We explore Krylov subspace algorithms to calculate φ functions of exponential integrators for circuit simulation. Higham [1] pointed out the potential numerical stability risk of φ functions computation. However, for the applications to circuit analysis, the choice of methods remains open. This work inspects the accuracy of matrix exponential and vector product with Krylov subspace methods, and identifies the proper approach to achieving numerically stable solutions for nonlinear circuits. Empirial results verify the quality of the proposed methods using various orders of φ functions. Furthermore, instead of Newton-Raphson (NR) iterations in conventional methods, an iterative residue correction algorithm is devised for nonlinear system analysis. The stability and efficiency of our methods are illustrated with experiments.

We propose a flat, analytic, mixed-size placement algorithm ePlace-3D for three-dimension integrated circuits (3D-ICs) using nonlinear optimization. Our contributions are (1) electrostatics based 3D density function with globally uniform smoothness (2) 3D numerical solution with improved spectral formulation (3) 3D nonlinear pre-conditioner for convergence acceleration (4) interleaved 2D-3D placement for efficiency enhancement. Our placer outperforms the leading work mPL6-3D and NTUplace3-3D with 6.44% and 37.15% shorter wirelength, 9.11% and 10.27% fewer 3D vertical interconnects (VI) on average of IBM-PLACE circuits. Validation on the large-scale modern mixed-size (MMS) 3D circuits shows high performance and scalability.

This paper presents a new transient electro-thermal simulation method for fast 3-D chip-level analysis of power electronics with field solver accuracy. The metallization stack and substrate are meshed and solved with 3-D field solver using nonlinear temperature-dependent electrical and thermal parameters, and the active transistors are modeled with table models to avoid time-consuming technology computer-aided design simulation. Two contributions are made to enhance the physical relevance and the computational performance: 1) the capacitive effects, including interconnect parasitic capacitance and gate capacitance of power devices with nonlinear dependence on bias and temperature, are explicitly accounted for and 2) a specialized nonlinear exponential integrator (EI) method is developed to address the considerably different time scales between electrical and thermal sectors. The EI-based transient solver allows the electrical system to step with much larger time steps than in conventional methods, thus the time step gap between the electrical and the thermal simulation is largely reduced.

We design an algorithmic framework using matrix exponentials for time-domain simulation of power delivery network (PDN). Our framework can reuse factorized matrices to simulate the large-scale linear PDN system with variable stepsizes. In contrast, current conventional PDN simulation solvers have to use fixed step-size approach in order to reuse factorized matrices generated by the expensive matrix decomposition. Based on the proposed exponential integration framework, we design a PDN solver R-MATEX with the flexible time-stepping capability. The key operation of matrix exponential and vector product is computed by the rational Krylov subspace method. To further improve the runtime, we also propose a distributed computing framework DR-MATEX. DR-MATEX reduces Krylov subspace generations caused by frequent breakpoints from a large number of current sources during simulation. By virtue of the superposition property of linear system and scaling invariance property of Krylov subspace, DR-MATEX can divide the whole simulation task into subtasks based on the alignments of breakpoints among those sources. The subtasks are processed in parallel at different computing nodes without any communication during the computation of transient simulation. The final result is obtained by summing up the partial results among all the computing nodes after they finish the assigned subtasks. Therefore, our computation model belongs to the category known as embarrassingly parallel model. Experimental results show R-MATEX and DR-MATEX can achieve up to around 14.4× and 98.0× runtime speedups over traditional trapezoidal integration-based solver with fixed time-step approach.

We propose an efficient algorithmic framework for time-domain circuit simulation using exponential integrators. This work addresses several critical issues exposed by previous matrix exponential based circuit simulation research, and makes it capable of simulating stiff nonlinear circuit system at a large scale. In this framework, the system's nonlinearity is treated with exponential Rosenbrock-Euler formulation. The matrix exponential and vector product is computed using invert Krylov subspace method. Our proposed method has several distinguished advantages over conventional formulations (e.g., the well-known backward Euler with Newton-Raphson method). The matrix factorization is performed only for the conductance/resistance matrix G, without being performed for the combinations of the capacitance/inductance matrix C and matrix G, which are used in traditional implicit formulations. Furthermore, due to the explicit nature of our formulation, we do not need to repeat LU decompositions when adjusting the length of time steps for error controls. Our algorithm is better suited to solving tightly coupled post-layout circuits in the pursuit for full-chip simulation. Our experimental results validate the advantages of our framework.

We propose an electrostatics-based placement algorithm for large-scale mixed-size circuits (ePlace-MS). ePlace-MS is generalized, flat, analytic and nonlinear. The density modeling method eDensity is extended to handle the mixed-size placement. We conduct detailed analysis on the correctness of the gradient formulation and the numerical solution, as well as the rationale of dc removal and the advantages over prior density functions. Nesterov's method is used as the nonlinear solver, which shows high yet stable performance over mixed-size circuits. The steplength is set as the inverse of Lipschitz constant of the gradient function, while we develop a backtracking method to prevent overestimation. An approximated nonlinear preconditioner is developed to minimize the topological and physical differences between large macros and standard cells. Besides, we devise a simulated annealer to legalize the layout of macros and use a second-phase global placement to reoptimize the standard cell layout. All the above innovations are integrated into our mixed-size placement prototype ePlace-MS, which outperforms all the related works in literature with better quality and efficiency. Compared to the leading-edge mixed-size placer NTUplace3, ePlace-MS produces up to 22.98% and on average 8.22% shorter wirelength over all the 16 modern mixed-size benchmark circuits with the same runtime.

We proposed MATEX, a distributed framework for transient simulation of power distribution networks (PDNs). MATEX utilizes matrix exponential kernel with Krylov subspace approximations to solve differential equations of linear circuit. First, the whole simulation task is divided into subtasks based on decompositions of current sources, in order to reduce the computational overheads. Then these subtasks are distributed to different computing nodes and processed in parallel. Within each node, after the matrix factorization at the beginning of simulation, the adaptive time stepping solver is performed without extra matrix re-factorizations. MATEX overcomes the stiffness hinder of previous matrix exponential-based circuit simulator by rational Krylov subspace method, which leads to larger step sizes with smaller dimensions of Krylov subspace bases and highly accelerates the whole computation. MATEX outperforms both traditional fixed and adaptive time stepping methods, e.g., achieving around 13X over the trapezoidal framework with fixed time step for the IBM power grid benchmarks.

The floating random walk (FRW) algorithm is an important field-solver algorithm for capacitance extraction, which has several merits compared with other boundary element method (BEM) based algorithms. In this paper, the FRW algorithm is accelerated with the modern graphics processing units (GPUs). We propose an iterative GPU-based FRW algorithm flow and the technique using an inverse cumulative probability array (ICPA), to reduce the divergence among walks and the global-memory accessing. A variant FRW scheme is proposed to utilize the benefit of ICPA, so that it accelerates the extraction of multi-dielectric structures. The technique for extracting multiple nets concurrently is also discussed. Numerical results show that our GPU-based FRW brings over 20X speedup for various test cases with 0.5% convergence criterion over the CPU counterpart. For the extraction of multiple nets, our GPU-based FRW outperforms the CPU counterpart by up to 59X.

A floating random walk (FRW) solver, called RWCap, is presented for the capacitance extraction of very-large-scale integration (VLSI) interconnects. An approach, including the numerical characterization of the cross-interface transition probability and weight value, is proposed to accelerate the extraction of structures with multiple dielectric layers. A comprehensive variance reduction scheme based on the importance sampling and stratified sampling is proposed to improve the convergence rate of the FRW algorithm. Finally, the space management technique using an octree data structure and the parallel computing technique are presented to further improve the efficiency. Numerical experiments are carried out with the test cases generated under the 180 and 45-nm process technologies. They demonstrate that the proposed multidielectric FRW algorithm achieves up to 160× speedup over the FRW algorithm using spherical transition domains to cross dielectric interface, with very small memory overhead. The variance reduction techniques further bring 3× or more speedup without memory overhead and the loss of accuracy. The RWCap also outperforms other existing FRW algorithm and fast boundary element method solvers in terms of computational time or scalability. The experiments on an 8-core CPU machine show that the parallel RWCap is over 6× faster than its serial-computing version.

The floating random walk (FRW) algorithm has several advantages for extracting 3D interconnect capacitance. However, for multi-layer dielectrics in VLSI technology, the efficiency of FRW algorithm would be degraded due to frequent stop of walks at dielectric interface and constraint of first-hop length especially in thin dielectrics. In this paper, we tackle these problems with the numerical characterization of Green's function for cross-interface transition probabilities and the corresponding weight value. We also present a space management technique with Octree data structure to reduce the time of each hop and parallelize the whole FRW by multi-threaded programming. Numerical results show large speedup brought by the proposed techniques for structures under the VLSI technology with thin dielectric layers.