The performance of parallel codes for the solution of initial value problems is usually strongly sensitive to the dimension of the continuous problem. This is due to the overhead related to the exchange of information among the processors and motivates the problem of minimizing the amount of communications. According to this principle, we define the so called Parallel Implicit Predictor Corrector Methods and in this class we derive A-stable, L-stable and numerically zero-stable formulas. The latter property refers to the zero-stability condition of a given formula when roundoff errors are introduced in its coefficients due to their representation in finite precision arithmetic. Some numerical experime...
In high performance computing, nearly all the implementations and published experiments use foating-...
How can small-scale parallelism best be exploited in the solution of nonstiff initial value problems...
SIGLECNRS 17660 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc
The performance of parallel codes for the solution of initial value problems is usually strongly...
AbstractThe stability properties of a class of predictor—corrector algorithms which are designed for...
Stability and efficiency (i.e. derivative function evaluations per processor) are the two main consi...
AbstractIn this paper we construct predictor-corrector methods using block Runge-Kutta methods as co...
AbstractRecently, various classes of predictor-corrector methods have been proposed as being suitabl...
In this paper we give a generalized predictor-corrector algorithm for solving ordinary differential ...
This paper describes the construction of block predictor-corrector methods based on Runge-Kutta-Nyst...
In this talk we derive a new class of linearly implicit numerical methods for stiff initial value pr...
AbstractThis paper describes the construction of block predictor-corrector methods based on Runge-Ku...
AbstractIn this paper, we are concerned with parallel predictor-corrector (PC) iteration of Runge-Ku...
In this work, we discuss a family of parallel implicit time integrators for multi-core and potential...
The increasing complexity of advanced devices and systems increases the scale of mathematical models...
In high performance computing, nearly all the implementations and published experiments use foating-...
How can small-scale parallelism best be exploited in the solution of nonstiff initial value problems...
SIGLECNRS 17660 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc
The performance of parallel codes for the solution of initial value problems is usually strongly...
AbstractThe stability properties of a class of predictor—corrector algorithms which are designed for...
Stability and efficiency (i.e. derivative function evaluations per processor) are the two main consi...
AbstractIn this paper we construct predictor-corrector methods using block Runge-Kutta methods as co...
AbstractRecently, various classes of predictor-corrector methods have been proposed as being suitabl...
In this paper we give a generalized predictor-corrector algorithm for solving ordinary differential ...
This paper describes the construction of block predictor-corrector methods based on Runge-Kutta-Nyst...
In this talk we derive a new class of linearly implicit numerical methods for stiff initial value pr...
AbstractThis paper describes the construction of block predictor-corrector methods based on Runge-Ku...
AbstractIn this paper, we are concerned with parallel predictor-corrector (PC) iteration of Runge-Ku...
In this work, we discuss a family of parallel implicit time integrators for multi-core and potential...
The increasing complexity of advanced devices and systems increases the scale of mathematical models...
In high performance computing, nearly all the implementations and published experiments use foating-...
How can small-scale parallelism best be exploited in the solution of nonstiff initial value problems...
SIGLECNRS 17660 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc