Modeling and Analysis of Noise and Interconnects for On-Chip Communication Link Design

This thesis considers modeling and analysis of noise and interconnects in onchip communication. Besides transistor count and speed, the capabilities of a modern design are often limited by on-chip communication links. These links typically consist of multiple interconnects that run parallel to each other for long distances between functional or memory blocks. Due to the scaling of technology, the interconnects have considerable electrical parasitics that affect their performance, power dissipation and signal integrity. Furthermore, because of electromagnetic coupling, the interconnects in the link need to be considered as an interacting group instead of as isolated signal paths. There is a need for accurate and computationally effective models in the early stages of the chip design process to assess or optimize issues affecting these interconnects. For this purpose, a set of analytical models is developed for on-chip data links in this thesis. First, a model is proposed for modeling crosstalk and intersymbol interference. The model takes into account the effects of inductance, initial states and bit sequences. Intersymbol interference is shown to affect crosstalk voltage and propagation delay depending on bus throughput and the amount of inductance. Next, a model is proposed for the switching current of a coupled bus. The model is combined with an existing model to evaluate power supply noise. The model is then applied to reduce both functional crosstalk and power supply noise caused by a bus as a trade-off with time. The proposed reduction method is shown to be effective in reducing long-range crosstalk noise. The effects of process variation on encoded signaling are then modeled. In encoded signaling, the input signals to a bus are encoded using additional signaling circuitry. The proposed model includes variation in both the signaling circuitry and in the wires to calculate the total delay variation of a bus. The model is applied to study level-encoded dual-rail and 1-of-4 signaling. In addition to regular voltage-mode and encoded voltage-mode signaling, current-mode signaling is a promising technique for global communication. A model for energy dissipation in RLC current-mode signaling is proposed in the thesis. The energy is derived separately for the driver, wire and receiver termination.Siirretty Doriast

On Co-Optimization Of Constrained Satisfiability Problems For Hardware Software Applications

Manufacturing technology has permitted an exponential growth in transistor count and density. However, making efficient use of the available transistors in the design has become exceedingly difficult. Standard design flow involves synthesis, verification, placement and routing followed by final tape out of the design. Due to the presence of various undesirable effects like capacitive crosstalk, supply noise, high temperatures, etc., verification/validation of the design has become a challenging problem. Therefore, having a good design convergence may not be possible within the target time, due to a need for a large number of design iterations. Capacitive crosstalk is one of the major causes of design convergence problems in deep sub-micron era. With scaling, the number of crosstalk violations has been increasing because of reduced inter-wire distances. Consequently only the most severe crosstalk faults are fixed pre-silicon while the rest are tested post-silicon. Testing for capacitive crosstalk involves generation of input patterns which can be applied post-silicon to the integrated circuit and comparison of the output response. These patterns are generated at the gate/ Register Transfer Level (RTL) of abstraction using Automatic Test Pattern Generation (ATPG) tools. In this dissertation, anInteger Linear Programming (ILP) based ATPG technique for maximizing crosstalk induced delay increase at the victim net, for multiple aggressor crosstalk faults, is presented. Moreover, various solutions for pattern generation considering both zero as well as unit delay models is also proposed. With voltage scaling, power supply switching noise has become one of the leading causes of signal integrity related failures in deep sub-micron designs. Hence, during power supply network design and analysis of power supply switching noise, computation of peak supply current is an essential step. Traditional peak current estimation approaches involve addition of peak current associated with all the CMOS gates which are switching in a combinational circuit. Consequently, this approach does not take the Boolean and temporal relationships of the circuit into account. This work presents an ILP based technique for generation of an input pattern pair which maximizes switching supply currents for a combinational circuit in the presence of integer gate delays. The input pattern pair generated using the above approach can be applied post-silicon for power droop testing. With high level of integration, Multi-Processor Systems on Chip (MPSoC) feature multiple processor cores and accelerators on the same die, so as to exploit the instruction level parallelism in the application. For hardware-software co-design, application programming model is based on a Task Graph, which represents task dependencies and execution/transfer times for various threads and processes within an application. Mapping an application to an MPSoC traditionally involves representing it in the form of a task graph and employing static scheduling in order to minimize the schedule length. Dynamic system behavior is not taken into consideration during static scheduling, while dynamic scheduling requires the knowledge of task graph at runtime. A run-time task graph extraction heuristic to facilitate dynamic scheduling is also presented here. A novel game theory based approach uses this extracted task graph to perform run-time scheduling in order to minimize total schedule length. With increase in transistor density, power density has gone up substantially. This has lead to generation of regions with very high temperature called Hotspots. Hotspots lead to reliability and performance issues and affect design convergence. In current generation Integrated Circuits (ICs) temperature is controlled by reducing power dissipation using Dynamic Thermal Management (DTM) techniques like frequency and/or voltage scaling. These techniques are reactive in nature and have detrimental effects on performance. Here, a look-ahead based task migration technique is proposed, in order to utilize the multitude of cores available in an MPSoC to eliminate thermal emergencies. Our technique is based on temperature prediction, leveraging upon a novel wavelet based thermal modeling approach. Hence, this work addresses several optimization problems that can be reduced to constrained max-satisfiability, involving integer as well as Boolean constraints in hardware and software domains. Moreover, it provides domain specific heuristic solutions for each of them

Discrete Gate Sizing Methodologies for Delay, Area and Power Optimization

The modeling of an individual gate and the optimization of circuit performance has long been a critical issue in the VLSI industry. In this work, we first study of the gate sizing problem for today\u27s industrial designs, and explore the contributions and limitations of all the existing approaches, which mainly suffer from producing only continuous solutions, using outdated timing models or experiencing performance inefficiency. In this dissertation, we present our new discrete gate sizing technique which optimizes different aspects of circuit performance, including delay, area and power consumption. And our method is fast and efficient as it applies the local search instead of global exhaustive search during gate size selection process, which greatly reduces the search space and improves the computation complexity. In addition to that, it is also flexible with different timing models, and it is able to deal with the constraints of input/output slew and output load capacitance, under which very few previous research works were reported. We then propose a new timing model, which is derived from the classic Elmore delay model, but takes the features of modern timing models from standard cell library. With our new timing model, we are able to formulate the combinatorial discrete sizing problem as a simplified mathematical expression and apply it to existing Lagrangian relaxation method, which is shown to converge to optimal solution. We demonstrate that the classic Elmore delay model based gate sizing approaches can still be valid. Therefore, our work might provide a new look into the numerous Elmore delay model based research works in various areas (such as placement, routing, layout, buffer insertion, timing analysis, etc.)

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

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities

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

High-performance Global Routing for Trillion-gate Systems-on-Chips.

Due to aggressive transistor scaling, modern-day CMOS circuits have continually increased in both complexity and productivity. Modern semiconductor designs have narrower and more resistive wires, thereby shifting the performance bottleneck to interconnect delay. These trends considerably impact timing closure and call for improvements in high-performance physical design tools to keep pace with the current state of IC innovation. As leading-edge designs may incorporate tens of millions of gates, algorithm and software scalability are crucial to achieving reasonable turnaround time. Moreover, with decreasing device sizes, optimizing traditional objectives is no longer sufficient. Our research focuses on (i) expanding the capabilities of standalone global routing, (ii) extending global routing for use in different design applications, and (iii) integrating routing within broader physical design optimizations and flows, e.g., congestion-driven placement. Our first global router relies on integer-linear programming (ILP), and can solve fairly large problem instances to optimality. Our second iterative global router relies on Lagrangian relaxation, where we relax the routing violation constraints to allowing routing overflow at a penalty. In both approaches, our desire is to give the router the maximum degree of freedom within a specified context. Empirically, both routers produce competitive results within a reasonable amount of runtime. To improve routability, we explore the incorporation of routing with placement, where the router estimates congestion and feeds this information to the placer. In turn, the emphasis on runtime is heightened, as the router will be invoked multiple times. Empirically, our placement-and-route framework significantly improves the final solution’s routability than performing the steps sequentially. To further enhance routability-driven placement, we (i) leverage incrementality to generate fast and accurate congestion maps, and (ii) develop several techniques to relieve cell-based and layout-based congestion. To broaden the scope of routing, we integrate a global router in a chip-design flow that addresses the buffer explosion problem.PHDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98025/1/jinhu_1.pd

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Energy-aware synthesis for networks on chip architectures

The Network on Chip (NoC) paradigm was introduced as a scalable communication infrastructure for future System-on-Chip applications. Designing application specific customized communication architectures is critical for obtaining low power, high performance solutions. Two significant design automation problems are the creation of an optimized configuration, given application requirement the implementation of this on-chip network. Automating the design of on-chip networks requires models for estimating area and energy, algorithms to effectively explore the design space and network component libraries and tools to generate the hardware description. Chip architects are faced with managing a wide range of customization options for individual components, routers and topology. As energy is of paramount importance, the effectiveness of any custom NoC generation approach lies in the availability of good energy models to effectively explore the design space. This thesis describes a complete NoC synthesis flow, called NoCGEN, for creating energy-efficient custom NoC architectures. Three major automation problems are addressed: custom topology generation, energy modeling and generation. An iterative algorithm is proposed to generate application specific point-to-point and packet-switched networks. The algorithm explores the design space for efficient topologies using characterized models and a system-level floorplanner for evaluating placement and wire-energy. Prior to our contribution, building an energy model required careful analysis of transistor or gate implementations. To alleviate the burden, an automated linear regression-based methodology is proposed to rapidly extract energy models for many router designs. The resulting models are cycle accurate with low-complexity and found to be within 10% of gate-level energy simulations, and execute several orders of magnitude faster than gate-level simulations. A hardware description of the custom topology is generated using a parameterizable library and custom HDL generator. Fully reusable and scalable network components (switches, crossbars, arbiters, routing algorithms) are described using a template approach and are used to compose arbitrary topologies. A methodology for building and composing routers and topologies using a template engine is described. The entire flow is implemented as several demonstrable extensible tools with powerful visualization functionality. Several experiments are performed to demonstrate the design space exploration capabilities and compare it against a competing min-cut topology generation algorithm

Secure Physical Design

An integrated circuit is subject to a number of attacks including information leakage, side-channel attacks, fault-injection, malicious change, reverse engineering, and piracy. Majority of these attacks take advantage of physical placement and routing of cells and interconnects. Several measures have already been proposed to deal with security issues of the high level functional design and logic synthesis. However, to ensure end-to-end trustworthy IC design flow, it is necessary to have security sign-off during physical design flow. This paper presents a secure physical design roadmap to enable end-to-end trustworthy IC design flow. The paper also discusses utilization of AI/ML to establish security at the layout level. Major research challenges in obtaining a secure physical design are also discussed