Noise-Constrained Performance Optimization by Simultaneous Gate and Wire Sizing Based on Lagrangian Relaxation

Noise, as well as area, delay, and power, is one of the most important concerns in the design of deep sub-micron ICs. Currently existing algorithms can not handle simultaneous switching conditions of signals for noise minimization. In this paper, we model not only physical coupling capacitance, but also simultaneous switching behavior for noise optimization. Based on Lagrangian relaxation, we present an algorithm that can optimally solve the simultaneous noise, area, delay, and power optimization problem by sizing circuit components. Our algorithm, with linear memory requirement overall and linear runtime per iteration, is very effective and efficient. For example, for a circuit of 6144 wires and 3512 gates, our algorithm solves the simultaneous optimization problem using only 2.1 MB memory and 47 minute runtime to achieve the precision of within 1% error on a SUN UltraSPARC-I workstation

Interconnect delay modeling under exponential input

Interconnect has become the dominating factor in determining the performance of VLSI deep submicron designs. With the rapid shrinking of feature size and development in the process technologies, it has been observed that the resistance per unit length of the interconnect continues to increase, capacitance per unit length remains roughly constant, and transistor or gate delay continues to decrease. This had led to the increasing dominance of interconnect delay over logic delay, and this trend is expected to continue. With this being the main bottleneck in realizing high speed circuits, complete understanding of the interconnect delay and thereby efficient and accurate delay circulation has assumed a greater significance in physical design, optimization and fast verification. In this thesis, a interconnect delay model under exponential input is presented. Because of its simple closed form expression, fast computation speed, and fidelity with respect to simulation, Elmore delay model remains popular. More accurate delay computation methods are typically central processing unit intensive and/or difficult to implement. To bridge this gap between accuracy and efficiency/simplicity, a new RC delay metric for interconnects which is as efficient as the Elmore metric, but more accurate, is proposed. However, there is no interconnect delay model considering exponential input waveform existing in the literature. The proposed Exponential Delay Metric uses exponential waveform as input and captures resistive shielding effects by modeling the downstream by a [pi]-model. An application of the delay model to perform interconnect optimization using wire sizing is also presented. Experimental results show that the proposed delay model is significantly more accurate than the existing interconnect delay models

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.)

Performance and power optimization in VLSI physical design

As VLSI technology enters the nanoscale regime, a great amount of efforts have been made to reduce interconnect delay. Among them, buffer insertion stands out as an effective technique for timing optimization. A dramatic rise in on-chip buffer density has been witnessed. For example, in two recent IBM ASIC designs, 25% gates are buffers. In this thesis, three buffer insertion algorithms are presented for the procedure of performance and power optimization. The second chapter focuses on improving circuit performance under inductance effect. The new algorithm works under the dynamic programming framework and runs in provably linear time for multiple buffer types due to two novel techniques: restrictive cost bucketing and efficient delay update. The experimental results demonstrate that our linear time algorithm consistently outperforms all known RLC buffering algorithms in terms of both solution quality and runtime. That is, the new algorithm uses fewer buffers, runs in shorter time and the buffered tree has better timing. The third chapter presents a method to guarantee a high fidelity signal transmission in global bus. It proposes a new redundant via insertion technique to reduce via variation and signal distortion in twisted differential line. In addition, a new buffer insertion technique is proposed to synchronize the transmitted signals, thus further improving the effectiveness of the twisted differential line. Experimental results demonstrate a 6GHz signal can be transmitted with high fidelity using the new approaches. In contrast, only a 100MHz signal can be reliably transmitted using a single-end bus with power/ground shielding. Compared to conventional twisted differential line structure, our new techniques can reduce the magnitude of noise by 45% as witnessed in our simulation. The fourth chapter proposes a buffer insertion and gate sizing algorithm for million plus gates. The algorithm takes a combinational circuit as input instead of individual nets and greatly reduces the buffer and gate cost of the entire circuit. The algorithm has two main features: 1) A circuit partition technique based on the criticality of the primary inputs, which provides the scalability for the algorithm, and 2) A linear programming formulation of non-linear delay versus cost tradeoff, which formulates the simultaneous buffer insertion and gate sizing into linear programming problem. Experimental results on ISCAS85 circuits show that even without the circuit partition technique, the new algorithm achieves 17X speedup compared with path based algorithm. In the meantime, the new algorithm saves 16.0% buffer cost, 4.9% gate cost, 5.8% total cost and results in less circuit delay

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

Physical design algorithms for asynchronous circuits

Asynchronous designs have been demonstrated to be able to achieve both higher performance and lower power compared with their synchronous counterparts. It provides a very promising solution to the emerging challenges in advanced technology. However, due to the lack of proper EDA tool support, the design cycle for asynchronous circuits is much longer compared with the one for synchronous circuits. Thus, even with many advantages, asynchronous circuits are still not the mainstream in the industry. In this thesis, we provides several algorithms to resolve the emerging issues for the physical design of asynchronous circuits. Our proposed algorithms optimize asynchronous circuits using placement, gate sizing, repeater insertion and pipeline buffer insertion techniques. An incremental maximum cycle ratio algorithm is also proposed to speed up the timing analysis of asynchronous circuits

Lagrangian relaxation-based multi-threaded discrete gate sizer

In integrated circuit design gate sizing is one of the key optimization techniques which is repeatedly invoked to trade-off delays for area and/or power of the gates during logic design and physical design stages. With increasing design sizes of a million gates and larger, discrete gate sizes and non-convex delay models the gate sizing algorithms that were designed for continuous sizes and convex delay models are slow and timing inaccurate. Of the several published discrete gate sizing algorithms, recent works have shown that Lagrangian relaxation based gate sizers have produced designs with the lowest power on average with high timing accuracy. But they are also very slow due to a large number of expensive timing updates spread across hundreds of iterations of solving the Lagrangian sub-problem. In this thesis we present a Lagrangian relaxation based multi-threaded discrete gate sizer for fast timing and power reduction by swapping the gate sizes and the threshold voltages. We developed two parallelization enabling techniques to reduce the runtime of Lagrangian sub-problem solver, namely, mutual exclusion edge (MEE) assignment and directed acyclic graph (DAG) based netlist traversal. MEEs are dummy edges assigned to reduce computational dependencies among gates sharing one or more common fan-ins. DAG based netlist traversal facilitates simultaneous resizing of gates belonging to different topological levels. We designed a Lagrange multiplier update framework that enables rapid convergence of the timing recovery and power recovery algorithms. To reduce the runtime of timing updates, we proposed a simple and fast-to-compute effective capacitance model and several mechanisms to calibrate the timing models to improve their accuracy. Compared to the state-of-the-art gate sizer, our proposed gate sizer is on average 15x faster and the optimized designs have only 1.7\% higher power. In digital synchronous designs simultaneous gate sizing and clock skew scheduling provides significantly more power saving. We extend the gate sizer to simultaneously schedule the clock skew. It can achieve an average of 18.8\% more reduction in power with only 20\% increase in the runtime

Scalable Analysis, Verification and Design of IC Power Delivery

Due to recent aggressive process scaling into the nanometer regime, power delivery network design faces many challenges that set more stringent and specific requirements to the EDA tools. For example, from the perspective of analysis, simulation efficiency for large grids must be improved and the entire network with off-chip models and nonlinear devices should be able to be analyzed. Gated power delivery networks have multiple on/off operating conditions that need to be fully verified against the design requirements. Good power delivery network designs not only have to save the wiring resources for signal routing, but also need to have the optimal parameters assigned to various system components such as decaps, voltage regulators and converters. This dissertation presents new methodologies to address these challenging problems. At first, a novel parallel partitioning-based approach which provides a flexible network partitioning scheme using locality is proposed for power grid static analysis. In addition, a fast CPU-GPU combined analysis engine that adopts a boundary-relaxation method to encompass several simulation strategies is developed to simulate power delivery networks with off-chip models and active circuits. These two proposed analysis approaches can achieve scalable simulation runtime. Then, for gated power delivery networks, the challenge brought by the large verification space is addressed by developing a strategy that efficiently identifies a number of candidates for the worst-case operating condition. The computation complexity is reduced from O(2^N) to O(N). At last, motivated by a proposed two-level hierarchical optimization, this dissertation presents a novel locality-driven partitioning scheme to facilitate divide-and-conquer-based scalable wire sizing for large power delivery networks. Simultaneous sizing of multiple partitions is allowed which leads to substantial runtime improvement. Moreover, the electric interactions between active regulators/converters and passive networks and their influences on key system design specifications are analyzed comprehensively. With the derived design insights, the system-level co-design of a complete power delivery network is facilitated by an automatic optimization flow. Results show significant performance enhancement brought by the co-design

Performance and power optimization in VLSI physical design

As VLSI technology enters the nanoscale regime, a great amount of efforts have been made to reduce interconnect delay. Among them, buffer insertion stands out as an effective technique for timing optimization. A dramatic rise in on-chip buffer density has been witnessed. For example, in two recent IBM ASIC designs, 25% gates are buffers. In this thesis, three buffer insertion algorithms are presented for the procedure of performance and power optimization. The second chapter focuses on improving circuit performance under inductance effect. The new algorithm works under the dynamic programming framework and runs in provably linear time for multiple buffer types due to two novel techniques: restrictive cost bucketing and efficient delay update. The experimental results demonstrate that our linear time algorithm consistently outperforms all known RLC buffering algorithms in terms of both solution quality and runtime. That is, the new algorithm uses fewer buffers, runs in shorter time and the buffered tree has better timing. The third chapter presents a method to guarantee a high fidelity signal transmission in global bus. It proposes a new redundant via insertion technique to reduce via variation and signal distortion in twisted differential line. In addition, a new buffer insertion technique is proposed to synchronize the transmitted signals, thus further improving the effectiveness of the twisted differential line. Experimental results demonstrate a 6GHz signal can be transmitted with high fidelity using the new approaches. In contrast, only a 100MHz signal can be reliably transmitted using a single-end bus with power/ground shielding. Compared to conventional twisted differential line structure, our new techniques can reduce the magnitude of noise by 45% as witnessed in our simulation. The fourth chapter proposes a buffer insertion and gate sizing algorithm for million plus gates. The algorithm takes a combinational circuit as input instead of individual nets and greatly reduces the buffer and gate cost of the entire circuit. The algorithm has two main features: 1) A circuit partition technique based on the criticality of the primary inputs, which provides the scalability for the algorithm, and 2) A linear programming formulation of non-linear delay versus cost tradeoff, which formulates the simultaneous buffer insertion and gate sizing into linear programming problem. Experimental results on ISCAS85 circuits show that even without the circuit partition technique, the new algorithm achieves 17X speedup compared with path based algorithm. In the meantime, the new algorithm saves 16.0% buffer cost, 4.9% gate cost, 5.8% total cost and results in less circuit delay