A Matrix Framework for Conjugate Gradient Methods and Some Variants of CG with Less Synchronization Overhead

نویسندگان

  • Eduardo F. D'Azevedo
  • Victor Eijkhout
  • Charles H. Romine
چکیده

We will present a matrix framework for the conjugate gradient methods, which is expressed in terms of whole vector sequences instead of single vectors or initial parts of sequences. Using this framework extremely concise derivations of the conjugate gradient method, the Lanczos algorithm, and methods such as GMRES, QMR, CGS, can be given. This framework is then used to present some equivalent forms of computing the inner products in the conjugate gradient and Lanczos algorithms. Such equivalent formulations can perform all inner product calculations of a single iteration simultaneously, thereby making the method more efficient in a parallel computing context. 1 Matrix Framework In his 1965 book, Householder [4] presented a short derivation of the conjugate gradient method using a matrix framework. By introducing matrices whose columns are the elements of a vector sequence, e.q. X = (x1, . . .), it becomes possible to express statements about sequences as matrix equations. For instance, a Krylov sequence xi+1 = Axi can be written as AX = XJ where J is the unit lower diagonal matrix (δi,j+1). In [3] this matrix framework is used to give derivations of a number of conjugate gradient-like methods, and to derive basic properties of the methods. As an example of the latter, here is a characterization of how Hessenberg matrices arise in iterative methods: Lemma 1 If A is a square matrix, R a vector sequence, and AR = RH, then H is a non-degenerate upper Hessenberg matrix if and only if the vectors ri are linear combinations of a Krylov sequence obtained from applying A to a multiple of r1. The proof follows from the fact that taking linear combinations corresponds in the matrix framework to right multiplication by an upper triangular matrix. ∗ This work was supported in part by the Applied Mathematical Sciences subprogram of the Office of Energy Research, U.S. Department of Energy under contract DE-AC05-84OR21400 with Martin Marietta Energy Systems, Inc. and in part by DARPA under contract number DAAL0391-C-0047 † Mathematical Sciences Section, Oak Ridge National Laboratory, Oak Ridge, TN 37831–6367. ‡ Computer Science Department, University of Tennessee, Knoxville, TN 37996–1301.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Global conjugate gradient method for solving large general Sylvester matrix equation

In this paper, an iterative method is proposed for solving large general Sylvester matrix equation $AXB+CXD = E$, where $A in R^{ntimes n}$ , $C in R^{ntimes n}$ , $B in R^{stimes s}$ and  $D in R^{stimes s}$ are given matrices and $X in R^{stimes s}$  is the unknown matrix. We present a global conjugate gradient (GL-CG) algo- rithm for solving linear system of equations with multiple right-han...

متن کامل

New variants of the global Krylov type methods for linear systems with multiple right-hand sides arising in elliptic PDEs

In this paper, we present new variants of global bi-conjugate gradient (Gl-BiCG) and global bi-conjugate residual (Gl-BiCR) methods for solving nonsymmetric linear systems with multiple right-hand sides. These methods are based on global oblique projections of the initial residual onto a matrix Krylov subspace. It is shown that these new algorithms converge faster and more smoothly than the Gl-...

متن کامل

Hiding global synchronization latency in the preconditioned Conjugate Gradient algorithm

Scalability of Krylov subspace methods suffers from costly global synchronization steps that arise in dot-products and norm calculations on parallel machines. In this work, a modified Conjugate Gradient (CG) method is presented that removes the costly global synchronization steps from the standard CG algorithm by only performing a single non-blocking reduction per iteration. This global communi...

متن کامل

Crack Detection In Functionally Graded Beams Using Conjugate Gradient Method

In this paper the conjugate gradient (CG) method is employed for identifying the parameters of crack in a functionally graded beam from natural frequency measurement. The crack is modeled as a massless rotational spring with sectional flexibility. By using the Euler-Bernoulli beam theory on two separate beams respectively and applying the compatibility requirements of the crack, the characteris...

متن کامل

Two Settings of the Dai-Liao Parameter Based on Modified Secant Equations

Following the setting of the Dai-Liao (DL) parameter in conjugate gradient (CG) methods‎, ‎we introduce two new parameters based on the modified secant equation proposed by Li et al‎. ‎(Comput‎. ‎Optim‎. ‎Appl‎. ‎202:523-539‎, ‎2007) with two approaches‎, ‎which use an extended new conjugacy condition‎. ‎The first is based on a modified descent three-term search direction‎, ‎as the descent Hest...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1993