Sökning: "Neuromorphic Hardware"

Visar resultat 1 - 5 av 15 uppsatser innehållade orden Neuromorphic Hardware.

  1. 1. Applicability of neuromorphic hardware in disease spread simulations : A comparison of a SpiNNaker board and a GPU

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

    Författare :Adam Ekelöf; Eric Sandberg; [2023]
    Nyckelord :;

    Sammanfattning : This research paper investigates whether neuromorphic hardware can outperform the traditional GPU in simulating disease spread. As the era of Moore’s Law draws to a close, researchers are seeking alternative solutions to enhance computational power. LÄS MER

  3. 2. Introducing GA-SSNN: A Method for Optimizing Stochastic Spiking Neural Networks : Scaling the Edge User Allocation Constraint Satisfaction Problem with Enhanced Energy and Time Efficiency

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

    Författare :Nathan Allard; [2023]
    Nyckelord :;

    Sammanfattning : As progress within Von Neumann-based computer architecture is being limited by the physical limits of transistor size, neuromorphic comuting has emerged as a promising area of research. Neuromorphic hardware tends to be substantially more power efficient by imitating the aspects of computations in networks of neurons in the brain. LÄS MER

  4. 3. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Cina Arjmand; [2023]
    Nyckelord :Artifical Intelligence; Machine Learning; Neuromorphic Engineering; Computer Vision; Technology and Engineering;

    Sammanfattning : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. LÄS MER

  5. 4. Evaluation of Ferroelectric Tunnel Junction memristor for in-memory computation in real world use cases

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Alec Guerin; Christos Papadopoulos; [2023]
    Nyckelord :FTJ; Ferroelectric Tunneling Junction; Analog in-memory computing; AIMC; Memristor; A.I.; AIHWKIT; Semantic segmentation; Natural Language Processing; NLP; Neuromorphic Computing; Matrix Vector Multiplication; Technology and Engineering;

    Sammanfattning : Machine learning algorithms are experiencing unprecedented attention, but their inherent computational complexity leads to high energy consumption. However, a paradigm shift in computing methods has the potential to address the issue. LÄS MER

  7. 5. Neuromorphic Medical Image Analysis at the Edge : On-Edge training with the Akida Brainchip

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

    Författare :Ebba Bråtman; Lucas Dow; [2023]
    Nyckelord :;

    Sammanfattning : Computed Tomography (CT) scans play a crucial role in medical imaging, allowing neuroscientists to identify intracranial pathologies such as haemorrhages and malignant tumours in the brain. This thesis explores the potential of deep learning models as an aid in intracranial pathology detection through medical imaging. LÄS MER