Incremental Timing-Driven Placement with Displacement Constraint

In the modern deep-submicron Very Large Integrated Circuit(VLSI) design flow intercon- nect delays are becoming major limiting factor for timing closure. Traditional placement algorithms such as routability-driven placement (improves routability) and wirelength- driven placement (reduces total wirelength) are no longer sufficient to close timing. To this end, timing-driven placement plays a crucial role in reducing the interconnect delay through timing critical paths (paths with timing violations/negative slacks) of the design and thereby achieving specific performance/clock frequency. In the placement flow, timing information about the design can be incorporated during global placement and/or incremental/detailed placement. Although, over the years, there has been significant advances in the quality of the global placement, there is a growing need for high performance incremental timing-driven placement due to the lack of accurate interconnect information during global placement. Moreover, incremental timing-driven placement is essential to recover timing while preserving the other optimization objectives such as total wirelength, routing congestion, and so forth which are optimized at the early stages of the design flow. This thesis proposes a simple, yet efficient, incremental timing-driven placement algo- rithm that seeks to find optimized locations for standard cells so that the total negative slack of the design can be maximized. Our algorithm consists two stages: (1) Global Move which positions standard cells inside a critical bounding box to eliminate timing violations on timing critical nets; and (2) Local Move which provides further timing improvement by finely adjusting the current locations of the standard cells within a local region. We evaluate our algorithm using ICCAD-2014 timing-driven placement contest bench- marks. The results show that, on average, our technique eliminates 94% and 30% of the late and early total negative slacks, respectively, and, 82% and 27% of the late and early worst negative slacks, respectively, under short and long displacement constraints. The 1st-place team of the contest improves late and early total negative slacks by 90% and 39%, respectively, and improves late and early worst negative slack by 76% and 32%, re- spectively. Taking into account both timing violation improvement and the placement quality (i.e., other objectives), on average, we outperform the 1st-place team by 3% in terms of the ICCAD-2014 contest quality score and our technique is 4.6× faster in terms of runtime

Graphics Processing Unit-Based Computer-Aided Design Algorithms for Electronic Design Automation

The electronic design automation (EDA) tools are a specific set of software that play important roles in modern integrated circuit (IC) design. These software automate the design processes of IC with various stages. Among these stages, two important EDA design tools are the focus of this research: floorplanning and global routing. Specifically, the goal of this study is to parallelize these two tools such that their execution time can be significantly shortened on modern multi-core and graphics processing unit (GPU) architectures. The GPU hardware is a massively parallel architecture, enabling thousands of independent threads to execute concurrently. Although a small set of EDA tools can benefit from using GPU to accelerate their speed, most algorithms in this field are designed with the single-core paradigm in mind. The floorplanning and global routing algorithms are among the latter, and difficult to render any speedup on the GPU due to their inherent sequential nature. This work parallelizes the floorplanning and global routing algorithm through a novel approach and results in significant speedups for both tools implemented on the GPU hardware. Specifically, with a complete overhaul of solution space and design space exploration, a GPU-based floorplanning algorithm is able to render 4-166X speedup, while achieving similar or improved solutions compared with the sequential algorithm. The GPU-based global routing algorithm is shown to achieve significant speedup against existing state-of-the-art routers, while delivering competitive solution quality. Importantly, this parallel model for global routing renders a stable solution that is independent from the level of parallelism. In summary, this research has shown that through a design paradigm overhaul, sequential algorithms can also benefit from the massively parallel architecture. The findings of this study have a positive impact on the efficiency and design quality of modern EDA design flow

Algorithms for Circuit Sizing in VLSI Design

One of the key problems in the physical design of computer chips, also known as integrated circuits, consists of choosing a  physical layout  for the logic gates and memory circuits (registers) on the chip. The layouts have a high influence on the power consumption and area of the chip and the delay of signal paths.  A discrete set of predefined layouts  for each logic function and register type with different physical properties is given by a library. One of the most influential characteristics of a circuit defined by the layout is its size. In this thesis we present new algorithms for the problem of choosing sizes for the circuits and its continuous relaxation,  and  evaluate these in theory and practice. A popular approach is based on Lagrangian relaxation and projected subgradient methods. We show that seemingly heuristic modifications that have been proposed for this approach can be theoretically justified by applying the well-known multiplicative weights algorithm. Subsequently, we propose a new model for the sizing problem as a min-max resource sharing problem. In our context, power consumption and signal delays are represented by resources that are distributed to customers. Under certain assumptions we obtain a polynomial time approximation for the continuous relaxation of the sizing problem that improves over the Lagrangian relaxation based approach. The new resource sharing algorithm has been implemented as part of the BonnTools software package which is developed at the Research Institute for Discrete Mathematics at the University of Bonn in cooperation with IBM. Our experiments on the ISPD 2013 benchmarks and state-of-the-art microprocessor designs provided by IBM illustrate that the new algorithm exhibits more stable convergence behavior compared to a Lagrangian relaxation based algorithm. Additionally, better timing and reduced power consumption was achieved on almost all instances. A subproblem of the new algorithm consists of finding sizes minimizing a weighted sum of power consumption and signal delays. We describe a method that approximates the continuous relaxation of this problem in polynomial time under certain assumptions. For the discrete problem we provide a fully polynomial approximation scheme under certain assumptions on the topology of the chip. Finally, we present a new algorithm for timing-driven optimization of registers. Their sizes and locations on a chip are usually determined during the clock network design phase, and remain mostly unchanged afterwards although the timing criticalities on which they were based can change. Our algorithm permutes register positions and sizes within so-called  clusters  without impairing the clock network such that it can be applied late in a design flow. Under mild assumptions, our algorithm finds an optimal solution which maximizes the worst cluster slack. It is implemented as part of the BonnTools and improves timing of registers on state-of-the-art microprocessor designs by up to 7.8% of design cycle time. </div

Rapid SoC Design: On Architectures, Methodologies and Frameworks

Modern applications like machine learning, autonomous vehicles, and 5G networking require an order of magnitude boost in processing capability. For several decades, chip designers have relied on Moore’s Law - the doubling of transistor count every two years to deliver improved performance, higher energy efficiency, and an increase in transistor density. With the end of Dennard’s scaling and a slowdown in Moore’s Law, system architects have developed several techniques to deliver on the traditional performance and power improvements we have come to expect. More recently, chip designers have turned towards heterogeneous systems comprised of more specialized processing units to buttress the traditional processing units. These specialized units improve the overall performance, power, and area (PPA) metrics across a wide variety of workloads and applications. While the GPU serves as a classical example, accelerators for machine learning, approximate computing, graph processing, and database applications have become commonplace. This has led to an exponential growth in the variety (and count) of these compute units found in modern embedded and high-performance computing platforms. The various techniques adopted to combat the slowing of Moore’s Law directly translates to an increase in complexity for modern system-on-chips (SoCs). This increase in complexity in turn leads to an increase in design effort and validation time for hardware and the accompanying software stacks. This is further aggravated by fabrication challenges (photo-lithography, tooling, and yield) faced at advanced technology nodes (below 28nm). The inherent complexity in modern SoCs translates into increased costs and time-to-market delays. This holds true across the spectrum, from mobile/handheld processors to high-performance data-center appliances. This dissertation presents several techniques to address the challenges of rapidly birthing complex SoCs. The first part of this dissertation focuses on foundations and architectures that aid in rapid SoC design. It presents a variety of architectural techniques that were developed and leveraged to rapidly construct complex SoCs at advanced process nodes. The next part of the dissertation focuses on the gap between a completed design model (in RTL form) and its physical manifestation (a GDS file that will be sent to the foundry for fabrication). It presents methodologies and a workflow for rapidly walking a design through to completion at arbitrary technology nodes. It also presents progress on creating tools and a flow that is entirely dependent on open-source tools. The last part presents a framework that not only speeds up the integration of a hardware accelerator into an SoC ecosystem, but emphasizes software adoption and usability.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168119/1/ajayi_1.pd

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

MOCAST 2021

The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications

Source-synchronous I/O Links using Adaptive Interface Training for High Bandwidth Applications

Mobility is the key to the global business which requires people to be always connected to a central server. With the exponential increase in smart phones, tablets, laptops, mobile traffic will soon reach in the range of Exabytes per month by 2018. Applications like video streaming, on-demand-video, online gaming, social media applications will further increase the traffic load. Future application scenarios, such as Smart Cities, Industry 4.0, Machine-to-Machine (M2M) communications bring the concepts of Internet of Things (IoT) which requires high-speed low power communication infrastructures. Scientific applications, such as space exploration, oil exploration also require computing speed in the range of Exaflops/s by 2018 which means TB/s bandwidth at each memory node. To achieve such bandwidth, Input/Output (I/O) link speed between two devices needs to be increased to GB/s. The data at high speed between devices can be transferred serially using complex Clock-Data-Recovery (CDR) I/O links or parallely using simple source-synchronous I/O links. Even though CDR is more efficient than the source-synchronous method for single I/O link, but to achieve TB/s bandwidth from a single device, additional I/O links will be required and the source-synchronous method will be more advantageous in terms of area and power requirements as additional I/O links do not require extra hardware resources. At high speed, there are several non-idealities (Supply noise, crosstalk, Inter- Symbol-Interference (ISI), etc.) which create unwanted skew problem among parallel source-synchronous I/O links. To solve these problems, adaptive trainings are used in time domain to synchronize parallel source-synchronous I/O links irrespective of these non-idealities. In this thesis, two novel adaptive training architectures for source-synchronous I/O links are discussed which require significantly less silicon area and power in comparison to state-of-the-art architectures. First novel adaptive architecture is based on the unit delay concept to synchronize two parallel clocks by adjusting the phase of one clock in only one direction. Second novel adaptive architecture concept consists of Phase Interpolator (PI)-based Phase Locked Loop (PLL) which can adjust the phase in both direction and achieve faster synchronization at the expense of added complexity. With an increase in parallel I/O links, clock skew which is generated by the improper clock tree, also affects the timing margin. Incorrect duty cycle further reduces the timing margin mainly in Double Data Rate (DDR) systems which are generally used to increase the bandwidth of a high-speed communication system. To solve clock skew and duty cycle problems, a novel clock tree buffering algorithm and a novel duty cycle corrector are described which further reduce the power consumption of a source-synchronous system