Tackling the questions that systems designers care about, this book brings queueing theory decisively back to computer science. The book is written with computer scientists and engineers in mind and ...is full of examples from computer systems, as well as manufacturing and operations research. Fun and readable, the book is highly approachable, even for undergraduates, while still being thoroughly rigorous and also covering a much wider span of topics than many queueing books. Readers benefit from a lively mix of motivation and intuition, with illustrations, examples and more than 300 exercises – all while acquiring the skills needed to model, analyze and design large-scale systems with good performance and low cost. The exercises are an important feature, teaching research-level counterintuitive lessons in the design of computer systems. The goal is to train readers not only to customize existing analyses but also to invent their own.
Principles of Model Checking Baier, Christel; Katoen, Joost-Pieter; Larsen, Kim Guldstrand
2008, 2008-06-03
eBook
A comprehensive introduction to the foundations of model checking, a fully automated technique for finding flaws in hardware and software; with extensive examples and both practical and theoretical ...exercises.
Simba Shao, Yakun Sophia; Clemons, Jason; Venkatesan, Rangharajan ...
Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture,
10/2019
Conference Proceeding
Package-level integration using multi-chip-modules (MCMs) is a promising approach for building large-scale systems. Compared to a large monolithic die, an MCM combines many smaller chiplets into a ...larger system, substantially reducing fabrication and design costs. Current MCMs typically only contain a handful of coarse-grained large chiplets due to the high area, performance, and energy overheads associated with inter-chiplet communication. This work investigates and quantifies the costs and benefits of using MCMs with fine-grained chiplets for deep learning inference, an application area with large compute and on-chip storage requirements. To evaluate the approach, we architected, implemented, fabricated, and tested Simba, a 36-chiplet prototype MCM system for deep-learning inference. Each chiplet achieves 4 TOPS peak performance, and the 36-chiplet MCM package achieves up to 128 TOPS and up to 6.1 TOPS/W. The MCM is configurable to support a flexible mapping of DNN layers to the distributed compute and storage units. To mitigate inter-chiplet communication overheads, we introduce three tiling optimizations that improve data locality. These optimizations achieve up to 16% speedup compared to the baseline layer mapping. Our evaluation shows that Simba can process 1988 images/s running ResNet-50 with batch size of one, delivering inference latency of 0.50 ms.
Fault Tolerant Systems Israel Koren, C. Mani Krishna
2007, 2010, 2010-07-19T00:00:00, 2010-07-19, c2007
eBook
There are many applications in which the reliability of the overall system must be far higher than the reliability of its individual components. In such cases, designers devise mechanisms and ...architectures that allow the system to either completely mask the effects of a component failure or recover from it so quickly that the application is not seriously affected. This is the work of fault-tolerant designers and their work is increasingly important and complex not only because of the increasing number of “mission critical” applications, but also because the diminishing reliability of hardware means that even systems for non-critical applications will need to be designed with fault-tolerance in mind. Reflecting the real-world challenges faced by designers of these systems, this book addresses fault tolerance design with a systems approach to both hardware and software. No other text on the market takes this approach, nor offers the comprehensive and up-to-date treatment the authors provide. Students, designers and architects of high performance processors will value this comprehensive overview of the field.
Cyber-Physical Systems Houbing Song, Danda B Rawat, Sabina Jeschke, Christian Brecher / Houbing Song, Danda B. Rawat, Sabina Jeschke, Christian Brecher
2016, 2016-09-11
eBook
Cyber-Physical Systems: Foundations, Principles and Applications explores the core system science perspective needed to design and build complex cyber- physical systems. Using Systems Science's ...underlying theories, such as probability theory, decision theory, game theory, organizational sociology, behavioral economics, and cognitive psychology, the book addresses foundational issues central across CPS applications, including System Design -- How to design CPS to be safe, secure, and resilient in rapidly evolving environments, System Verification -- How to develop effective metrics and methods to verify and certify large and complex CPS, Real-time Control and Adaptation -- How to achieve real-time dynamic control and behavior adaptation in a diverse environments, such as clouds and in network-challenged spaces, Manufacturing -- How to harness communication, computation, and control for developing new products, reducing product concepts to realizable designs, and producing integrated software-hardware systems at a pace far exceeding today's timeline. The book is part of the Intelligent Data-Centric Systems: Sensor- Collected Intelligence series edited by Fatos Xhafa, Technical University of Catalonia. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS * Includes in-depth coverage of the latest models and theories that unify perspectives, expressing the interacting dynamics of the computational and physical components of a system in a dynamic environment * Focuses on new design, analysis, and verification tools that embody the scientific principles of CPS and incorporate measurement, dynamics, and control * Covers applications in numerous sectors, including agriculture, energy, transportation, building design and automation, healthcare, and manufacturing
Empirical studies have become an integral element of software engineering research and practice. This unique text/reference includes chapters from some of the top international empirical software ...engineering researchers and focuses on the practical knowledge necessary for conducting, reporting and using empirical methods in software engineering. Part 1, 'Research Methods and Techniques', examines the proper use of various strategies for collecting and analysing data, and the uses for which those strategies are most appropriate. Part 2, 'Practical Foundations', provides a discussion of several important global issues that need to be considered from the very beginning of research planning. Finally, 'Knowledge Creation' offers insight on using a set of disparate studies to provide useful decision support. Topics and features: - Offers information across a range of techniques, methods, and qualitative and quantitative issues, providing a toolkit for the reader that is applicable across the diversity of software development contexts - Presents reference material with concrete software engineering examples - Provides guidance on how to design, conduct, analyse, interpret and report empirical studies, taking into account the common difficulties and challenges encountered in the field - Arms researchers with the information necessary to avoid fundamental risks - Tackles appropriate techniques for addressing disparate studies - ensuring the relevance of empirical software engineering, and showing its practical impact - Describes methods that are less often used in the field, providing less conventional but still rigorous and useful ways of collecting data - Supplies detailed information on topics (such as surveys) that often contain methodological errors This broad-ranging, practical guide will prove an invaluable and useful reference for practising software engineers and researchers. In addition, it will be suitable for graduate students studying empirical methods in software development. Dr. Forrest Shull is a senior scientist at the Fraunhofer Center for Experimental Software Engineering, Maryland, and the director of its Measurement and Knowledge Management Division. In addition, he serves as associate editor in chief of IEEE Software magazine, specializing in empirical studies. Dr. Janice Singer heads the Human Computer Interaction program at the National Research Council, Canada. She has been conducting empirical research in software engineering for the past 12 years. Dr. Dag Sjøberg is currently research director of the software engineering group of the Simula Research Laboratory, Norway, which is ranked No. 3 in the world (out of 1400 institutions) in an evaluation in 2007 in the area of software and systems engineering.
Fault-tolerant control aims at a graceful degradation of the behaviour of automated systems in case of faults. It satisfies the industrial demand for enhanced availability and safety, in contrast to ...traditional reactions to faults that bring about sudden shutdowns and loss of availability. The book presents effective model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault throught the process, to test the fault detectability and to find the redundancies in the process that can be used to ensure fault tolerance. Design methods for diagnostic systems and fault-tolerant controllers are presented for processes that are described by analytical models, by discrete-event models or that can be dealt with as quantised systems. Five case studies on pilot processes show the applicability of the presented methods. The theoretical results are illustrated by two running examples used throughout the book. The second edition includes new material about reconfigurable control, diagnosis of nonlinear systems, and remote diagnosis. The application examples are extended by a steering-by-wire system and the air path of a diesel engine, both of which include experimental results. The bibliographical notes at the end of all chapters have been up-dated. The chapters end with exercises to be used in lectures.
As societies become increasingly digital, the importance of cyber security has grown significantly for individuals, companies, and nations. The rising number of cyber attacks surpasses the existing ...defense capabilities, partly due to a shortage of skilled cyber security professionals.
Convolutional Neural Networks (CNNs) have emerged as a fundamental technology for machine learning. High performance and extreme energy efficiency are critical for deployments of CNNs, especially in ...mobile platforms such as autonomous vehicles, cameras, and electronic personal assistants. This paper introduces the Sparse CNN (SCNN) accelerator architecture, which improves performance and energy efficiency by exploiting the zero-valued weights that stem from network pruning during training and zero-valued activations that arise from the common ReLU operator. Specifically, SCNN employs a novel dataflow that enables maintaining the sparse weights and activations in a compressed encoding, which eliminates unnecessary data transfers and reduces storage requirements. Furthermore, the SCNN dataflow facilitates efficient delivery of those weights and activations to a multiplier array, where they are extensively reused; product accumulation is performed in a novel accumulator array. On contemporary neural networks, SCNN can improve both performance and energy by a factor of 2.7× and 2.3×, respectively, over a comparably provisioned dense CNN accelerator.
PDF
