Computer Memory and Data Storage presents a comprehensive exploration of the intricacies of memory design, delving into the challenges and advanced techniques involved in optimizing power consumption, performance, reliability, and data integrity. The chapters provide a complete understanding of modern memory technologies, ranging from radiation-hardened memory for space applications to diverse memory designs and their trade-offs.
The superabundance of data that is created by today's businesses is making storage a strategic investment priority for companies of all sizes. As storage takes precedence, the following major initiatives emerge: Flatten and converge your network: IBM® takes an open, standards-based approach to implement the latest advances in the flat, converged data center network designs of today. IBM Storage solutions enable clients to deploy a high-speed, low-latency Unified Fabric Architecture. Optimize and automate virtualization: Advanced virtualization awareness reduces the cost and complexity of deploying physical and virtual data center infrastructure. Simplify management: IBM data center networks are easy to deploy, maintain, scale, and virtualize, delivering the foundation of consolidated operations for dynamic infrastructure management. Storage is no longer an afterthought. Too much is at stake. Companies are searching for more ways to efficiently manage expanding volumes of data, and to make that data accessible throughout the enterprise. This demand is propelling the move of storage into the network. Also, the increasing complexity of managing large numbers of storage devices and vast amounts of data is driving greater business value into software and services. With current estimates of the amount of data to be managed and made available increasing at 60% each year, this outlook is where a storage area network (SAN) enters the arena. SANs are the leading storage infrastructure for the global economy of today. SANs offer simplified storage management, scalability, flexibility, and availability; and improved data access, movement, and backup. Welcome to the cognitive era. The smarter data center with the improved economics of IT can be achieved by connecting servers and storage with a high-speed and intelligent network fabric. A smarter data center that hosts IBM Storage solutions can provide an environment that is smarter, faster, greener, open, and easy to manage. This IBM® Redbooks® publication provides an introduction to SAN and Ethernet networking, and how these networks help to achieve a smarter data center. This book is intended for people who are not very familiar with IT, or who are just starting out in the IT world.
Memory Mass Storage describes the fundamental storage technologies, like Semiconductor, Magnetic, Optical and Uncommon, detailing the main technical characteristics of the storage devices. It deals not only with semiconductor and hard disk memory, but also with different ways to manufacture and assembly them, and with their application to meet market requirements. It also provides an introduction to the epistemological issues arising in defining the process of remembering, as well as an overview on human memory, and an interesting excursus about biological memories and their organization, to better understand how the best memory we have, our brain, is able to imagine and design memory.
In today’s workplace, computer and cybersecurity professionals must understand both hardware and software to deploy effective security solutions. This book introduces readers to the fundamentals of computer architecture and organization for security, and provides them with both theoretical and practical solutions to design and implement secure computer systems. Offering an in-depth and innovative introduction to modern computer systems and patent-pending technologies in computer security, the text integrates design considerations with hands-on lessons learned to help practitioners design computer systems that are immune from attacks. Studying computer architecture and organization from a security perspective is a new area. There are many books on computer architectures and many others on computer security. However, books introducing computer architecture and organization with security as the main focus are still rare. This book addresses not only how to secure computer components (CPU, Memory, I/O, and network) but also how to secure data and the computer system as a whole. It also incorporates experiences from the author’s recent award-winning teaching and research. The book also introduces the latest technologies, such as trusted computing, RISC-V, QEMU, cache security, virtualization, cloud computing, IoT, and quantum computing, as well as other advanced computing topics into the classroom in order to close the gap in workforce development. The book is chiefly intended for undergraduate and graduate students in computer architecture and computer organization, as well as engineers, researchers, cybersecurity professionals, and middleware designers.
Computer Programming and IT: For RTU is a student-friendly, practical and example-driven book gives students a solid foundation in the basics of computer programming and information technology. The contents have been tailored to exactly correspond with the requirements of the core course, Computer Programming and IT, offered to the students of Rajasthan Technical University during their first semester. A rich collection of solved examples and chapters mapped to the university syllabus make this book indispensable for students.
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer
In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. This book provides the technical foundation for processing combined transactional and analytical operations in the same database. In the year since we published the first edition of this book, the performance gains enabled by the use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes.
Describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.
When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
Is your memory hierarchy stopping your microprocessor from performing at the high level it should be? Memory Systems: Cache, DRAM, Disk shows you how to resolve this problem. The book tells you everything you need to know about the logical design and operation, physical design and operation, performance characteristics and resulting design trade-offs, and the energy consumption of modern memory hierarchies. You learn how to to tackle the challenging optimization problems that result from the side-effects that can appear at any point in the entire hierarchy.As a result you will be able to design and emulate the entire memory hierarchy. - Understand all levels of the system hierarchy -Xcache, DRAM, and disk. - Evaluate the system-level effects of all design choices. - Model performance and energy consumption for each component in the memory hierarchy.
