Essays about: "hårdvara"

Showing result 1 - 5 of 372 essays containing the word hårdvara.

1. 1. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Khalid El Yaacoub; [2024]
   Keywords : Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Abstract : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. READ MORE

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Jiayi Feng; [2023]
   Keywords : 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;

   Abstract : 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. READ MORE

4. 3. Code Synthesis for Heterogeneous Platforms

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Zhouxiang Fu; [2023]
   Keywords : Code Synthesis; Heterogeneous Platform; Zero-Overhead Topology Infrastructure; Kodsyntes; Heterogen plattform; Zero-Overhead Topologi Infrastruktur;

   Abstract : Heterogeneous platforms, systems with both general-purpose processors and task-specific hardware, are largely used in industry to increase efficiency, but the heterogeneity also increases the difficulty of design and verification. We often need to wait for the completion of all the modules to know whether the functionality of the design is correct or not, which can cause costly and tedious design iteration cycles. READ MORE

5. 4. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

   University essay from KTH/Mekatronik och inbyggda styrsystem

   Author : Helgi Hrafn Björnsson; Jón Kaldal; [2023]
   Keywords : Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

   Abstract : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. READ MORE

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Adam Ekelöf; Eric Sandberg; [2023]
   Keywords : ;

   Abstract : 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. READ MORE