The computational complexities of some common operations with n by n matrices are given in the table below. Operations Matrix-matrix multiplication Flops 2n 2n 2n /3+0(n2) n/3+0(n²) Matrix-vector multiplication LU factorization Cholesky factorization Back/forward substitution Tridiagonal solve 8 You have a 2.5 GHz workstation with 6 cores where each core can do 6 floating point operations per clock cycle. Consider then by n linear system Aa b where A is tridiagonal. Estimate the largest value of n such that the linear system can be solved in 140 minutos. 2.75 E7 O1.04E5 O 1.31E5 9.45E13
The computational complexities of some common operations with n by n matrices are given in the table below. Operations Matrix-matrix multiplication Flops 2n 2n 2n /3+0(n2) n/3+0(n²) Matrix-vector multiplication LU factorization Cholesky factorization Back/forward substitution Tridiagonal solve 8 You have a 2.5 GHz workstation with 6 cores where each core can do 6 floating point operations per clock cycle. Consider then by n linear system Aa b where A is tridiagonal. Estimate the largest value of n such that the linear system can be solved in 140 minutos. 2.75 E7 O1.04E5 O 1.31E5 9.45E13
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter2: Systems Of Linear Equations
Section2.2: Direct Methods For Solving Linear Systems
Problem 1CEXP
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