorithms With Applications To Stream Mining And Classification
(2010-08-24)
Data mining is an area to find valid, novel, potentially useful, and ultimately understandable abstractions in a data. Frequent itemset mining is one of the important data mining approaches to find those abstractions in ...
Large Scale Implementation Of The Block Lanczos Algorithm
(2010-08-16)
Large sparse matrices arise in many applications, especially in the major problems of Cryptography of factoring integers and computing discrete logarithms. We focus attention on such matrices called sieve matrices generated ...
Efficient Compilation Of Stream Programs Onto Multi-cores With Accelerators
(2010-12-30)
Over the past two decades, microprocessor manufacturers have typically relied on wider issue widths and deeper pipelines to obtain performance improvements for single threaded applications. However, in the recent years, ...