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ETD at Indian Institute of Science (2.878 recursos)

Repository of Theses and Dissertations of Indian Institute of Science, Bangalore, India. The repository has been developed to capture, disseminate and preserve research theses of Indian Institute of Science.

Computer Science and Automation (csa)

Mostrando recursos 1 - 20 de 112

  1. Power Issues in SoCs : Power Aware DFT Architecture and Power Estimation

    Tudu, Jaynarayan Thakurdas
    Test power, data volume, and test time have been long-standing problems for sequential scan based testing of system-on-chip (SoC) design. The modern SoCs fabricated at lower technology nodes are complex in nature, the transistor count is as large as billions of gate for some of the microprocessors. The design complexity is further projected to increase in the coming years in accordance with Moore's law. The larger gate count and integration of multiple functionalities are the causes for higher test power dissipation, test time and data volume. The dynamic power dissipation during scan testing, i.e. during scan shift, launch and response...

  2. Power Issues in SoCs : Power Aware DFT Architecture and Power Estimation

    Tudu, Jaynarayan Thakurdas
    Test power, data volume, and test time have been long-standing problems for sequential scan based testing of system-on-chip (SoC) design. The modern SoCs fabricated at lower technology nodes are complex in nature, the transistor count is as large as billions of gate for some of the microprocessors. The design complexity is further projected to increase in the coming years in accordance with Moore's law. The larger gate count and integration of multiple functionalities are the causes for higher test power dissipation, test time and data volume. The dynamic power dissipation during scan testing, i.e. during scan shift, launch and response...

  3. Symmetry in Scalar Fields

    Thomas, Dilip Mathew
    Scalar fields are used to represent physical quantities measured over a domain of interest. Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. This thesis proposes three methods to detect symmetry in scalar fields. The first method models symmetry detection as a subtree matching problem in the contour tree, which is a topological graph abstraction of the scalar field. The contour tree induces a hierarchical segmentation of features at different scales and hence this method can detect symmetry at different scales. The second method...

  4. Game-Theoretic Analysis of Strategic Behaviour in Networks, Crowds and Classrooms

    Vallam, Rohith Dwarakanath
    Over the past decade, the explosive growth of the Internet has led to a surge of interest to understand and predict aggregate behavior of large number of people or agents, particularly when they are connected through an underlying network structure. Numerous Internet-based applications have emerged that are as diverse as getting micro-tasks executed through online labor markets (also known as crowd sourcing) to acquiring new skills through massively open online courses (also known as MOOCs). However, there has been a major inadequacy in existing studies with respect to evaluating the impact of strategic behavior of the agents participating in such...

  5. Consistency of Spectral Algorithms for Hypergraphs under Planted Partition Model

    Ghoshdastidar, Debarghya
    Hypergraph partitioning lies at the heart of a number of problems in machine learning as well as other engineering disciplines. While partitioning uniform hypergraphs is often required in computer vision problems that involve multi-way similarities, non-uniform hypergraph partitioning has applications in database systems, circuit design etc. As in the case of graphs, it is known that for given objective and balance constraints, the problem of optimally partitioning a hypergraph is NP-hard. Yet, over the last two decades, several efficient heuristics have been studied in the literature and their empirical success is widely appreciated. In contrast to the extensive studies related...

  6. Consistency of Spectral Algorithms for Hypergraphs under Planted Partition Model

    Ghoshdastidar, Debarghya
    Hypergraph partitioning lies at the heart of a number of problems in machine learning as well as other engineering disciplines. While partitioning uniform hypergraphs is often required in computer vision problems that involve multi-way similarities, non-uniform hypergraph partitioning has applications in database systems, circuit design etc. As in the case of graphs, it is known that for given objective and balance constraints, the problem of optimally partitioning a hypergraph is NP-hard. Yet, over the last two decades, several efficient heuristics have been studied in the literature and their empirical success is widely appreciated. In contrast to the extensive studies related...

  7. Targeted Client Synthesis for Detecting Concurrency Bugs

    Samak, Malavika
    Detecting concurrency bugs can be challenging due to the intricacies associated with their manifestation. These intricacies correspond to identifying the methods that need to be invoked concurrently, the inputs passed to these methods and the interleaving of the threads that cause the erroneous behavior. Neither fuzzing-based testing techniques nor over-approximate static analyses are well positioned to detect subtle concurrency defects while retaining high accuracy alongside satisfactory coverage. While dynamic analysis techniques have been proposed to overcome some of the challenges in detecting concurrency bugs, we observe that their success is critically dependent on the availability of effective multithreaded clients. Without...

  8. Targeted Client Synthesis for Detecting Concurrency Bugs

    Samak, Malavika
    Detecting concurrency bugs can be challenging due to the intricacies associated with their manifestation. These intricacies correspond to identifying the methods that need to be invoked concurrently, the inputs passed to these methods and the interleaving of the threads that cause the erroneous behavior. Neither fuzzing-based testing techniques nor over-approximate static analyses are well positioned to detect subtle concurrency defects while retaining high accuracy alongside satisfactory coverage. While dynamic analysis techniques have been proposed to overcome some of the challenges in detecting concurrency bugs, we observe that their success is critically dependent on the availability of effective multithreaded clients. Without...

  9. A Case for Protecting Huge Pages from the Kernel

    Patel, Naman
    Modern architectures support multiple size pages to facilitate applications that use large chunks of contiguous memory either for buffer allocation, application specific memory management, in-memory caching or garbage collection. Most general purpose processors support larger page sizes, for e.g. x86 architecture supports 2MB and 1GB pages while PowerPC architecture supports 64KB, 16MB, 16GB pages. Such larger size pages are also known as superpages or huge pages. With the help of huge pages TLB reach can be increased significantly. The Linux kernel can transparently use these huge pages to significantly bring down the cost of TLB translations. With Transparent Huge Pages...

  10. A Case for Protecting Huge Pages from the Kernel

    Patel, Naman
    Modern architectures support multiple size pages to facilitate applications that use large chunks of contiguous memory either for buffer allocation, application specific memory management, in-memory caching or garbage collection. Most general purpose processors support larger page sizes, for e.g. x86 architecture supports 2MB and 1GB pages while PowerPC architecture supports 64KB, 16MB, 16GB pages. Such larger size pages are also known as superpages or huge pages. With the help of huge pages TLB reach can be increased significantly. The Linux kernel can transparently use these huge pages to significantly bring down the cost of TLB translations. With Transparent Huge Pages...

  11. Resolving the Complexity of Some Fundamental Problems in Computational Social Choice

    Dey, Palash
    In many real world situations, especially involving multiagent systems and artificial intelligence, participating agents often need to agree upon a common alternative even if they have differing preferences over the available alternatives. Voting is one of the tools of choice in these situations. Common and classic applications of voting in modern applications include collaborative filtering and recommender systems, metasearch engines, coordination and planning among multiple automated agents etc. Agents in these applications usually have computational power at their disposal. This makes the study of computational aspects of voting crucial. This thesis is devoted to a study of computational complexity of...

  12. Identifying Method Memoization Opportunities in Java Programs

    Chugh, Pallavi
    Memorization of a method is a commonly used re-factoring wherein developer modules the code of a method to save return values for some or all incoming parameter values. Whenever a parameter-tuple is received for the second or subsequent time, the method's execution can be elided and the corresponding saved value can be returned. It is quite challenging for developers to identify suitable methods for memorization, as these may not necessarily be the methods that account for a high fraction of the running time in the program. What are really sought are the methods that cumulatively incur signi_cant execution time in...

  13. Identifying Method Memoization Opportunities in Java Programs

    Chugh, Pallavi
    Memorization of a method is a commonly used re-factoring wherein developer modules the code of a method to save return values for some or all incoming parameter values. Whenever a parameter-tuple is received for the second or subsequent time, the method's execution can be elided and the corresponding saved value can be returned. It is quite challenging for developers to identify suitable methods for memorization, as these may not necessarily be the methods that account for a high fraction of the running time in the program. What are really sought are the methods that cumulatively incur signi_cant execution time in...

  14. Delaunay Graphs for Various Geometric Objects

    Agrawal, Akanksha
    Given a set of n points P ⊂ R2, the Delaunay graph of P for a family of geometric objects C is a graph defined as follows: the vertex set is P and two points p, p' ∈ P are connected by an edge if and only if there exists some C ∈ C containing p, p' but no other point of P. Delaunay graph of circle is often called as Delaunay triangulation as each of its inner face is a triangle if no three points are co-linear and no four points are co-circular. The dual of the Delaunay triangulation...

  15. Learning with Complex Performance Measures : Theory, Algorithms and Applications

    Narasimhan, Harikrishna
    We consider supervised learning problems, where one is given objects with labels, and the goal is to learn a model that can make accurate predictions on new objects. These problems abound in applications, ranging from medical diagnosis to information retrieval to computer vision. Examples include binary or multiclass classi cation, where the goal is to learn a model that can classify objects into two or more categories (e.g. categorizing emails into spam or non-spam); bipartite ranking, where the goal is to learn a model that can rank relevant objects above the irrelevant ones (e.g. ranking documents by relevance to a...

  16. Learning with Complex Performance Measures : Theory, Algorithms and Applications

    Narasimhan, Harikrishna
    We consider supervised learning problems, where one is given objects with labels, and the goal is to learn a model that can make accurate predictions on new objects. These problems abound in applications, ranging from medical diagnosis to information retrieval to computer vision. Examples include binary or multiclass classi cation, where the goal is to learn a model that can classify objects into two or more categories (e.g. categorizing emails into spam or non-spam); bipartite ranking, where the goal is to learn a model that can rank relevant objects above the irrelevant ones (e.g. ranking documents by relevance to a...

  17. Hitting and Piercing Geometric Objects Induced by a Point Set

    Rajgopal, Ninad

  18. Machine Learning and Rank Aggregation Methods for Gene Prioritization from Heterogeneous Data Sources

    Laha, Anirban
    Gene prioritization involves ranking genes by possible relevance to a disease of interest. This is important in order to narrow down the set of genes to be investigated biologically, and over the years, several computational approaches have been proposed for automat-ically prioritizing genes using some form of gene-related data, mostly using statistical or machine learning methods. Recently, Agarwal and Sengupta (2009) proposed the use of learning-to-rank methods, which have been used extensively in information retrieval and related fields, to learn a ranking of genes from a given data source, and used this approach to successfully identify novel genes related to...

  19. Variants of Hegselmann-Krause Model

    Shiragur, Kirankumar Shivanand
    The Hegselmann-Krause system (HK system for short) is one of the most popular models for the dynamics of opinion formation in multi agent systems. Agents are modeled as points in opinion space, and at every time step, each agent moves to the mass center of all the agents within unit distance. The rate of convergence of HK systems has been the subject of several recent works and the current best bounds are O(n3) in one dimension and O(n4) in higher dimension where n being the number of agents. In this work, we investigate the convergence behavior of a few natural...

  20. Variants of Hegselmann-Krause Model

    Shiragur, Kirankumar Shivanand
    The Hegselmann-Krause system (HK system for short) is one of the most popular models for the dynamics of opinion formation in multi agent systems. Agents are modeled as points in opinion space, and at every time step, each agent moves to the mass center of all the agents within unit distance. The rate of convergence of HK systems has been the subject of several recent works and the current best bounds are O(n3) in one dimension and O(n4) in higher dimension where n being the number of agents. In this work, we investigate the convergence behavior of a few natural...

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