Ranging from low-level application and architecture optimizations to high-level modeling and exploration concerns, this authoritative reference compiles essential research on various levels of abstraction appearing in embedded systems and software design. It promotes platform-based design for improved system implementation and modeling and enhanced
Modern consumers carry many electronic devices, like a mobile phone, digital camera, GPS, PDA and an MP3 player. The functionality of each of these devices has gone through an important evolution over recent years, with a steep increase in both the number of features as in the quality of the services that they provide. However, providing the required compute power to support (an uncompromised combination of) all this functionality is highly non-trivial. Designing processors that meet the demanding requirements of future mobile devices requires the optimization of the embedded system in general and of the embedded processors in particular, as they should strike the correct balance between flexibility, energy efficiency and performance. In general, a designer will try to minimize the energy consumption (as far as needed) for a given performance, with a sufficient flexibility. However, achieving this goal is already complex when looking at the processor in isolation, but, in reality, the processor is a single component in a more complex system. In order to design such complex system successfully, critical decisions during the design of each individual component should take into account effect on the other parts, with a clear goal to move to a global Pareto optimum in the complete multi-dimensional exploration space. In the complex, global design of battery-operated embedded systems, the focus of Ultra-Low Energy Domain-Specific Instruction-Set Processors is on the energy-aware architecture exploration of domain-specific instruction-set processors and the co-optimization of the datapath architecture, foreground memory, and instruction memory organisation with a link to the required mapping techniques or compiler steps at the early stages of the design. By performing an extensive energy breakdown experiment for a complete embedded platform, both energy and performance bottlenecks have been identified, together with the important relations between the different components. Based on this knowledge, architecture extensions are proposed for all the bottlenecks.
Ranging from low-level application and architecture optimizations to high-level modeling and exploration concerns, this authoritative reference compiles essential research on various levels of abstraction appearing in embedded systems and software design. It promotes platform-based design for improved system implementation and modeling and enhanced performance and cost analyses. Domain-Specific Processors relies upon notions of concurrency and parallelism to satisfy performance and cost constraints resulting from increasingly complex applications and architectures and addresses concepts in specification, simulation, and verification in embedded systems and software design.
Discover the future of programmable and reconfigurable embedded processors. The assessments in this text run from the realizations of the extended linearization model to the optimization for piecewise regular processor arrays. It also emphasizes efficiency in discussions of scalable parallel-pipelined and compiled regular architectures and covers single-chip multiprocessing for consumer electronics.
Modern signal processing systems require more and more processing capacity as times goes on. Previously, large increases in speed and power efficiency have come from process technology improvements. However, lately the gain from process improvements have been greatly reduced. Currently, the way forward for high-performance systems is to use specialized hardware and/or parallel designs. Application Specific Integrated Circuits (ASICs) have long been used to accelerate the processing of tasks that are too computationally heavy for more general processors. The problem with ASICs is that they are costly to develop and verify, and the product life time can be limited with newer standards. Since they are very specific the applicable domain is very narrow. More general processors are more flexible and can easily adapt to perform the functions of ASIC based designs. However, the generality comes with a performance cost that renders general designs unusable for some tasks. The question then becomes, how general can a processor be while still being power efficient and fast enough for some particular domain? Application Specific Instruction set Processors (ASIPs) are processors that target a specific application domain, and can offer enough performance with power efficiency and silicon cost that is comparable to ASICs. The flexibility allows for the same hardware design to be used over several system designs, and also for multiple functions in the same system, if some functions are not used simultaneously. One problem with ASIPs is that they are more difficult to program than a general purpose processor, given that we want efficient software. Utilizing all of the features that give an ASIP its performance advantage can be difficult at times, and new tools and methods for programming them are needed. This thesis will present ePUMA (embedded Parallel DSP platform with Unique Memory Access), an ASIP architecture that targets algorithms with predictable data access. These kinds of algorithms are very common in e.g. baseband processing or multimedia applications. The primary focus will be on the specific features of ePUMA that are utilized to achieve high performance, and how it is possible to automatically utilize them using tools. The most significant features include data permutation for conflict-free data access, and utilization of address generation features for overhead free code execution. This sometimes requires specific information; for example the exact sequences of addresses in memory that are accessed, or that some operations may be performed in parallel. This is not always available when writing code using the traditional way with traditional languages, e.g. C, as extracting this information is still a very active research topic. In the near future at least, the way that software is written needs to change to exploit all hardware features, but in many cases in a positive way. Often the problem with current methods is that code is overly specific, and that a more general abstractions are actually easier to generate code from.
Customizable processors have been described as the next natural step in the evolution of the microprocessor business: a step in the life of a new technology where top performance alone is no longer sufficient to guarantee market success. Other factors become fundamental, such as time to market, convenience, energy efficiency, and ease of customization. This book is the first to explore comprehensively one of the most fundamental trends which emerged in the last decade: to treat processors not as rigid, fixed entities, which designers include “as is in their products; but rather, to build sound methodologies to tailor-fit processors to the specific needs of such products. This book addresses the goal of maintaining a very large family of processors, with a wide range of features, at a cost comparable to that of maintaining a single processor. First book to present comprehensively the major ASIP design methodologies and tools without any particular bias Written by most of the pioneers and top international experts of this young domain Unique mix of management perspective, technical detail, research outlook, and practical implementation
Application Specific Processors is written for use by engineers who are developing specialized systems (application specific systems). Traditionally, most high performance signal processors have been realized with application specific processors. The explanation is that application specific processors can be tailored to exactly match the (usually very demanding) application requirements. The result is that no `processing power' is wasted for unnecessary capabilities and maximum performance is achieved. A disadvantage is that such processors have been expensive to design since each is a unique design that is customized to the specific application. In the last decade, computer-aided design systems have been developed to facilitate the development of application specific integrated circuits. The success of such ASIC CAD systems suggests that it should be possible to streamline the process of application specific processor design. Application Specific Processors consists of eight chapters which provide a mixture of techniques and examples that relate to application specific processing. The inclusion of techniques is expected to suggest additional research and to assist those who are faced with the requirement to implement efficient application specific processors. The examples illustrate the application of the concepts and demonstrate the efficiency that can be achieved via application specific processors. The chapters were written by members and former members of the application specific processing group at the University of Texas at Austin. The first five chapters relate to specific arithmetic which often is the key to achieving high performance in application specific processors. The next two chapters focus on signal processing systems, and the final chapter examines the interconnection of possibly disparate elements to create systems.
Over the past several decades, researchers and programmers across many disciplines have relied on Moores law and Dennard scaling for increases in compute capability in modern processors. However, recent data suggest that the number of transistors per square inch on integrated circuits is losing pace with Moores laws projection due to the breakdown of Dennard scaling at smaller semiconductor process nodes. This has signaled the beginning of a new "golden age in computer architecture" in which the paradigm will be shifted from improving traditional processor performance for general tasks to architecting hardware that executes a class of applications in a high-performing manner. This shift will be paved, in part, by making compute systems more heterogeneous and investigating domain specific architectures. However, the notion of domain specific architectures raises many research questions. Specifically, what constitutes a domain? How does one architect hardware for a specific domain? In this dissertation, we present our work towards domain specific computing. We start by constructing a guiding definition for our target domain and then creating a benchmark suite of applications based on our domain definition. We then use quantitative metrics from the literature to characterize our domain in order to gain insights regarding what would be most beneficial in hardware targeted specifically for the domain. From the characterization, we learn that data movement is a particularly salient aspect of our domain. Motivated by this fact, we evaluate our target platform, the Intel HARPv2 CPU+FPGA system, for architecting domain specific hardware through a portability and performance evaluation. To guide the creation of domain specific hardware for this platform, we create a novel tool to quantify spatial and temporal locality. We apply this tool to our benchmark suite and use the generated outputs as features to an unsupervised clustering algorithm. We posit that the resulting clusters represent sub-domains within our originally specified domain; specifically, these clusters inform whether a kernel of computation should be designed as a widely vectorized or deeply pipelined compute unit. Using the lessons learned from the domain characterization and hardware platform evaluation, we outline our process of designing hardware for our domain, and empirically verify that our prediction regarding a wide or deep kernel implementation is correct.
