Add to ORKGSolving a system of linear simultaneous equations representing an electrical circuit is one of the most time consuming tasks for large scale circuit simulations. In order to facilitate a multiprocessor implementation of the circuit simulation program SPICE, a decomposition algorithm is employed to partition the sparse matrix equution qf an overall circuit into a number of sub-circuit equations for parallel processing. In this paper, various implementation and performance tuning issues of a parallel direct method matrix equation solving routine is reported This routine is written in such a manner that the data structure is compatible with SPICE Version 3CI. The speed-up obtained for the simulation of several test circuits on a message passin...
This paper describes a methodology for solving efficiently the sparse network equations on multiproc...
Efficient multiprocessing approaches to the execution of digital computer programs, which analyse po...
International audienceIn this paper, the performance of a parallel sparse direct solver on a shared ...
Sparse-matrix solution is a dominant part of execution time in simulating VLSI circuits by a detaile...
As part of our effort to parallelise SPICE simulations over multiple FPGAs, we present a parallel FP...
A general approach to parallelizing direct method circuit simulation has been developed via novel al...
This book describes algorithmic methods and parallelization techniques to design a parallel sparse d...
Fine-grained dataflow processing of sparse matrix-solve computation (Ax = b) in the SPICE circuit si...
Abstract—SPICE is widely used for transistor-level circuit simulation. However, with the growing com...
Fine-grained dataflow processing of sparse Matrix-Solve computation (A~x = ~b) in the SPICE circuit ...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
SPICE, from the University of California, at Berkeley, is the de facto world standard for circuit si...
[[abstract]]This paper describes a sparse matrix solver for a circuit simulation. For simulation spe...
A coarse-grain parallel implementation is presented of LU factorisation, forward and backward substi...
This paper describes a methodology for solving efficiently the sparse network equations on multiproc...
Efficient multiprocessing approaches to the execution of digital computer programs, which analyse po...
International audienceIn this paper, the performance of a parallel sparse direct solver on a shared ...
Sparse-matrix solution is a dominant part of execution time in simulating VLSI circuits by a detaile...
As part of our effort to parallelise SPICE simulations over multiple FPGAs, we present a parallel FP...
A general approach to parallelizing direct method circuit simulation has been developed via novel al...
This book describes algorithmic methods and parallelization techniques to design a parallel sparse d...
Fine-grained dataflow processing of sparse matrix-solve computation (Ax = b) in the SPICE circuit si...
Abstract—SPICE is widely used for transistor-level circuit simulation. However, with the growing com...
Fine-grained dataflow processing of sparse Matrix-Solve computation (A~x = ~b) in the SPICE circuit ...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
SPICE, from the University of California, at Berkeley, is the de facto world standard for circuit si...
[[abstract]]This paper describes a sparse matrix solver for a circuit simulation. For simulation spe...
A coarse-grain parallel implementation is presented of LU factorisation, forward and backward substi...
This paper describes a methodology for solving efficiently the sparse network equations on multiproc...
Efficient multiprocessing approaches to the execution of digital computer programs, which analyse po...
International audienceIn this paper, the performance of a parallel sparse direct solver on a shared ...