Sökning: "Deep Neural Network Accelerators"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Deep Neural Network Accelerators.

  1. 1. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

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

    Författare :Jiayi Feng; [2023]
    Nyckelord :DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

    Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER

  2. 2. Deep Learning Model Deployment for Spaceborne Reconfigurable Hardware : A flexible acceleration approach

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

    Författare :Javier Ferre Martin; [2023]
    Nyckelord :Space Situational Awareness; Deep Learning; Convolutional Neural Networks; FieldProgrammable Gate Arrays; System-On-Chip; Computer Vision; Dynamic Partial Reconfiguration; High-Level Synthesis; Rymdsituationstänksamhet; Djupinlärning; Konvolutionsnätverk; Omkonfigurerbara Field-Programmable Gate Arrays FPGAs ; System-On-Chip SoC ; Datorseende; Dynamisk partiell omkonfigurering; Högnivåsyntes.;

    Sammanfattning : Space debris and space situational awareness (SSA) have become growing concerns for national security and the sustainability of space operations, where timely detection and tracking of space objects is critical in preventing collision events. Traditional computer-vision algorithms have been used extensively to solve detection and tracking problems in flight, but recently deep learning approaches have seen widespread adoption in non-space related applications for their high accuracy. LÄS MER

  3. 3. Deep Neural Networks as SurrogateModels for Fuel Performance Codes

    Kandidat-uppsats, Uppsala universitet/Tillämpad kärnfysik

    Författare :Wenhan Zhou; [2023]
    Nyckelord :Transuranus; AI; Nuclear Fuel Rods;

    Sammanfattning : The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. LÄS MER

  4. 4. Low-power Implementation of Neural Network Extension for RISC-V CPU

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

    Författare :Dario Lo Presti Costantino; [2023]
    Nyckelord :Artificial intelligence; Deep learning; Neural networks; Edge computing; Convolutional neural networks; Low-power electronics; RISC-V; AI accelerators; Parallel processing; Artificiell intelligens; Deep learning; Neurala nätverk; Edge computing; konvolutionella neurala nätverk; Lågeffektelektronik; RISC-V; AI-acceleratorer; Parallell bearbetning;

    Sammanfattning : Deep Learning and Neural Networks have been studied and developed for many years as of today, but there is still a great need of research on this field, because the industry needs are rapidly changing. The new challenge in this field is called edge inference and it is the deployment of Deep Learning on small, simple and cheap devices, such as low-power microcontrollers. LÄS MER

  5. 5. Real-time remote processing enabled by high speed Ethernet

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

    Författare :Dumitra Iancu; Lina Tinnerberg; [2023]
    Nyckelord :Large Intelligent Surfaces; Deep Neural Networks; FPGA; VHDL; Ethernet; Technology and Engineering;

    Sammanfattning : A growing trend within the technologies acting as enablers for 6g, such as Massive MIMO and Large Intelligence Surfaces, is benefiting from both the communication and the positioning aspects that they can provide. As these kinds of systems are employing a large number of arrays which provide high amounts of data, a distributed hardware approach having near-antenna processing is explored in this work. LÄS MER