Management And Scheduling Of Accelerators For Heterogeneous High Performance Computing

The use of heterogeneous computing resources, such as graphics processing units or other specialized co-processors, has become widespread in recent years because of their performance and energy efficiency advantages. Operating system approaches that are limited to optimizing CPU usage are no longer sufficient for the efficient utilization of systems that comprise diverse resource types. Enabling task preemption on these architectures and migration of tasks between different resource types at run-time is not only key to improving the performance and energy consumption but also to enabling automatic scheduling methods for heterogeneous compute nodes. This thesis proposes novel techniques for run-time management of heterogeneous resources and enabling tasks to migrate between diverse hardware. It provides fundamental work towards future operating systems by discussing implications, limitations, and chances of the heterogeneity and introducing solutions for energy- and performance-efficient run-time systems. Scheduling methods to utilize heterogeneous systems by the use of a centralized scheduler are presented that show benefits over existing approaches in varying case studies.

This book constitutes the refereed proceedings of the 36th International Conference on High Performance Computing, ISC High Performance 2021, held virtually in June/July 2021. The 24 full papers presented were carefully reviewed and selected from 74 submissions. The papers cover a broad range of topics such as architecture, networks, and storage; machine learning, AI, and emerging technologies; HPC algorithms and applications; performance modeling, evaluation, and analysis; and programming environments and systems software.

This book constitutes the refereed proceedings of the 32nd International Conference, ISC High Performance 2017, held in Frankfurt, Germany, in June 2017. The 22 revised full papers presented in this book were carefully reviewed and selected from 66 submissions. The papers cover the following topics: applications and algorithms; proxy applications; architecture and system optimization; and energy-aware computing.

element of relationships between entities, but, above all, it positively influences the building of an organization's intellectual capital. This capital can be defined in different ways, but its definition always references elements that determine the potential of sustainable organizations, often in human, social, relational, organizational, and innovation dimensions. Trust is increasingly becoming the key determinant of this capital (Kożuch, Lenart-Gansiniec, 2017). Trust also has a number of different definitions. However, the basis of many of these definitions is the building of relationships focused on developing some kind of individual or inter-organizational link. Organizational trust is a complicated concept, and it is the basis of all organized activities performed by people in the organization, largely because trust is needed to develop relationships with integrity and commitment. Thus, it is interesting to study the relationship between trust and the building of the intellectual capital of sustainable organizations. Indeed, intellectual capital plays a special role here. It is a guide and a platform for achieving not only a competitive advantage for the sustainable organization, but also a source of value creation in the short and long term. Thus, this strategic hybrid, composed of a business model, strategy, and business processes, is favorable to the development of intellectual capital (Jabłoński 2017). Trust is an element that ties this capital to relationships in business. Moreover, it has an integrated character (R.C. Mayer, J. H. Davis, F. D. Schoorman 1995). Assuming that, nowadays, the network paradigm is becoming increasingly important, it is worth asking how the mechanism of building trust-based intellectual capital in a sustainable organization functions as its key asset in the network environment.

Hardware acceleration in the form of customized datapath and control circuitry tuned to specific applications has gained popularity for its promise to utilize transistors more efficiently. Historically, the computer architecture community has focused on general-purpose processors, and extensive research infrastructure has been developed to support research efforts in this domain. Envisioning future computing systems with a diverse set of general-purpose cores and accelerators, computer architects must add accelerator-related research infrastructures to their toolboxes to explore future heterogeneous systems. This book serves as a primer for the field, as an overview of the vast literature on accelerator architectures and their design flows, and as a resource guidebook for researchers working in related areas.

This book is open access under a CC BY NC ND license. It addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses.

This book constitutes the refereed proceedings of the 19th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2019, held in Pythagorion, Samos, Greece, in July 2019. The 21 regular papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on system design space exploration; deep learning optimization; system security; multi/many-core scheduling; system energy and heat management; many-core communication; and electronic system-level design and verification. In addition there are 13 papers from three special sessions which were organized on topics of current interest: insights from negative results; machine learning implementations; and European projects.

This volume constitutes the papers of several workshops which were held in conjunction with the 38th International Conference on High Performance Computing, ISC High Performance 2023, held in Hamburg, Germany, during May 21–25, 2023. The 49 revised full papers presented in this book were carefully reviewed and selected from 70 submissions. ISC High Performance 2023 presents the following workshops: ​2nd International Workshop on Malleability Techniques Applications in High-Performance Computing (HPCMALL) 18th Workshop on Virtualization in High-Performance Cloud Computing (VHPC 23) HPC I/O in the Data Center (HPC IODC) Workshop on Converged Computing of Cloud, HPC, and Edge (WOCC’23) 7th International Workshop on In Situ Visualization (WOIV’23) Workshop on Monitoring and Operational Data Analytics (MODA23) 2nd Workshop on Communication, I/O, and Storage at Scale on Next-Generation Platforms: Scalable Infrastructures First International Workshop on RISC-V for HPC Second Combined Workshop on Interactive and Urgent Supercomputing (CWIUS) HPC on Heterogeneous Hardware (H3)