Essays about: "network processors"
Showing result 1 - 5 of 61 essays containing the words network processors.
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1. A SYSTEMATIC REVIEW OF ATTRIBUTE-BASED ENCRYPTION FOR SECURE DATA SHARING IN IoT ENVIRONMENT.
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Internet of Things (IoT) refers to a network of global and interrelated computing devices that connects humans and machines. It connects anything that has access to the internet and creates an avenue for data and information exchange. READ MORE
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2. Mobile Traffic Classification and Multi-Cell Base Station Control for Energy-Efficient 5G Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The global energy consumption of mobile networks is rapidly increasing due to the exponential growth of mobile network traffic. The advent of next-generation cellular technologies such as fifth-generation (5G) and beyond promises higher network throughput and lower latency but also demands higher power consumption for its denser base station (BS) deployment and more energy-intensive processors. READ MORE
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3. A General Purpose Near Data Processing Architecture Optimized for Data-intensive Applications
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : In recent years, as Internet of Things (IoT) and machine learning technologies have advanced, there has been increasing interest in the study of energy-efficient and flexible architectures for embedded systems. To bridge the performance gap between microprocessors and memory systems, Near-Data Processing (NDP) was introduced. READ MORE
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4. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : 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. READ MORE
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5. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Instruction Scheduling is a back-end compiler optimisation technique that can provide significant performance gains. It refers to ordering instructions in a particular order to reduce latency for processors with instruction-level parallelism. READ MORE