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1. 1. Code Synthesis for Heterogeneous Platforms

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

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

   Sammanfattning : 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. LÄS MER

3. 2. Autonomous Navigation in Partially-Known Environment using Nano Drones with AI-based Obstacle Avoidance : A Vision-based Reactive Planning Approach for Autonomous Navigation of Nano Drones

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

   Författare :Mattia Sartori; [2023]
   Nyckelord :Nano Drones; Obstacle Avoidance; Autonomous Exploration; Autonomous Surveillance; Resource-Constrained Drones; Safe Navigation; Reactive Planning; Vision-based Navigation; Nanodrönare; Undvikande av Hinder; Autonom Utforskning; Autonom Övervakning; Resursbegränsade Drönare; Säker Navigering; Reaktiv Planering; Visionsbaserad Navigering;

   Sammanfattning : The adoption of small-size Unmanned Aerial Vehicles (UAVs) in the commercial and professional sectors is rapidly growing. The miniaturisation of sensors and processors, the advancements in connected edge intelligence and the exponential interest in Artificial Intelligence (AI) are boosting the affirmation of autonomous nano-size drones in the Internet of Things (IoT) ecosystem. LÄS MER

4. 3. Mobile Traffic Classification and Multi-Cell Base Station Control for Energy-Efficient 5G Networks

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

   Författare :Cai Tianzhang; [2023]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

5. 4. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks

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

   Författare :Lucas Alava Peña; [2023]
   Nyckelord :Instruction Scheduling; Deep reinforcement Learning; Compilers; Graph Convolutional Networks; Schemaläggning av instruktioner; Deep Reinforcement Learning; kompilatorer; grafkonvolutionella nätverk;

   Sammanfattning : 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. LÄS MER

7. 5. Embedded Software Simulation Method for Multi-Core Environments Using Parallelism

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

   Författare :Joachim Larsson; [2023]
   Nyckelord :Embedded software; linux processes; multi-core simulation; parallelism; Inbyggd mjukvara; linux processer; flerkärnig simulering;

   Sammanfattning : As technology advances, embedded systems become increasingly complex, with embedded software implemented on platforms with many processors running in parallel. Testing such software on hardware might not always be possible and, when possible, can be time-consuming and costly. LÄS MER