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This book serves as both a textbook and handbook on the benchmarking of systems and components used as building blocks of modern information and communication technology applications. It provides theoretical and practical foundations as well as an in-depth exploration of modern benchmarks and benchmark development. The book is divided into two parts: foundations and applications. The first part introduces the foundations of benchmarking as a discipline, covering the three fundamental elements of each benchmarking approach: metrics, workloads, and measurement methodology. The second part focuses on different application areas, presenting contributions in specific fields of benchmark development. These contributions address the unique challenges that arise in the conception and development of benchmarks for specific systems or subsystems, and demonstrate how the foundations and concepts in the first part of the book are being used in existing benchmarks. Further, the book presents a number of concrete applications and case studies based on input from leading benchmark developers from consortia such as the Standard Performance Evaluation Corporation (SPEC) and the Transaction Processing Performance Council (TPC). Providing both practical and theoretical foundations, as well as a detailed discussion of modern benchmarks and their development, the book is intended as a handbook for professionals and researchers working in areas related to benchmarking. It offers an up-to-date point of reference for existing work as well as latest results, research challenges, and future research directions. It also can be used as a textbook for graduate and postgraduate students studying any of the many subjects related to benchmarking. While readers are assumed to be familiar with the principles and practices of computer science, as well as software and systems engineering, no specific expertise in any subfield of these disciplines is required.
Peer-to-peer systems are now widely used and have become the focus of attention for many researchers over the past decade. A number of algorithms for decentralized search, content distribution, and media streaming have been developed. This book provides fundamental concepts for the benchmarking of those algorithms in peer-to-peer systems. It also contains a collection of characteristic benchmarking results. The chapters of the book have been organized in three topical sections on: Fundamentals of Benchmarking in P2P Systems; Synthetic Benchmarks for Peer-to-Peer Systems; and Application Benchmarks for Peer-to-Peer Systems. They are preceded by a detailed introduction to the subject.
A comprehensive collection of benchmarks for measuring dependability in hardware-software systems As computer systems have become more complex and mission-critical, it is imperative for systems engineers and researchers to have metrics for a system's dependability, reliability, availability, and serviceability. Dependability benchmarks are useful for guiding development efforts for system providers, acquisition choices of system purchasers, and evaluations of new concepts by researchers in academia and industry. This book gathers together all dependability benchmarks developed to date by industry and academia and explains the various principles and concepts of dependability benchmarking. It collects the expert knowledge of DBench, a research project funded by the European Union, and the IFIP Special Interest Group on Dependability Benchmarking, to shed light on this important area. It also provides a large panorama of examples and recommendations for defining dependability benchmarks. Dependability Benchmarking for Computer Systems includes contributions from a credible mix of industrial and academic sources: IBM, Intel, Microsoft, Sun Microsystems, Critical Software, Carnegie Mellon University, LAAS-CNRS, Technical University of Valencia, University of Coimbra, and University of Illinois. It is an invaluable resource for engineers, researchers, system vendors, system purchasers, computer industry consultants, and system integrators.
This book constitutes the thoroughly refereed proceedings of the 5th International Workshop, PMBS 2014 in New Orleans, LA, USA in November 2014. The 12 full and 2 short papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers cover topics on performance benchmarking and optimization; performance analysis and prediction; and power, energy and checkpointing.
To design and develop capable, dependable, and affordable intelligent systems, their performance must be measurable. Scienti?c methodologies for standardization and benchmarking are crucial for quantitatively evaluating the performance of eme- ing robotic and intelligent systems’ technologies. There is currently no accepted standard for quantitatively measuring the performance of these systems against user-de?ned requirements; and furthermore, there is no consensus on what obj- tive evaluation procedures need to be followed to understand the performance of these systems. The lack of reproducible and repeatable test methods has precluded researchers working towards a common goal from exchanging and communic- ing results, inter-comparing system performance, and leveraging previous work that could otherwise avoid duplication and expedite technology transfer. Currently, this lack of cohesion in the community hinders progress in many domains, such as m- ufacturing, service, healthcare, and security. By providing the research community with access to standardized tools, reference data sets, and open source libraries of solutions, researchers and consumers will be able to evaluate the cost and be- ?ts associated with intelligent systems and associated technologies. In this vein, the edited book volume addresses performance evaluation and metrics for intel- gent systems, in general, while emphasizing the need and solutions for standardized methods. To the knowledge of the editors, there is not a single book on the market that is solely dedicated to the subject of performance evaluation and benchmarking of intelligent systems.
Systems for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are currently separate. The potential of the latest technologies and changes in operational and analytical applications over the last decade have given rise to the unification of these systems, which can be of benefit for both workloads. Research and industry have reacted and prototypes of hybrid database systems are now appearing. Benchmarks are the standard method for evaluating, comparing and supporting the development of new database systems. Because of the separation of OLTP and OLAP systems, existing benchmarks are only focused on one or the other. With the rise of hybrid database systems, benchmarks to assess these systems will be needed as well. Based on the examination of existing benchmarks, a new benchmark for hybrid database systems is introduced in this book. It is furthermore used to determine the effect of adding OLAP to an OLTP workload and is applied to analyze the impact of typically used optimizations in the historically separate OLTP and OLAP domains in mixed-workload scenarios.
Cloud storage services and NoSQL systems typically offer only "Eventual Consistency", a rather weak guarantee covering a broad range of potential data consistency behavior. The degree of actual (in-)consistency, however, is unknown. This work presents novel solutions for determining the degree of (in-)consistency via simulation and benchmarking, as well as the necessary means to resolve inconsistencies leveraging this information.
This book constitutes the refereed proceedings papers from the 8th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems, PMBS 2017, held in Denver, Colorado, USA, in November 2017. The 10 full papers and 3 short papers included in this volume were carefully reviewed and selected from 36 submissions. They were organized in topical sections named: performance evaluation and analysis; performance modeling and simulation; and short papers.