Soft Error Reliability Using Virtual Platforms: Early Evaluation of Multicore Systems - Image 1

£76.13

Springer Soft Error Reliability Using Virtual Platforms: Early Evaluation of Multicore Systems

Name: Soft Error Reliability Using Virtual Platforms: Early Evaluation of Multicore Systems
Brand: Springer
Price: 76.13 GBP
Availability: InStock

Architecture & Microprocessors

Price History & Forecast

Last 4 days • 4 data points

Historical

Generating forecast...

Price Distribution

Price distribution over 4 days • 1 price levels

Days at Price

Price Analysis

Most common price: £76 (4 days, 100.0%)

Price range: £76 - £76

Price levels: 1 different prices over 4 days

Description

This book describes the benefits and drawbacks inherent in the use of virtual platforms (VPs) to perform fast and early soft error assessment of multicore systems. The authors show that VPs provide engineers with appropriate means to investigate new and more efficient fault injection and mitigation techniques. Coverage also includes the use of machine learning techniques (e.g., linear regression) to speed-up the soft error evaluation process by pinpointing parameters (e.g., architectural) with the most substantial impact on the software stack dependability. This book provides valuable information and insight through more than 3 million individual scenarios and 2 million simulation-hours. Further, this book explores machine learning techniques usage to navigate large fault injection datasets.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 3030557065
Category: Books > Subjects > Computing & Internet > Computer Science > Architecture & Microprocessors
Domain: Amazon UK
Release Date: 03 November 2021
Listed Since: 07 October 2021

Barcode

No barcode data available

Springer Soft Error Reliability Using Virtual Platforms: Early Evaluation of Multicore Systems

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Multiprocessor Scheduling for Real-Time Systems (Embedded Systems)

Predictive Analytics in System Reliability (Springer Series in Reliability Engineering)

Software Architectures: Advances and Applications

Dependable Computer Systems: 97 (Advances in Intelligent and Soft Computing, 97)

Quality-of-Service Aware Design and Management of Embedded Mixed-Criticality Systems

Fault Diagnosis for Linear Discrete Time-Varying Systems and Its Applications

Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications: 480 (Studies in Systems, Decision and Control, 480)

Embedded and Real-Time Operating Systems

Advances in Interdisciplinary Research in Engineering and Business Management (Asset Analytics)

Software Failure Risk: Measurement and Management (Applications of Modern Technology in Business)

Ein Verfahren zur Entwicklung flexibler Fahrzeug-Software- und -Hardware-Architekturen unter Unsicherheit

Application-Specific Arithmetic: Computing Just Right for the Reconfigurable Computer and the Dark Silicon Era

Agile Enterprise Engineering: Smart Application of Human Factors: Models, Methods, Practices, Case Studies: 175 (Smart Innovation, Systems and Technologies, 175)

A Concise Introduction to Software Engineering: With Open Source and GenAI (Undergraduate Topics in Computer Science)

Software Engineering for Games in Serious Contexts: Theories, Methods, Tools, and Experiences

Control Charts and Machine Learning for Anomaly Detection in Manufacturing (Springer Series in Reliability Engineering)

Advanced Multicore Systems-On-Chip: Architecture, On-Chip Network, Design

Embedded Machine Learning with Microcontrollers: Applications on STM32 Development Boards

System on Chip (SOC) Architecture: A Practical Approach

Web Engineering: Modelling and Implementing Web Applications: 12 (Human–Computer Interaction Series)

Multi-physical and Non-orthogonal Geotechnical Plasticity Modeling and Algorithms

ERP Systems and Organisational Change: A Socio-technical Insight (Springer Series in Advanced Manufacturing)

Modeling and Simulation in Industrial Engineering (Management and Industrial Engineering)

Machine Learning and Granular Computing: A Synergistic Design Environment (Studies in Big Data)