Sökning: "resource optimisation"

Visar resultat 1 - 5 av 31 uppsatser innehållade orden resource optimisation.

1. 1. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Jonna Matthiesen; [2023-10-24]
   Nyckelord :Compression; Deep Learning; DNN; Hyperparameters; Optimization; Pruning; Hyperparameter Optimisation; Hyperparameter Tuning;

   Sammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER

3. 2. 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

4. 3. Intelligent autoscaling in Kubernetes : the impact of container performance indicators in model-free DRL methods

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

   Författare :Tommaso Praturlon; [2023]
   Nyckelord :Cloud computing; container autoscaling; resource optimisation; Deep Reinforcement Learning; Actor-Critic; Kubernetes; service mesh; Cloud computing; container autoscaling; Optimering av resurser; Deep Reinforcement Learning; Actor-Critic; Kubernetes; service mesh;

   Sammanfattning : A key challenge in the field of cloud computing is to automatically scale software containers in a way that accurately matches the demand for the services they run. To manage such components, container orchestrator tools such as Kubernetes are employed, and in the past few years, researchers have attempted to optimise its autoscaling mechanism with different approaches. LÄS MER

5. 4. Exploring Circular BESS for the Commercial and Industrial Sector: A customer-centric perspective

   Master-uppsats, Lunds universitet/Internationella miljöinstitutet

   Författare :Luca Schumann; [2023]
   Nyckelord :BESS; Circular Economy; Circularity strategies; Customer journey; Digital enabler; Earth and Environmental Sciences;

   Sammanfattning : In recent years, battery energy storage systems (BESS) have gained prominence as a key technology enabling much needed electricity grid flexibility while simultaneously providing distinct value to its end-users. With the anticipated increase of residual value holding used batteries from mobility applications entering the market, more and more companies are looking to construct BESS offers around these second-life batteries in an attempt to unlock the potential of circular business offers. LÄS MER

7. 5. Performance Evaluation of Kubernetes Autoscaling strategies on GKE clusters

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

   Författare :Johanna Nilsen; [2023]
   Nyckelord :Cloud Computing; Containerisation; Kubernetes; Google Kubernetes Engine; Autoscaling; Horizontal Pod Autoscaling; Vertical Pod Autoscaling; Hybrid Pod Autoscaling; Molntjänster; Containerisering; Kubernetes; Google Kubernetes Engine; Autoskalning; Horisontell Pod-autoskalning; Vertikal Pod-autoskalning; Hybrid Pod-autoskalning;

   Sammanfattning : Cloud computing and containerisation have experienced significant growth in recent years. With cloud providers requiring users to specify resource limits and requests, the need for performance and resource optimisation has emerged in the cloud computing domain. LÄS MER