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Filtering by: Creator Chen, Chi-Shen Remove constraint Creator: Chen, Chi-Shen Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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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:
    Chen Machine learning applied to computer architecture has rapidly transitioned from a theoretical

  • A Distributed Scheme for Accelerating and Scaling PSPNet

    Creator:
    Krishna, Ajay
    Abstract:
    Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
    Resource Type:
    Masters Thesis
    Full Text:
    Accelerating and Scaling PSPNet Abstract approved: Lizhong Chen Advances in deep learning based image

  • Improving Peak Power Shaving in Data Centers using Deep Neural Networks

    Creator:
    Qi, Fang
    Abstract:
    Data centers have been charged a great amount of electric bill by the power company and demand charge can contribute up to 40% of the electric bill due to the "random" workload. This phenomenon can be avoided by using the existing Uninterrupted Power Supply (UPS) as the assistant power source...
    Resource Type:
    Capstone Project
    Full Text:
    approved: _____________________________________________________ Lizhong Chen Data centers have

  • A case for application-based linear transformers : applied towards text-to-spectrogram

    Creator:
    Agostinelli, Victor
    Abstract:
    Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
    Resource Type:
    Masters Thesis
    Full Text:
    approved: Lizhong Chen Various natural language processing (NLP) tasks necessitate deep models that are

  • Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

    Creator:
    Li, Yunfan
    Abstract:
    The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
    Resource Type:
    Dissertation
    Full Text:
    approved: Lizhong Chen The Machine Learning (ML) algorithms are increasingly explored in varies of

  • 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:
    Learning for Architectural Design Space Exploration and Resource Control Abstract approved: Lizhong Chen

  • Towards Deep Learning Model Portability for Domain-Agnostic Device Fingerprinting

    Creator:
    Gaskin, Jared
    Abstract:
    In recent years, RF (Radio Frequency) device fingerprinting using deep learning has emerged as a method of identifying devices solely by their RF transmissions. Conventional approaches to this type of device fingerprinting are not portable to different domains. That is, if a model for this purpose is trained on data...
    Resource Type:
    Masters Thesis
    Full Text:
    : Bechir Hamdaoui Lizhong Chen In recent years, RF (Radio Frequency) device fingerprinting using deep

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Junkun Chen

  • Micropower incremental analog-to-digital converters

    Creator:
    Chen, Chia-Hung
    Abstract:
    Incremental ADCs (IADCs) have many advantages for low-frequency high-accuracy data conversion—they are easy to multiplex between channels, need simpler digital decimation filter, and allow extended counting with a Nyquist-rate ADC. A single-loop incremental ADC was designed and fabricated in 90 nm for a biosensor interface circuit. It incorporates one integrator,...
    Resource Type:
    Dissertation
    Full Text:
    ______________________________________________________ AN ABSTRACT OF THE THESIS OF Chia-Hung Chen for the degree of

  • Low-power double-sampled delta-sigma modulator for broadband applications

    Creator:
    Shen, Weilun
    Abstract:
    High speed and high resolution analog-to-digital converter is a key building block for broadband wireless communications, high definition video applications, medical images and so on. By leveraging the down scaling of the latest CMOS technology and the noise shaping properties, delta-sigma (ΔΣ) ADCs are able to achieve wide-band operation and...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Weilun Shen for the degree of Doctor of Philosophy in