The diagonally implicit 2-point block backward differentiation formulas (DI2BBDF) of order two, order three, and order four are derived for solving stiff initial value problems (IVPs). The stability properties of the derived methods are investigated. The implementation of the method using Newton iteration is also discussed. The performance of the proposed methods in terms of maximum error and computational time is compared with the fully implicit block backward differentiation formulas (FIBBDF) and fully implicit block extended backward differentiation formulas (FIBEBDF). The numerical results show that the proposed method outperformed both existing methods.
Parallel implementation of fourth order Block Backward Differentiation Formulas (BBDF(4)) is presented for a numerical solution of first order stiff ordinary differential equations (ODEs). This method computes the numerical solution at two points concurrently in each block. The sequential and parallel codes are developed on Message Passing Interface (MPI) library and run on High Performance Computing (HPC). The performance of this new method is measured in terms of Speedup (Sp) and Efficiency (Ef). It is shown that the parallel implementation BBDF(4) produced a better speed up compared to the sequential timing.
We derive a variable step of the implicit block methods based on the backward differentiation formulae (BDF) for solving stiff initial value problems (IVPs). A simplified strategy in controlling the step size is proposed with the aim of optimizing the performance in terms of precision and computation time. The numerical results obtained support the enhancement of the method proposed as compared to MATLAB's suite of ordinary differential equations (ODEs) solvers, namely, ode15s and ode23s.
An advanced method using block backward differentiation formula (BBDF) is introduced with efficient strategy in choosing the step size and order of the method. Variable step and variable order block backward differentiation formula (VSVO-BBDF) approach is applied throughout the numerical computation. The stability regions of the VSVO-BBDF method are investigated and presented in distinct graphs. The improved performances in terms of accuracy and computation time are presented in the numerical results with different sets of test problems. Comparisons are made between the proposed method and MATLAB's suite of ordinary differential equations (ODEs) solvers, namely, ode15s and ode23s.
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