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Based on the current widespread use of underwater vehicles, a special type of underwater glider equipped with energy-saving diamond-structured rotatable wings that can improve the underwater vehicle's lift-drag ratio optimize hydrodynamic performance, and enhance flight quality was studied. With the support of adaptive meshing technology and Fluent's epsilon standard turbulence model, lift and drag...
In this paper, the conceptual design with integrating motion control and considering the cross current was applied to establish a submarine motion simulator, where the path motion stability is evaluated. The methods used to construct the simulator include the standard navigation approach by applying the LOS algorithms and PD control Euler-Rodriguez quaternion for conversion between submarines motion...
Algebraic multigrid (AMG) is a class of high-performance linear solvers based on multigrid principles. Compared to geometric multigrid (GMG) solvers that rely on the geometric information of underlying problems, AMG solvers build hierarchical coarse level problems according to the input matrices. Graph-theoretic Algebraic Multigrid (AMG) algorithms have emerged for solving large Symmetric Diagonally...
Vectorless integrity verification is becoming increasingly critical to robust design of nanoscale power delivery networks (PDNs). To dramatically improve efficiency and capability of vectorless integrity verifications, this paper introduces a scalable multilevel integrity verification framework by leveraging a hierarchy of almost linear-sized spectral power grid sparsifiers that can well retain effective...
TinySPICE was a SPICE simulator on GPU developed to achieve dramatic speedups in statistical simulations of small nonlinear circuits, such as standard cell designs and SRAMs. While TinySPICE can perform circuit simulations much faster than traditional SPICE tools for small circuits, it may not be efficient for handling relatively large logic/memory circuit designs due to the embedded dense MNA matrix...
Spectral graph sparsification aims to find an ultra-sparse subgraph whose Laplacian matrix can well approximate the original Laplacian matrix in terms of its eigenvalues and eigenvectors. The resultant sparsified subgraph can be efficiently leveraged as a proxy in a variety of numerical computation applications and graph-based algorithms. This paper introduces a practically efficient, nearly-linear...
Harmonic Balance (HB) analysis is key to efficient verification of large post-layout RF and microwave integrated circuits (ICs). This paper introduces a novel transient-simulation guided graph sparsification technique, as well as an efficient runtime performance modeling approach tailored for heterogeneous manycore CPU-GPU computing system to build nearly-optimal subgraph preconditioners that can...
Existing state-of-the-art realizable RC reduction methods may not be suitable for scalable power grid reductions due to the fast growing computational complexity and the large number of ports. In this work, we present a scalable power grid reduction method for reducing large-scale flip-chip power grids based on recent spectral graph sparsification techniques. The first step of the proposed approach...
Unlike traditional fast SPICE simulation techniques that rely on a variety of approximation approaches to trade off simulation accuracy for greater speed, SPICE-accurate integrated circuit (IC) simulations can truthfully predict circuit electrical behaviors, and therefore become indispensable for verification of large IC designs. Post-layout SPICE-accurate simulation should be able to encapsulate...
In the past decades, harmonic balance (HB) has been widely used for computing steady-state solutions of nonlinear radio-frequency (RF) and microwave circuits. However, using HB for simulating strongly nonlinear RF circuits still remains a very challenging task. Although direct solution methods can be adopted to handle moderate to strong nonlinearities in HB analysis, such methods do not scale efficiently...
In nowadays variation-aware IC designs, cell characterizations and SRAMmemory yield analysis require many thousands or even millions of repeated SPICE simulations for relatively small nonlinear circuits. In this work, we present a massively parallel SPICE simulator on GPU, TinySPICE, for efficiently analyzing small nonlinear circuits, such as standard cell designs, SRAMs, etc. In order to gain high...
To deal with the growing phenomenon of electromigration (EM), power grid current integrity verification becomes indispensable to designing reliable power delivery networks (PDNs). Unlike previous works that focus on vectorless voltage integrity verification of power grids, in this work, for the first time we present a scalable vectorless power grid current integrity verification framework. By taking...
In recent years, social media has changed the way we interact and communicate. Although the existing structure of social media allows users to easily create, receive, and propagate pieces of information, many a time, users do not have background knowledge about the received information, including the provenance (sources or originators) of information, and other recipients who may have retransmitted...
To improve the efficiency of direct solution methods in SPICE-accurate nonlinear circuit simulations, preconditioned iterative solution techniques have been widely studied in the past decades. However, it still has been an extremely challenging task to develop general-purpose preconditioning methods that can deal with various large-scale nonlinear circuit simulations. In this work, a novel circuit-oriented,...
SPICE-accurate simulation of present-day large-scale nonlinear integrated circuit (IC) systems with millions of linear/nonlinear components can be prohibitively expensive, and thus extremely challenging. In this paper, we present a novel support-circuit preconditioning (SCP) technique for tackling large-scale nonlinear circuit simulations by exploiting sparsified graphs of a given circuit network...
It is increasingly challenging to analyze present day large-scale power delivery networks (PDNs) due to the drastically growing complexity in power grid design. To achieve greater runtime and memory efficiencies, a variety of preconditioned iterative algorithms has been investigated in the past few decades with promising performance, while incremental power grid analysis also becomes popular to facilitate...
Large VLSI on-chip power delivery networks (PDN) are challenging to analyze due to sheer network complexity. In this paper, three power grid solvers developed in our group: a direct solver using Cholesky decomposition, a GPU-based multigrid preconditioning solver, and a partitioning-based solver using spatial locality, are reviewed. Following the requirements of TAU 2011 Power Grid Simulation Contest,...
Multi-core architecture has emerged as the primary architectural choice to achieve power-efficient computing in microprocessors and SoCs. Power gating is indispensable for system power and thermal management and well suited for multi-core architectures. However, checking the power integrity (such as electromigration and voltage drop) of large gated power delivery networks (PDNs) presents a significant...
To facilitate full chip capacitance extraction, field solvers are typically deployed for characterizing capacitance libraries for various interconnect structures and configurations. In the past decades, various algorithms for accelerating boundary element methods (BEM) have been developed to improve the efficiency of field solvers for capacitance extraction. This paper presents the first massively...
While effective thermal management for 3D-ICs is becoming increasingly challenging due to the ever increasing power density and chip design complexity, traditional heat sinks are expected to quickly reach their limits for meeting the cooling needs of 3D-ICs. Alternatively, integrated liquid-cooled microchannel heat sink becomes one of the most effective solutions. For the first time, we present fast...
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