Sökning: "Deep Neural Network Accelerators"
Visar resultat 1 - 5 av 10 uppsatser innehållade orden Deep Neural Network Accelerators.
1. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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. Deep Learning Model Deployment for Spaceborne Reconfigurable Hardware : A flexible acceleration approach
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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. Deep Neural Networks as SurrogateModels for Fuel Performance Codes
Kandidat-uppsats, Uppsala universitet/Tillämpad kärnfysikSammanfattning : 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. Low-power Implementation of Neural Network Extension for RISC-V CPU
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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. Real-time remote processing enabled by high speed Ethernet
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : 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