High Performance Computer Architecture

This update of the popular book on computer architecture presents design ideas embodied in many high-performance machines and stresses techniques for evaluating them. Stone develops a proper understanding of the design process by treating the various trade-offs that exist in designing choices, and shows how good designs make efficient use of technology.Features Teaches techniques for the design and analysis of high-performance machines Develops students' intuition for design by treating various tradeoffs that exist in design choices Discusses many important topics: RISC architectures, interconnection meshes, Cache coherent and multiprocessors, and Cache Memory. Includes enhanced descriptions of RISC Processors Expands material on Cache Memory Analysis Current technology in RISC with a focused look on super scalar Additional memory models and techniques for doing Cache design New porposals for coherent memory systems in System C parallel processors Both design and thought problems and problems with limiting parameters are provided 0201526883B04062001

Introduction 1. 1 Historical Developments 1 1. 2 Techniques for Improving Performance 2 1. 3 An Architectural Design Example 3 2 Instructions and Addresses 2. 1 Three-address Systems - The CDC 6600 and 7600 7 2. 2 Two-address Systems - The IBM System/360 and /370 10 2. 3 One-address Systems 12 2. 4 Zero-address Systems 15 2. 5 The MU5 Instruction Set 17 2. 6 Comparing Instruction Formats 22 3 Storage Hierarcbies 3. 1 Store Interleaving 26 3. 2 The Atlas Paging System 29 3. 3 IBM Cache Systems 33 3. 4 The MU5 Name Store 37 3. 5 Data Transfers in the MU5 Storage Hierarchy 44 4 Pipelines 4. 1 The MU5 Primary Operand Unit Pipeline 49 4. 2 Arithmetic Pipelines - The TI ASC 62 4. 3 The IBM System/360 Model 91 Common Data Bus 67 5 Instruction Buffering 5. 1 The IBM System/360 Model 195 Instruction Processor 72 5. 2 Instruction Buffering in CDC Computers 77 5. 3 The MU5 Instruction Buffer Unit 82 5. 4 The CRAY-1 Instruction Buffers 87 5. 5 Position of the Control Point 89 6 Parallel Functional Units 6. 1 The CDC 6600 Central Processor 95 6. 2 The CDC 7600 Central Processor 104 6. 3 Performance 110 6 • 4 The CRA Y-1 112 7 Vector Processors 7. 1 Vector Facilities in MU5 126 7. 2 String Operations in MU5 136 7. 3 The CDC Star-100 142 7. 4 The CDC CYBER 205 146 7.

Datacenter networks provide the communication substrate for large parallel computer systems that form the ecosystem for high performance computing (HPC) systems and modern Internet applications. The design of new datacenter networks is motivated by an array of applications ranging from communication intensive climatology, complex material simulations and molecular dynamics to such Internet applications as Web search, language translation, collaborative Internet applications, streaming video and voice-over-IP. For both Supercomputing and Cloud Computing the network enables distributed applications to communicate and interoperate in an orchestrated and efficient way. This book describes the design and engineering tradeoffs of datacenter networks. It describes interconnection networks from topology and network architecture to routing algorithms, and presents opportunities for taking advantage of the emerging technology trends that are influencing router microarchitecture. With the emergence of "many-core" processor chips, it is evident that we will also need "many-port" routing chips to provide a bandwidth-rich network to avoid the performance limiting effects of Amdahl's Law. We provide an overview of conventional topologies and their routing algorithms and show how technology, signaling rates and cost-effective optics are motivating new network topologies that scale up to millions of hosts. The book also provides detailed case studies of two high performance parallel computer systems and their networks. Table of Contents: Introduction / Background / Topology Basics / High-Radix Topologies / Routing / Scalable Switch Microarchitecture / System Packaging / Case Studies / Closing Remarks

Until now, there were few textbooks that focused on the dynamic subject of speculative execution, a topic that is crucial to the development of high performance computer architectures. Speculative Execution in High Performance Computer Architectures describes many recent advances in speculative execution techniques. It covers cutting-edge research

An authoritative guide to today's revolution in "commodity supercomputing, " this book brings together more than 100 of the field's leading practitioners, providing a single source for up-to-the-minute information on virtually every key system issue associated with high-performance cluster computing.

This book describes how we can design and make efficient processors for high-performance computing, AI, and data science. Although there are many textbooks on the design of processors we do not have a widely accepted definition of the efficiency of a general-purpose computer architecture. Without a definition of the efficiency, it is difficult to make scientific approach to the processor design. In this book, a clear definition of efficiency is given and thus a scientific approach for processor design is made possible. In chapter 2, the history of the development of high-performance processor is overviewed, to discuss what quantity we can use to measure the efficiency of these processors. The proposed quantity is the ratio between the minimum possible energy consumption and the actual energy consumption for a given application using a given semiconductor technology. In chapter 3, whether or not this quantity can be used in practice is discussed, for many real-world applications. In chapter 4, general-purpose processors in the past and present are discussed from this viewpoint. In chapter 5, how we can actually design processors with near-optimal efficiencies is described, and in chapter 6 how we can program such processors. This book gives a new way to look at the field of the design of high-performance processors.

Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author