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Multithreaded architectures now appear across the entire range of computing devices, from the highest-performing general purpose devices to low-end embedded processors. Multithreading enables a processor core to more effectively utilize its computational resources, as a stall in one thread need not cause execution resources to be idle. This enables the computer architect to maximize performance within area constraints, power constraints, or energy constraints. However, the architectural options for the processor designer or architect looking to implement multithreading are quite extensive and varied, as evidenced not only by the research literature but also by the variety of commercial implementations. This book introduces the basic concepts of multithreading, describes a number of models of multithreading, and then develops the three classic models (coarse-grain, fine-grain, and simultaneous multithreading) in greater detail. It describes a wide variety of architectural and software design tradeoffs, as well as opportunities specific to multithreading architectures. Finally, it details a number of important commercial and academic hardware implementations of multithreading. Table of Contents: Introduction / Multithreaded Execution Models / Coarse-Grain Multithreading / Fine-Grain Multithreading / Simultaneous Multithreading / Managing Contention / New Opportunities for Multithreaded Processors / Experimentation and Metrics / Implementations of Multithreaded Processors / Conclusion
Multithreaded computer architecture has emerged as one of the most promising and exciting avenues for the exploitation of parallelism. This new field represents the confluence of several independent research directions which have united over a common set of issues and techniques. Multithreading draws on recent advances in dataflow, RISC, compiling for fine-grained parallel execution, and dynamic resource management. It offers the hope of dramatic performance increases through parallel execution for a broad spectrum of significant applications based on extensions to `traditional' approaches. Multithreaded Computer Architecture is divided into four parts, reflecting four major perspectives on the topic. Part I provides the reader with basic background information, definitions, and surveys of work which have in one way or another been pivotal in defining and shaping multithreading as an architectural discipline. Part II examines key elements of multithreading, highlighting the fundamental nature of latency and synchronization. This section presents clever techniques for hiding latency and supporting large synchronization name spaces. Part III looks at three major multithreaded systems, considering issues of machine organization and compilation strategy. Part IV concludes the volume with an analysis of multithreaded architectures, showcasing methodologies and actual measurements. Multithreaded Computer Architecture: A Summary of the State of the Art is an excellent reference source and may be used as a text for advanced courses on the subject.
Chip multiprocessors - also called multi-core microprocessors or CMPs for short - are now the only way to build high-performance microprocessors, for a variety of reasons. Large uniprocessors are no longer scaling in performance, because it is only possible to extract a limited amount of parallelism from a typical instruction stream using conventional superscalar instruction issue techniques. In addition, one cannot simply ratchet up the clock speed on today's processors, or the power dissipation will become prohibitive in all but water-cooled systems. Compounding these problems is the simple fact that with the immense numbers of transistors available on today's microprocessor chips, it is too costly to design and debug ever-larger processors every year or two. CMPs avoid these problems by filling up a processor die with multiple, relatively simpler processor cores instead of just one huge core. The exact size of a CMP's cores can vary from very simple pipelines to moderately complex superscalar processors, but once a core has been selected the CMP's performance can easily scale across silicon process generations simply by stamping down more copies of the hard-to-design, high-speed processor core in each successive chip generation. In addition, parallel code execution, obtained by spreading multiple threads of execution across the various cores, can achieve significantly higher performance than would be possible using only a single core. While parallel threads are already common in many useful workloads, there are still important workloads that are hard to divide into parallel threads. The low inter-processor communication latency between the cores in a CMP helps make a much wider range of applications viable candidates for parallel execution than was possible with conventional, multi-chip multiprocessors; nevertheless, limited parallelism in key applications is the main factor limiting acceptance of CMPs in some types of systems. After a discussion of the basic pros and cons of CMPs when they are compared with conventional uniprocessors, this book examines how CMPs can best be designed to handle two radically different kinds of workloads that are likely to be used with a CMP: highly parallel, throughput-sensitive applications at one end of the spectrum, and less parallel, latency-sensitive applications at the other. Throughput-sensitive applications, such as server workloads that handle many independent transactions at once, require careful balancing of all parts of a CMP that can limit throughput, such as the individual cores, on-chip cache memory, and off-chip memory interfaces. Several studies and example systems, such as the Sun Niagara, that examine the necessary tradeoffs are presented here. In contrast, latency-sensitive applications - many desktop applications fall into this category - require a focus on reducing inter-core communication latency and applying techniques to help programmers divide their programs into multiple threads as easily as possible. This book discusses many techniques that can be used in CMPs to simplify parallel programming, with an emphasis on research directions proposed at Stanford University. To illustrate the advantages possible with a CMP using a couple of solid examples, extra focus is given to thread-level speculation (TLS), a way to automatically break up nominally sequential applications into parallel threads on a CMP, and transactional memory. This model can greatly simplify manual parallel programming by using hardware - instead of conventional software locks - to enforce atomic code execution of blocks of instructions, a technique that makes parallel coding much less error-prone. Contents: The Case for CMPs / Improving Throughput / Improving Latency Automatically / Improving Latency using Manual Parallel Programming / A Multicore World: The Future of CMPs
This book constitutes the refereed proceedings of the 7th International Conference on High Performance Computing, HiPC 2000, held in Bangalore, India in December 2000. The 46 revised papers presented together with five invited contributions were carefully reviewed and selected from a total of 127 submissions. The papers are organized in topical sections on system software, algorithms, high-performance middleware, applications, cluster computing, architecture, applied parallel processing, networks, wireless and mobile communication systems, and large scale data mining.
Chip multiprocessors - also called multi-core microprocessors or CMPs for short - are now the only way to build high-performance microprocessors, for a variety of reasons. Large uniprocessors are no longer scaling in performance, because it is only possible to extract a limited amount of parallelism from a typical instruction stream using conventional superscalar instruction issue techniques. In addition, one cannot simply ratchet up the clock speed on today's processors, or the power dissipation will become prohibitive in all but water-cooled systems. After a discussion of the basic pros and cons of CMPs when they are compared with conventional uniprocessors, this book examines how CMPs can best be designed to handle two radically different kinds of workloads that are likely to be used with a CMP: highly parallel, throughput-sensitive applications at one end of the spectrum, and less parallel, latency-sensitive applications at the other. Throughput-sensitive applications, such as server workloads that handle many independent transactions at once, require careful balancing of all parts of a CMP that can limit throughput, such as the individual cores, on-chip cache memory, and off-chip memory interfaces. Several studies and example systems, such as the Sun Niagara, that examine the necessary tradeoffs are presented here. In contrast, latency-sensitive applications - many desktop applications fall into this category - require a focus on reducing inter-core communication latency and applying techniques to help programmers divide their programs into multiple threads as easily as possible. This book discusses many techniques that can be used in CMPs to simplify parallel programming, with an emphasis on research directions proposed at Stanford University. To illustrate the advantages possible with a CMP using a couple of solid examples, extra focus is given to thread-level speculation (TLS), a way to automatically break up nominally sequential applications into parallel threads on a CMP, and transactional memory. This model can greatly simplify manual parallel programming by using hardware - instead of conventional software locks - to enforce atomic code execution of blocks of instructions, a technique that makes parallel coding much less error-prone. Book jacket.
Informatics - 10 Years Back, 10 Years Ahead presents a unique collection of expository papers on major current issues in the field of computer science and information technology. The 26 contributions written by leading researchers on personal invitation assess the state of the art of the field by looking back over the past decade, presenting important results, identifying relevant open problems, and developing visions for the decade to come. This book marks two remarkable and festive moments: the 10th anniversary of the International Research and Conference Center for Computer Science in Dagstuhl, Germany and the 2000th volume published in the Lecture Notes in Computer Science series.
This book describes the architecture of microprocessors from simple in-order short pipeline designs to out-of-order superscalars.
There is arguably no field in greater need of a comprehensive handbook than computer engineering. The unparalleled rate of technological advancement, the explosion of computer applications, and the now-in-progress migration to a wireless world have made it difficult for engineers to keep up with all the developments in specialties outside their own
New design architectures in computer systems have surpassed industry expectations. Limits, which were once thought of as fundamental, have now been broken. Digital Systems and Applications details these innovations in systems design as well as cutting-edge applications that are emerging to take advantage of the fields increasingly sophisticated capabilities. This book features new chapters on parallelizing iterative heuristics, stream and wireless processors, and lightweight embedded systems. This fundamental text— Provides a clear focus on computer systems, architecture, and applications Takes a top-level view of system organization before moving on to architectural and organizational concepts such as superscalar and vector processor, VLIW architecture, as well as new trends in multithreading and multiprocessing. includes an entire section dedicated to embedded systems and their applications Discusses topics such as digital signal processing applications, circuit implementation aspects, parallel I/O algorithms, and operating systems Concludes with a look at new and future directions in computing Features articles that describe diverse aspects of computer usage and potentials for use Details implementation and performance-enhancing techniques such as branch prediction, register renaming, and virtual memory Includes a section on new directions in computing and their penetration into many new fields and aspects of our daily lives