Heterogeneity, High Performance Computing, Self-Organization and the Cloud.

• Superior document: Palgrave Studies in Digital Business and Enabling Technologies Series
• Author: Lynn, Theo.
• TeilnehmendeR: Morrison, John P.; Kenny, David.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2018.; ©2018.
• Year of Publication: 2018
• Edition: 1st ed.
• Language: English
• Series: Palgrave Studies in Digital Business and Enabling Technologies Series
• Physical Description: 1 online resource (183 pages)

Table of Contents

Intro -- Preface -- Acknowledgements -- Contents -- Notes on Contributors -- List of Abbreviations -- List of Figures -- List of Tables -- Chapter 1: Addressing the Complexity of HPC in the Cloud: Emergence, Self-Organisation, Self-Management, and the Separation of Concerns -- 1.1 Introduction -- 1.2 Cloud Computing -- 1.3 High Performance Computing -- 1.4 HPC and the Cloud -- 1.5 Heterogeneous Computing -- 1.6 Addressing Complexity in the Cloud through Self-* Design Principles -- 1.7 Application Scenarios -- 1.7.1 Oil and Gas Exploration -- 1.7.2 Ray Tracing -- 1.7.3 Genomics -- 1.8 Conclusion -- 1.9 Chapter 1 Related CloudLightning Readings -- References -- Chapter 2: Cloud Architectures and Management Approaches -- 2.1 Introduction -- 2.2 Cloud Architecture -- 2.2.1 Infrastructure Organisation -- 2.2.1.1 The Switch-Centric Model -- 2.2.1.2 The Server-Centric Model -- 2.2.2 The Cloud Management Layer -- 2.2.2.1 OpenStack -- 2.2.2.2 Google Kubernetes -- 2.2.3 The Service Delivery Layer -- 2.3 Transitioning to Heterogeneous Clouds -- 2.3.1 Resource Management -- 2.3.2 Resource Abstraction -- 2.4 The CloudLightning Approach -- 2.4.1 Infrastructure Organisation -- 2.4.2 Hardware Organisation -- 2.4.2.1 Resource Abstraction -- 2.4.3 The Cloud Management Layer -- 2.4.3.1 CL-Resource Discovery -- 2.4.3.2 The CL-Resource Selection -- 2.4.3.3 Resource Acquisition -- 2.4.3.4 Coalition Lifecycle Management -- 2.4.3.5 Self-Organisation Agent -- 2.4.3.6 Classification of vRack Managers -- 2.4.3.7 vRack Manager Activities -- 2.4.4 Service Delivery Model -- 2.4.5 Advanced Architecture Support -- 2.4.5.1 Auto-Scaling -- 2.4.5.2 High Availability -- 2.4.5.3 Data Locality -- 2.4.5.4 Dynamic VPN Creation for Blueprint Service Execution -- 2.5 Conclusion -- 2.6 Chapter 2 Related CloudLightning Readings -- References.

Chapter 3: Self-Organising, Self-Managing Frameworks and Strategies -- 3.1 Introduction -- 3.2 Key Concepts -- 3.3 Augmenting the CloudLightning Architecture -- 3.4 Self-Organisation and Self-Management in CloudLightning Architecture -- 3.4.1 Directed Evolution -- 3.4.1.1 The Goal State -- 3.4.1.2 Cell State -- 3.4.1.3 pRouter State and pSwitch State -- 3.4.1.4 vRM State -- 3.4.1.5 Steering by the Cell -- 3.4.1.6 Steering by the pRouter -- 3.4.1.7 Steering by the pSwitch -- 3.4.2 Self-Management Mechanisms -- 3.4.2.1 Mechanism to Send Metrics from a vRM to pSwitch -- 3.4.2.2 Mechanism to Send Metrics from a pSwitch to pRouter -- 3.4.2.3 Mechanism to Send Metrics from pRouter to Cell -- 3.4.2.4 Mechanism to Send Weights from Cell to pRouters -- 3.4.2.5 Mechanism to Send Weights from pRouters to pSwitches -- 3.4.2.6 Mechanism to Send Weights from pSwitch to vRMs -- 3.4.2.7 A Mechanism in the Cell to Modify Local Behaviour in an Effort to Respond to Impetus Provided by the Directed Evolution and Metrics Coming from Attached pRouters -- 3.4.2.8 A Mechanism in a pRouter to Modify Local Behaviour in an Effort to Respond to Impetus Transmitted by the Cell and Metrics Coming from Attached pSwitches -- 3.4.2.9 A Mechanism in a pSwitch to Modify Local Behaviour in an Effort to Respond to Impetus Transmitted by its pRouter and Metrics Coming from Attached vRMs -- 3.4.2.10 A Mechanism in a vRM to Modify Local Behaviour in an Effort to Respond to Impetus Transmitted by its pSwitch and Metrics Coming from its vRack -- 3.4.2.11 Sample Events that Trigger the Transmission of Metrics at each Level in the Hierarchy -- 3.4.2.12 Sample Events that Trigger the Transmission of Weights at Each Level in the Hierarchy -- 3.4.3 Self-Organisation Mechanisms -- 3.5 CloudLightning SOSM Strategies -- 3.5.1 Self-Management Strategies.

3.5.1.1 An Example Self-Management Scenario -- 3.5.2 Self-Organisation Strategies -- 3.5.2.1 An Example Self-Organisation Scenario -- 3.6 Conclusion -- 3.7 Chapter 3 Related CloudLightning Readings -- Chapter 4: Application Blueprints and Service Description -- 4.1 Introduction -- 4.2 Representative Application Lifecycle and Resource Management Frameworks -- 4.3 CloudLightning Stakeholders and Associated Concerns -- 4.4 The CloudLightning Approach Based on Separation of Concerns -- 4.4.1 CloudLightning Requirements -- 4.4.2 Separation of Concerns -- 4.4.2.1 Application Lifecycle Management -- 4.4.2.2 Resource Lifecycle Management -- 4.5 The CloudLightning Gateway Architecture -- 4.5.1 Gateway Service Architecture -- 4.5.2 Service Decomposition -- 4.5.3 Interaction with the SOSM System -- 4.5.3.1 Resource Discovery -- 4.5.3.2 Resource Release -- 4.6 The CloudLightning Blueprint Extensions -- 4.6.1 CloudLightning Brooklyn Extensions -- 4.6.2 CloudLightning Abstract Blueprint -- 4.6.3 CloudLightning Blueprint -- 4.7 Example of Application Creation and Deployment -- 4.8 Conclusion -- 4.9 Chapter 4 Related CloudLightning Readings -- References -- Chapter 5: Simulating Heterogeneous Clouds at Scale -- 5.1 Introduction -- 5.2 Cloud Simulation Frameworks -- 5.3 CloudLightning Simulator -- 5.3.1 Architecture and Basic Characteristics of the Parallel CloudLightning Simulation Framework -- 5.3.2 SOSM Engine -- 5.3.2.1 Power Consumption Modelling -- CPU Power Models -- Combined CPU-Accelerator Power Models -- 5.3.2.2 Memory, Storage, and Network Modelling -- 5.3.2.3 Application Models -- 5.3.2.4 Execution Models -- 5.4 Experimental Results -- 5.5 Conclusion -- 5.6 Chapter 5 Related CloudLightning Readings -- References -- Chapter 6: Concluding Remarks -- References -- Index.