Sökning: "Distributed deep learning architecture"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Distributed deep learning architecture.

  1. 1. Quality Attributes of Data in Distributed Deep Learning Architectures

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :SHAMEER KUMAR PRADHAN; SAGAR TUNGAL; [2021-09-28]
    Nyckelord :Data quality; Data; Data quality attributes; Data quality challenges; Data quality workflow; Data quality assessment; Data quality maintenance; Design science research; Artifacts; Template; Deep learning; Distributed architecture; Distributed deep learning architecture; Advanced driver assistance systems;

    Sammanfattning : Large volume of data is generated by different systems. Intelligent systems such asautonomous driving uses such large volume of data to train their artificial intelligence models. However, good quality data is one of the foremost needs of any system to function in an effective and safe manner. LÄS MER

  2. 2. Distributed Robust Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Akhil Yerrapragada; [2021]
    Nyckelord :Byzantine resilient decentralized training; Gradient aggregation rules; α; f Byzantine resilience; Fault tolerance; Ring all-reduce.; Byzantinsk motståndskraftig decentraliserad träning; Gradientaggregeringsregler; α; f Byzantinsk motståndskraft; Feltolerans; Ring allreducera.;

    Sammanfattning : Accuracy obtained when training deep learning models with large amounts of data is high, however, training a model with such huge amounts of data on a single node is not feasible due to various reasons. For example, it might not be possible to fit the entire data set in the memory of a single node, training times can significantly increase since the dataset is huge. LÄS MER

  3. 3. Efficient serverless resource scheduling for distributed deep learning.

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Johan Sundkvist; [2021]
    Nyckelord :Serverless; distributed; deep learning; scheduling; regression;

    Sammanfattning : Stemming from the growth and increased complexity of computer vision, natural language processing, and speech recognition algorithms; the need for scalability and fault tolerance of machine learning systems has risen. In order to comply with these demands many have turned their focus towards implementing machine learning on distributed systems. LÄS MER

  4. 4. Comparing a gang-like scheduler with the default Kubernetes scheduler in a multi-tenant serverless distributed deep learning training environment

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Frans-Lukas Lövenvald; [2021]
    Nyckelord :Deep learning; serverless; scheduling;

    Sammanfattning : Systems for running distributed deep learning training on the cloud have recently been developed. An important component of a distributed deep learning job handler is its resource allocation scheduler. This scheduler allocates computing resources to parts of a distributed training architecture. LÄS MER

  5. 5. Investigation and Implementation of Federation Mechanisms of SVP

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Babar Khan; [2020]
    Nyckelord :Bonseyes Marketplace; AI Engineering; Resource Federation; Federation mechanisms; Distributed Secure Virtual Premise;

    Sammanfattning : The development of AI application on the edge devices require integrated data, algorithms, and tools. Big companies like Google and Apple have integrated data, algorithms, and tools for building end to end systems with optimized and dedicated hardware for deep learning applications. LÄS MER