Scalable System-on-Chip Design

The crisis of technology scaling led the industry of semiconductors towards the adoption of disruptive technologies and innovations to sustain the evolution of microprocessors and keep under control the timing of the design cycle. Multi-core and many-core architectures sought more energy-efficient computation by replacing a power-hungry processor with multiple simpler cores exploiting parallelism. Multi-core processors alone, however, turned out to be insufficient to sustain the ever growing demand for energy and power-efficient computation without compromising performance. Therefore, designers were pushed to drift from homogeneous architectures towards more complex heterogeneous systems that employ the large number of available transistors to incorporate a combination of customized energy-efficient accelerators, along with the general-purpose processor cores. Meanwhile, enhancements in manufacturing processes allowed designers to move a variety of peripheral components and analog devices into the chip. This paradigm shift defined the concept of {\em system-on-chip} (SoC) as a single-chip design that integrates several heterogeneous components. The rise of SoCs corresponds to a rapid decrease of the opportunity cost for integrating accelerators. In fact, on one hand, employing more transistors for powerful cores is not feasible anymore, because transistors cannot be active all at once within reasonable power budgets. On the other hand, increasing the number of homogeneous cores incurs more and more diminishing returns. The availability of cost effective silicon area for specialized hardware creates an opportunity to enter the market of semiconductors for new small players: engineers from several different scientific areas can develop competitive algorithms suitable for acceleration for domain-specific applications, such as multimedia systems, self-driving vehicles, robotics, and more. However, turning these algorithms into SoC components, referred to as {\em intellectual property}, still requires expert hardware designers who are typically not familiar with the specific domain of the target application. Furthermore, heterogeneity makes SoC design and programming much more difficult, especially because of the challenges of the integration process. This is a fine art in the hands of few expert engineers who understand system-level trade-offs, know how to design good hardware, how to handle memory and power management, how to shape and balance the traffic over an interconnect, and are able to deal with many different hardware-software interfaces. Designers need solutions enabling them to build scalable and heterogeneous SoCs. My thesis is that {\em the key to scalable SoC designs is a regular and flexible architecture that hides the complexity of heterogeneous integration from designers, while helping them focus on the important aspects of domain-specific applications through a companion system-level design methodology.} I open a path towards this goal by proposing an architecture that mitigates heterogeneity with regularity and addresses the challenges of heterogeneous component integration by implementing a set of {\em platform services}. These are hardware and software interfaces that from a system-level viewpoint give the illusion of working with a homogeneous SoC, thus making it easier to reuse accelerators and port applications across different designs, each with its own target workload and cost-performance trade-off point. A companion system-level design methodology exploits the regularity of the architecture to guide designers in implementing their intellectual property and enables an extensive design-space exploration across multiple levels of abstraction. Throughout the dissertation, I present a fully automated flow to deploy heterogeneous SoCs on single or multiple field-programmable-gate-array devices. The flow provides non-expert designers with a set of knobs for tuning system-level features based on the given mix of accelerators that they have integrated. Many contributions of my dissertation have already influenced other research projects as well as the content of an advanced course for graduate and senior undergraduate students, which aims to form a new generation of system-level designers. These new professionals need not to be circuit or register-transfer level design experts, and not even gurus of operating systems. Instead, they are trained to design efficient intellectual property by considering system-level trade-offs, while the architecture and the methodology that I describe in this dissertation empower them to integrate their components into an SoC. Finally, with the open-source release of the entire infrastructure, including the SoC-deployment flow and the software stack, I hope I will be able to inspire other research groups and help them implement ideas that further reduce the cost and design-time of future heterogeneous systems

High-performance and Low-power Clock Network Synthesis in the Presence of Variation.

Semiconductor technology scaling requires continuous evolution of all aspects of physical design of integrated circuits. Among the major design steps, clock-network synthesis has been greatly affected by technology scaling, rendering existing methodologies inadequate. Clock routing was previously sufficient for smaller ICs, but design difficulty and structural complexity have greatly increased as interconnect delay and clock frequency increased in the 1990s. Since a clock network directly influences IC performance and often consumes a substantial portion of total power, both academia and industry developed synthesis methodologies to achieve low skew, low power and robustness from PVT variations. Nevertheless, clock network synthesis under tight constraints is currently the least automated step in physical design and requires significant manual intervention, undermining turn-around-time. The need for multi-objective optimization over a large parameter space and the increasing impact of process variation make clock network synthesis particularly challenging. Our work identifies new objectives, constraints and concerns in the clock-network synthesis for systems-on-chips and microprocessors. To address them, we generate novel clock-network structures and propose changes in traditional physical-design flows. We develop new modeling techniques and algorithms for clock power optimization subject to tight skew constraints in the presence of process variations. In particular, we offer SPICE-accurate optimizations of clock networks, coordinated to reduce nominal skew below 5 ps, satisfy slew constraints and trade-off skew, insertion delay and power, while tolerating variations. To broaden the scope of clock-network-synthesis optimizations, we propose new techniques and a methodology to reduce dynamic power consumption by 6.8%-11.6% for large IC designs with macro blocks by integrating clock network synthesis within global placement. We also present a novel non-tree topology that is 2.3x more power-efficient than mesh structures. We fuse several clock trees to create large-scale redundancy in a clock network to bridge the gap between tree-like and mesh-like topologies. Integrated optimization techniques for high-quality clock networks described in this dissertation strong empirical results in experiments with recent industry-released benchmarks in the presence of process variation. Our software implementations were recognized with the first-place awards at the ISPD 2009 and ISPD 2010 Clock-Network Synthesis Contests organized by IBM Research and Intel Research.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89711/1/ejdjsy_1.pd

Driving the Network-on-Chip Revolution to Remove the Interconnect Bottleneck in Nanoscale Multi-Processor Systems-on-Chip

The sustained demand for faster, more powerful chips has been met by the availability of chip manufacturing processes allowing for the integration of increasing numbers of computation units onto a single die. The resulting outcome, especially in the embedded domain, has often been called SYSTEM-ON-CHIP (SoC) or MULTI-PROCESSOR SYSTEM-ON-CHIP (MP-SoC). MPSoC design brings to the foreground a large number of challenges, one of the most prominent of which is the design of the chip interconnection. With a number of on-chip blocks presently ranging in the tens, and quickly approaching the hundreds, the novel issue of how to best provide on-chip communication resources is clearly felt. NETWORKS-ON-CHIPS (NoCs) are the most comprehensive and scalable answer to this design concern. By bringing large-scale networking concepts to the on-chip domain, they guarantee a structured answer to present and future communication requirements. The point-to-point connection and packet switching paradigms they involve are also of great help in minimizing wiring overhead and physical routing issues. However, as with any technology of recent inception, NoC design is still an evolving discipline. Several main areas of interest require deep investigation for NoCs to become viable solutions: • The design of the NoC architecture needs to strike the best tradeoff among performance, features and the tight area and power constraints of the onchip domain. • Simulation and verification infrastructure must be put in place to explore, validate and optimize the NoC performance. • NoCs offer a huge design space, thanks to their extreme customizability in terms of topology and architectural parameters. Design tools are needed to prune this space and pick the best solutions. • Even more so given their global, distributed nature, it is essential to evaluate the physical implementation of NoCs to evaluate their suitability for next-generation designs and their area and power costs. This dissertation performs a design space exploration of network-on-chip architectures, in order to point-out the trade-offs associated with the design of each individual network building blocks and with the design of network topology overall. The design space exploration is preceded by a comparative analysis of state-of-the-art interconnect fabrics with themselves and with early networkon- chip prototypes. The ultimate objective is to point out the key advantages that NoC realizations provide with respect to state-of-the-art communication infrastructures and to point out the challenges that lie ahead in order to make this new interconnect technology come true. Among these latter, technologyrelated challenges are emerging that call for dedicated design techniques at all levels of the design hierarchy. In particular, leakage power dissipation, containment of process variations and of their effects. The achievement of the above objectives was enabled by means of a NoC simulation environment for cycleaccurate modelling and simulation and by means of a back-end facility for the study of NoC physical implementation effects. Overall, all the results provided by this work have been validated on actual silicon layout

Automatic synthesis and optimization of chip multiprocessors

The microprocessor technology has experienced an enormous growth during the last decades. Rapid downscale of the CMOS technology has led to higher operating frequencies and performance densities, facing the fundamental issue of power dissipation. Chip Multiprocessors (CMPs) have become the latest paradigm to improve the power-performance efficiency of computing systems by exploiting the parallelism inherent in applications. Industrial and prototype implementations have already demonstrated the benefits achieved by CMPs with hundreds of cores.CMP architects are challenged to take many complex design decisions. Only a few of them are:- What should be the ratio between the core and cache areas on a chip?- Which core architectures to select?- How many cache levels should the memory subsystem have?- Which interconnect topologies provide efficient on-chip communication?These and many other aspects create a complex multidimensional space for architectural exploration. Design Automation tools become essential to make the architectural exploration feasible under the hard time-to-market constraints. The exploration methods have to be efficient and scalable to handle future generation on-chip architectures with hundreds or thousands of cores.Furthermore, once a CMP has been fabricated, the need for efficient deployment of the many-core processor arises. Intelligent techniques for task mapping and scheduling onto CMPs are necessary to guarantee the full usage of the benefits brought by the many-core technology. These techniques have to consider the peculiarities of the modern architectures, such as availability of enhanced power saving techniques and presence of complex memory hierarchies.This thesis has several objectives. The first objective is to elaborate the methods for efficient analytical modeling and architectural design space exploration of CMPs. The efficiency is achieved by using analytical models instead of simulation, and replacing the exhaustive exploration with an intelligent search strategy. Additionally, these methods incorporate high-level models for physical planning. The related contributions are described in Chapters 3, 4 and 5 of the document.The second objective of this work is to propose a scalable task mapping algorithm onto general-purpose CMPs with power management techniques, for efficient deployment of many-core systems. This contribution is explained in Chapter 6 of this document.Finally, the third objective of this thesis is to address the issues of the on-chip interconnect design and exploration, by developing a model for simultaneous topology customization and deadlock-free routing in Networks-on-Chip. The developed methodology can be applied to various classes of the on-chip systems, ranging from general-purpose chip multiprocessors to application-specific solutions. Chapter 7 describes the proposed model.The presented methods have been thoroughly tested experimentally and the results are described in this dissertation. At the end of the document several possible directions for the future research are proposed

A Scalable and Adaptive Network on Chip for Many-Core Architectures

In this work, a scalable network on chip (NoC) for future many-core architectures is proposed and investigated. It supports different QoS mechanisms to ensure predictable communication. Self-optimization is introduced to adapt the energy footprint and the performance of the network to the communication requirements. A fault tolerance concept allows to deal with permanent errors. Moreover, a template-based automated evaluation and design methodology and a synthesis flow for NoCs is introduced

Supervised Design-Space Exploration

Low-cost Very Large Scale Integration (VLSI) electronics have revolutionized daily life and expanded the role of computation in science and engineering. Meanwhile, process-technology scaling has changed VLSI design to an exploration process that strives for the optimal balance among multiple objectives, such as power, performance, and area, i.e. multi-objective Pareto-set optimization. Besides, modern VLSI design has shifted to synthesis-centric methodologies in order to boost the design productivity, which leads to better design quality given limited time and resources. However, current decade-old synthesis-centric design methodologies suffer from: (i) long synthesis tool runtime, (ii) elusive optimal setting of many synthesis knobs, (iii) limitation to one design implementation per synthesis run, and (iv) limited capability of digesting only component-level designs as opposed to holistic system-wide synthesis. These challenges make Design Space Exploration (DSE) with synthesis tools a daunting task for both novice and experienced VLSI designers, thus stagnating the development of more powerful (i.e. more complex) computer systems. To address these challenges, I propose Supervised Design-Space Exploration (SDSE), an abstraction layer between a designer and a synthesis tool, aiming to autonomously supervise synthesis jobs for DSE. For system-level exploration, SDSE can approximate a system Pareto set given limited information: only lightweight component characterization is required, yet the necessary component synthesis jobs are discovered on-the-fly in order to compose the system Pareto set. For component-level exploration, SDSE can approximate a component Pareto set by iteratively refining the approximation with promising knob settings, guided by synthesis-result estimation with machine-learning models. Combined, SDSE has been applied with the three major synthesis stages, namely high-level, logic, and physical synthesis, to the design of heterogeneous accelerator cores as well as high-performance processor cores. In particular, SDSE has been successfully integrated into the IBM Synthesis Tuning System, yielding 20% better circuit performance than the original system on the design of a 22nm server processor that is currently in production. Looking ahead, SDSE can be applied to other VLSI designs beyond the accelerator and the programmable cores. Moreover, SDSE opens several research avenues for: (i) new development and deployment platforms of synthesis tools, (ii) large-scale collaborative design engineering, and (iii) new computer-aided design approaches for new classes of systems beyond VLSI chips

Vector support for multicore processors with major emphasis on configurable multiprocessors

It recently became increasingly difficult to build higher speed uniprocessor chips because of performance degradation and high power consumption. The quadratically increasing circuit complexity forbade the exploration of more instruction-level parallelism (JLP). To continue raising the performance, processor designers then focused on thread-level parallelism (TLP) to realize a new architecture design paradigm. Multicore processor design is the result of this trend. It has proven quite capable in performance increase and provides new opportunities in power management and system scalability. But current multicore processors do not provide powerful vector architecture support which could yield significant speedups for array operations while maintaining arealpower efficiency. This dissertation proposes and presents the realization of an FPGA-based prototype of a multicore architecture with a shared vector unit (MCwSV). FPGA stands for Filed-Programmable Gate Array. The idea is that rather than improving only scalar or TLP performance, some hardware budget could be used to realize a vector unit to greatly speedup applications abundant in data-level parallelism (DLP). To be realistic, limited by the parallelism in the application itself and by the compiler\u27s vectorizing abilities, most of the general-purpose programs can only be partially vectorized. Thus, for efficient resource usage, one vector unit should be shared by several scalar processors. This approach could also keep the overall budget within acceptable limits. We suggest that this type of vector-unit sharing be established in future multicore chips. The design, implementation and evaluation of an MCwSV system with two scalar processors and a shared vector unit are presented for FPGA prototyping. The MicroBlaze processor, which is a commercial IP (Intellectual Property) core from Xilinx, is used as the scalar processor; in the experiments the vector unit is connected to a pair of MicroBlaze processors through standard bus interfaces. The overall system is organized in a decoupled and multi-banked structure. This organization provides substantial system scalability and better vector performance. For a given area budget, benchmarks from several areas show that the MCwSV system can provide significant performance increase as compared to a multicore system without a vector unit. However, a MCwSV system with two MicroBlazes and a shared vector unit is not always an optimized system configuration for various applications with different percentages of vectorization. On the other hand, the MCwSV framework was designed for easy scalability to potentially incorporate various numbers of scalar/vector units and various function units. Also, the flexibility inherent to FPGAs can aid the task of matching target applications. These benefits can be taken into account to create optimized MCwSV systems for various applications. So the work eventually focused on building an architecture design framework incorporating performance and resource management for application-specific MCwSV (AS-MCwSV) systems. For embedded system design, resource usage, power consumption and execution latency are three metrics to be used in design tradeoffs. The product of these metrics is used here to choose the MCwSV system with the smallest value

Design of electronic systems for automotive sensor conditioning

This thesis deals with the development of sensor systems for automotive, mainly targeting the exploitation of the new generation of Micro Electro-Mechanical Sensors (MEMS), which achieve a dramatic reduction of area and power consumption but at the same time require more complexity in the sensor conditioning interface. Several issues concerning the development of automotive ASICs are presented, together with an overview of automotive electronics market and its main sensor applications. The state of the art for sensor interfaces design (the generic sensor interface concept), consists in sharing the same electronics among similar sensor applications, thus saving cost and time-to-market but also implementing a sub-optimal system with area and power overheads. A Platform Based Design methodology is proposed to overcome the limitations of generic sensor interfaces, by keeping the platform generality at the highest design layers and pursuing the maximum optimization and performances in the platform customization for a specific sensor. A complete design flow is presented (up to the ASIC implementation for gyro sensor conditioning), together with examples regarding IP development for reuse and low power optimization of third party designs. A further evolution of Platform Based Design has been achieved by means of implementation into silicon of the ISIF (Intelligent Sensor InterFace) platform. ISIF is a highly programmable mixed-signal chip which allows a substantial reduction of design space exploration time, as it can implement in a short time a wide class of sensor conditioning architectures. Thus it lets the designers evaluate directly on silicon the impact of different architectural choices, as well as perform feasibility studies, sensor evaluations and accurate estimation of the resulting dedicated ASIC performances. Several case studies regarding fast prototyping possibilities with ISIF are presented: a magneto-resistive position sensor, a biosensor (which produces pA currents in presence of surface chemical reactions) and two capacitive inertial sensors, a gyro and a low-g YZ accelerometer. The accelerometer interface has also been implemented in miniboards of about 3 cm2 (with ISIF and sensor dies bonded together) and a series of automatic trimming and characterization procedures have been developed in order to evaluate sensor and interface behaviour over the automotive temperature range, providing a valuable feedback for the implementation of a dedicated accelerometer interface

Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications

The challenging deployment of compute-intensive applications from domains such Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of computing systems to explore new design approaches. Approximate Computing appears as an emerging solution, allowing to tune the quality of results in the design of a system in order to improve the energy efficiency and/or performance. This radical paradigm shift has attracted interest from both academia and industry, resulting in significant research on approximation techniques and methodologies at different design layers (from system down to integrated circuits). Motivated by the wide appeal of Approximate Computing over the last 10 years, we conduct a two-part survey to cover key aspects (e.g., terminology and applications) and review the state-of-the art approximation techniques from all layers of the traditional computing stack. In Part II of our survey, we classify and present the technical details of application-specific and architectural approximation techniques, which both target the design of resource-efficient processors/accelerators & systems. Moreover, we present a detailed analysis of the application spectrum of Approximate Computing and discuss open challenges and future directions.Comment: Under Review at ACM Computing Survey

On Multicast in Asynchronous Networks-on-Chip: Techniques, Architectures, and FPGA Implementation

In this era of exascale computing, conventional synchronous design techniques are facing unprecedented challenges. The consumer electronics market is replete with many-core systems in the range of 16 cores to thousands of cores on chip, integrating multi-billion transistors. However, with this ever increasing complexity, the traditional design approaches are facing key issues such as increasing chip power, process variability, aging, thermal problems, and scalability. An alternative paradigm that has gained significant interest in the last decade is asynchronous design. Asynchronous designs have several potential advantages: they are naturally energy proportional, burning power only when active, do not require complex clock distribution, are robust to different forms of variability, and provide ease of composability for heterogeneous platforms. Networks-on-chip (NoCs) is an interconnect paradigm that has been introduced to deal with the ever-increasing system complexity. NoCs provide a distributed, scalable, and efficient interconnect solution for today’s many-core systems. Moreover, NoCs are a natural match with asynchronous design techniques, as they separate communication infrastructure and timing from the computational elements. To this end, globally-asynchronous locally-synchronous (GALS) systems that interconnect multiple processing cores, operating at different clock speeds, using an asynchronous NoC, have gained significant interest. While asynchronous NoCs have several advantages, they also face a key challenge of supporting new types of traffic patterns. Once such pattern is multicast communication, where a source sends packets to arbitrary number of destinations. Multicast is not only common in parallel computing, such as for cache coherency, but also for emerging areas such as neuromorphic computing. This important capability has been largely missing from asynchronous NoCs. This thesis introduces several efficient multicast solutions for these interconnects. In particular, techniques, and network architectures are introduced to support high-performance and low-power multicast. Two leading network topologies are the focus: a variant mesh-of-trees (MoT) and a 2D mesh. In addition, for a more realistic implementation and analysis, as well as significantly advancing the field of asynchronous NoCs, this thesis also targets synthesis of these NoCs on commercial FPGAs. While there has been significant advances in FPGA technologies, there has been only limited research on implementing asynchronous NoCs on FPGAs. To this end, a systematic computeraided design (CAD) methodology has been introduced to efficiently and safely map asynchronous NoCs on FPGAs. Overall, this thesis makes the following three contributions. The first contribution is a multicast solution for a variant MoT network topology. This topology consists of simple low-radix switches, and has been used in high-performance computing platforms. A novel local speculation technique is introduced, where a subset of the network’s switches are speculative that always broadcast every packet. These switches are very simple and have high performance. Speculative switches are surrounded by non-speculative ones that route packets based on their destinations and also throttle any redundant copies created by the former. This hybrid network architecture achieved significant performance and power benefits over other multicast approaches. The second contribution is a multicast solution for a 2D-mesh topology, which is more complex with higher-radix switches and also is more commonly used. A novel continuous-time replication strategy is introduced to optimize the critical multi-way forking operation of a multicast transmission. In this technique, a multicast packet is first stored in an input port of a switch, from where it is sent through distinct output ports towards different destinations concurrently, at each output’s own rate and in continuous time. This strategy is shown to have significant latency and energy benefits over an approach that performs multicast using multiple distinct serial unicasts to each destination. Finally, a systematic CAD methodology is introduced to synthesize asynchronous NoCs on commercial FPGAs. A two-fold goal is targeted: correctness and high performance. For ease of implementation, only existing FPGA synthesis tools are used. Moreover, since asynchronous NoCs involve special asynchronous components, a comprehensive guide is introduced to map these elements correctly and efficiently. Two asynchronous NoC switches are synthesized using the proposed approach on a leading Xilinx FPGA in 28 nm: one that only handles unicast, and the other that also supports multicast. Both showed significant energy benefits with some performance gains over a state-of-the-art synchronous switch