Parallel algorithms for inductance extraction

In VLSI circuits, signal delays play an important role in design, timing verification and signal integrity checks. These delays are attributed to the presence of parasitic resistance, capacitance and inductance. With increasing clock speed and reducing feature sizes, these delays will be dominated b...

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Main Author: Mahawar, Hemant
Other Authors: Sarin, Vivek
Format: Others
Language:en_US
Published: Texas A&M University 2007
Subjects:
Online Access:http://hdl.handle.net/1969.1/5930
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spelling ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-59302013-01-08T10:38:52ZParallel algorithms for inductance extractionMahawar, HemantPreconditioningInductance ExtractionParallel AlgorithmsMixed Mode ParallelizationIterative MethodsIn VLSI circuits, signal delays play an important role in design, timing verification and signal integrity checks. These delays are attributed to the presence of parasitic resistance, capacitance and inductance. With increasing clock speed and reducing feature sizes, these delays will be dominated by parasitic inductance. In the next generation VLSI circuits, with more than millions of components and interconnect segments, fast and accurate inductance estimation becomes a crucial step. A generalized approach for inductance extraction requires the solution of a large, dense, complex linear system that models mutual inductive effects among circuit elements. Iterative methods are used to solve the system without explicit computation of the system matrix itself. Fast hierarchical techniques are used to compute approximate matrix-vector products with the dense system matrix in a matrix-free way. Due to unavailability of system matrix, constructing a preconditioner to accelerate the convergence of the iterative method becomes a challenging task. This work presents a class of parallel algorithms for fast and accurate inductance extraction of VLSI circuits. We use the solenoidal basis approach that converts the linear system into a reduced system. The reduced system of equations is solved by a preconditioned iterative solver that uses fast hierarchical methods to compute products with the dense coefficient matrix. A Green’s function based preconditioner is proposed that achieves near-optimal convergence rates in several cases. By formulating the preconditioner as a dense matrix similar to the coefficient matrix, we are able to use fast hierarchical methods for the preconditioning step as well. Experiments on a number of benchmark problems highlight the efficient preconditioning scheme and its advantages over FastHenry. To further reduce the solution time of the software, we have developed a parallel implementation. The parallel software package is capable of analyzing interconnects con- figurations involving several conductors within reasonable time. A two-tier parallelization scheme enables mixed mode parallelization, which uses both OpenMP and MPI directives. The parallel performance of the software is demonstrated through experiments on the IBM p690 and AMD Linux clusters. These experiments highlight the portability and efficiency of the software on multiprocessors with shared, distributed, and distributed-shared memory architectures.Texas A&M UniversitySarin, Vivek2007-09-17T19:38:28Z2007-09-17T19:38:28Z2003-052007-09-17T19:38:28ZBookThesisElectronic Dissertationtext785600 byteselectronicapplication/pdfborn digitalhttp://hdl.handle.net/1969.1/5930en_US
collection NDLTD
language en_US
format Others
sources NDLTD
topic Preconditioning
Inductance Extraction
Parallel Algorithms
Mixed Mode Parallelization
Iterative Methods
spellingShingle Preconditioning
Inductance Extraction
Parallel Algorithms
Mixed Mode Parallelization
Iterative Methods
Mahawar, Hemant
Parallel algorithms for inductance extraction
description In VLSI circuits, signal delays play an important role in design, timing verification and signal integrity checks. These delays are attributed to the presence of parasitic resistance, capacitance and inductance. With increasing clock speed and reducing feature sizes, these delays will be dominated by parasitic inductance. In the next generation VLSI circuits, with more than millions of components and interconnect segments, fast and accurate inductance estimation becomes a crucial step. A generalized approach for inductance extraction requires the solution of a large, dense, complex linear system that models mutual inductive effects among circuit elements. Iterative methods are used to solve the system without explicit computation of the system matrix itself. Fast hierarchical techniques are used to compute approximate matrix-vector products with the dense system matrix in a matrix-free way. Due to unavailability of system matrix, constructing a preconditioner to accelerate the convergence of the iterative method becomes a challenging task. This work presents a class of parallel algorithms for fast and accurate inductance extraction of VLSI circuits. We use the solenoidal basis approach that converts the linear system into a reduced system. The reduced system of equations is solved by a preconditioned iterative solver that uses fast hierarchical methods to compute products with the dense coefficient matrix. A Green’s function based preconditioner is proposed that achieves near-optimal convergence rates in several cases. By formulating the preconditioner as a dense matrix similar to the coefficient matrix, we are able to use fast hierarchical methods for the preconditioning step as well. Experiments on a number of benchmark problems highlight the efficient preconditioning scheme and its advantages over FastHenry. To further reduce the solution time of the software, we have developed a parallel implementation. The parallel software package is capable of analyzing interconnects con- figurations involving several conductors within reasonable time. A two-tier parallelization scheme enables mixed mode parallelization, which uses both OpenMP and MPI directives. The parallel performance of the software is demonstrated through experiments on the IBM p690 and AMD Linux clusters. These experiments highlight the portability and efficiency of the software on multiprocessors with shared, distributed, and distributed-shared memory architectures.
author2 Sarin, Vivek
author_facet Sarin, Vivek
Mahawar, Hemant
author Mahawar, Hemant
author_sort Mahawar, Hemant
title Parallel algorithms for inductance extraction
title_short Parallel algorithms for inductance extraction
title_full Parallel algorithms for inductance extraction
title_fullStr Parallel algorithms for inductance extraction
title_full_unstemmed Parallel algorithms for inductance extraction
title_sort parallel algorithms for inductance extraction
publisher Texas A&M University
publishDate 2007
url http://hdl.handle.net/1969.1/5930
work_keys_str_mv AT mahawarhemant parallelalgorithmsforinductanceextraction
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