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  • Machine learning for computer architecture design and optimization

    Creator:
    Penney, Drew
    Abstract:
    Machine learning applied to computer architecture has rapidly transitioned from a theoretical novelty to being a driving force behind design, control, and simulation in practically all components. These machine-learning-based methodologies are further notable for their scalability to increasingly complex design challenges, which has allowed these methodologies to surpass the prior...
    Resource Type:
    Dissertation
    Full Text:
    placed increasing burden on architects to supplant technology scaling with architectural advances

  • Machine Learning for Architectural Design Space Exploration and Resource Control

    Creator:
    Penney, Drew D.
    Abstract:
    Machine learning has enabled significant advancements in diverse fields, yet, with a few exceptions, has had limited impact on computer architecture. Recent work, however, has begun to explore broader application to design, optimization, and simulation. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This thesis first...
    Resource Type:
    Masters Thesis
    Full Text:
    advancements in computa- tional capabilities has placed increasing burden on architects to supplant Moore’s

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation
    Full Text:
    ., Waymo LLC., Facebook Reality Lab and Apple Inc. for providing me memorable internship experiences

  • Design and Application of Variational Representations

    Creator:
    Smeltzer, Karl J.
    Abstract:
    Variability is an important and widely studied topic across domains such as version control, software product lines, and metaprogramming. This dissertation presents an investigation into the process of systematically adding variability to data structures and programs, leading to guidelines for variational data structures and implications for programs that create, manipulate,...
    Resource Type:
    Dissertation
    Full Text:
    by a variety of professionals, ranging from architects and industrial designers using CAD tools