Sunday July 11, 2010
One of the typical tasks facing a computational scientist is ensuring the accuracy and precision of results are within acceptable limits. Accuracy refers to how close your answers are to the actual answer; precision refers to how many digits, or bits, of a result that you can trust. Both are related to how you manage the error of your solution. This problem challenges you to solve a numerical integration problem taking accuracy and precision into consideration.
Code, solve and run the following numerical integration problem: Integral of(x * sin(x^2) - (1-x) * sin(1-x^2)) dx, with x = 0 and x = 1 as boundaries.


-You should make use of MPI or CUDA (see the nVidia site for CUDA information)

-You should review the following:

*The theory of numerical integration, such as calculating area under a curve; a helpful primer can be found here.

*Numerical Analysis: understanding of various kinds of error and management of that error
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