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Reliable on-chip power delivery is a challenging design task for sub-100nm and below VLSI technologies as voltage IR drops become more and more pronounced. This situation gets worse as technology continues to scale down. And efficient verification of power integrity becomes critical for design closure. In addition, the increasing process-induced variability makes it even worse for reliable power delivery networks. The process induced variations manifest themselves at different levels (wafer level, die-level and within a die) and they are caused by different sources (lithograph, materials, aging, etc.). In this dissertation, for power delivery networks without considering process variations, we propose an efficient simulation approach, called ETBR (Extended Truncated Balanced Realization), which uses MOR (Model Order Reduction) to speedup the simulation. To make ETBR more accuracy, we further introduce an error control mechanism into it. For power delivery networks with considering process variations, we propose varETBR (variational Extended Truncated Balanced Realization), a reduced Monte-Carlo simulation approach, which can handle a large number of variables and different variation distributions. To further speedup the MOR process used in the fast simulation, a hierarchical Krylov subspace projection based MOR approach, hiePrimor, is proposed.
Integrated System-Level Modeling of Network-on-Chip Enabled Multi-Processor Platforms first gives a comprehensive update on recent developments in the area of SoC platforms and ESL design methodologies. The main contribution is the rigorous definition of a framework for modeling at the timing approximate level of abstraction. Subsequently this book presents a set of tools for the creation and exploration of timing approximate SoC platform models.
Modeling Microprocessor Performance focuses on the development of a design and evaluation tool, named RIPE (Rensselaer Interconnect Performance Estimator). This tool analyzes the impact on wireability, clock frequency, power dissipation, and the reliability of single chip CMOS microprocessors as a function of interconnect, device, circuit, design and architectural parameters. It can accurately predict the overall performance of existing microprocessor systems. For the three major microprocessor architectures, DEC, PowerPC and Intel, the results have shown agreement within 10% on key parameters. The models cover a broad range of issues that relate to the implementation and performance of single chip CMOS microprocessors. The book contains a detailed discussion of the various models and the underlying assumptions based on actual design practices. As such, RIPE and its models provide an insightful tool into single chip microprocessor design and its performance aspects. At the same time, it provides design and process engineers with the capability to model, evaluate, compare and optimize single chip microprocessor systems using advanced technology and design techniques at an early design stage without costly and time consuming implementation. RIPE and its models demonstrate the factors which must be considered when estimating tradeoffs in device and interconnect technology and architecture design on microprocessor performance.
A Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 2 covers application-specific MPSoC design, including compilers and architecture exploration. This second volume describes optimization methods, tools to optimize and port specific applications on MPSoC architectures. Details on compilation, power consumption and wireless communication are also presented, as well as examples of modeling frameworks and CAD tools. Explanations of specific platforms for automotive and real-time computing are also included.
This book constitutes the refereed proceedings of the 21st International Conference on Integrated Circuit and System Design, PATMOS 2011, held in Madrid, Spain, in September 2011. The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The paper feature emerging challenges in methodologies and tools for the design of upcoming generations of integrated circuits and systems and focus especially on timing, performance and power consumption as well as architectural aspects with particular emphasis on modeling, design, characterization, analysis and optimization.
Conventional on-chip communication design mostly use ad-hoc approaches that fail to meet the challenges posed by the next-generation MultiCore Systems on-chip (MCSoC) designs. These major challenges include wiring delay, predictability, diverse interconnection architectures, and power dissipation. A Network-on-Chip (NoC) paradigm is emerging as the solution for the problems of interconnecting dozens of cores into a single system on-chip. However, there are many problems associated with the design of such systems. These problems arise from non-scalable global wire delays, failure to achieve global synchronization, and difficulties associated with non-scalable bus-based functional interconnects. The book consists of three parts, with each part being subdivided into four chapters. The first part deals with design and methodology issues. The architectures used in conventional methods of MCSoCs design and custom multiprocessor architectures are not flexible enough to meet the requirements of different application domains and not scalable enough to meet different computation needs and different complexities of various applications. Several chapters of the first part will emphasize on the design techniques and methodologies. The second part covers the most critical part of MCSoCs design — the interconnections. One approach to addressing the design methodologies is to adopt the so-called reusability feature to boost design productivity. In the past years, the primitive design units evolved from transistors to gates, finite state machines, and processor cores. The network-on-chip paradigm offers this attractive property for the future and will be able to close the productivity gap. The last part of this book delves into MCSoCs validations and optimizations. A more qualitative approach of system validation is based on the use of formal techniques for hardware design. The main advantage of formal methods is the possibility to prove the validity of essential design requirements. As formal languages have a mathematical foundation, it is possible to formally extract and verify these desired properties of the complete abstract state space. Online testing techniques for identifying faults that can lead to system failure are also surveyed. Emphasis is given to analytical redundancy-based techniques that have been developed for fault detection and isolation in the automatic control area.
System on chips designs have evolved from fairly simple unicore, single memory designs to complex heterogeneous multicore SoC architectures consisting of a large number of IP blocks on the same silicon. To meet high computational demands posed by latest consumer electronic devices, most current systems are based on such paradigm, which represents a real revolution in many aspects in computing. The attraction of multicore processing for power reduction is compelling. By splitting a set of tasks among multiple processor cores, the operating frequency necessary for each core can be reduced, allowing to reduce the voltage on each core. Because dynamic power is proportional to the frequency and to the square of the voltage, we get a big gain, even though we may have more cores running. As more and more cores are integrated into these designs to share the ever increasing processing load, the main challenges lie in efficient memory hierarchy, scalable system interconnect, new programming paradigms, and efficient integration methodology for connecting such heterogeneous cores into a single system capable of leveraging their individual flexibility. Current design methods tend toward mixed HW/SW co-designs targeting multicore systems on-chip for specific applications. To decide on the lowest cost mix of cores, designers must iteratively map the device’s functionality to a particular HW/SW partition and target architectures. In addition, to connect the heterogeneous cores, the architecture requires high performance complex communication architectures and efficient communication protocols, such as hierarchical bus, point-to-point connection, or Network-on-Chip. Software development also becomes far more complex due to the difficulties in breaking a single processing task into multiple parts that can be processed separately and then reassembled later. This reflects the fact that certain processor jobs cannot be easily parallelized to run concurrently on multiple processing cores and that load balancing between processing cores – especially heterogeneous cores – is very difficult.
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
A Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 1 covers the key components of MPSoC: processors, memory, interconnect and interfaces. It describes advance features of these components and technologies to build efficient MPSoC architectures. All the main components are detailed: use of memory and their technology, communication support and consistency, and specific processor architectures for general purposes or for dedicated applications.