Parallelizing An Algorithm of Charles S Peskin for Describing Incompressible Fl
Parallelizing An Algorithm of Charles S Peskin for Describing Incompressible Fl
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In our eReader you can find the full English version of the book. Read Parallelizing An Algorithm of Charles S Peskin for Describing Incompressible Fl Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book Parallelizing An Algorithm of Charles S Peskin for Describing Incompressible Fl
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1. The predicted values are given in parenthesis. The agreement is seen to be good.
p PROBLEM SIZE Np N2 (//iter) 2 4, ] . 9867 L6 (6) (. 9872) 8, : = ^^ = = = = . 9927 52 (5) (. 9930) 16, . 9955 64 (5) (. 9957) 3 . 8629 (. 8632) . 9520 (. 9520) . 9527 (. 9528) 4 . 9644 (. 9663) . 9789 (. 9793) . 9870 (. 9872) 7 . 7156 (. 7159) . 8475 (. 8476) . 8713 (. 8702) 8 . 8888 (. 8906) . 9585 (. 9605) . 9707 (. 9707) 15 . 4756 (. 4750) . 6541 (. 6542) . 7579 (. 7576) 16 . 7691 (. 7700) . 8466 (. 8484) .... 9523 (. 9538) 31 . 3974 (. 3974) . 4383 (. 4379) . 6135 (. 6131) 32 . 3850 (. 3850) . 6866 (. 6878) . 7864 (. 7871) 48 (. 2566) (. 4584) (. 5248) 64 (. 1925) (. 3438) (. 5833) Table 6. 2 6. 4. Estimating efficiency for large size problems can not be done by using formulas (5. 3) and (6. 4) directly since #iter is not known. If one substitutes (5. 5), (5. 6) into (5. 3) then efficiency appears as a rational function E(#iter) of the form E(#iter) = A X //iter + B C X ^;iter + D where the coefficients A, B, C, D depend on the problem size parameters -33- and on P.
What to read after Parallelizing An Algorithm of Charles S Peskin for Describing Incompressible Fl?
You can find similar books in the "Read Also" column, or choose other free books by B D Lubachevsky to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
1. The predicted values are given in parenthesis. The agreement is seen to be good.
p PROBLEM SIZE Np N2 (//iter) 2 4, ] . 9867 L6 (6) (. 9872) 8, : = ^^ = = = = . 9927 52 (5) (. 9930) 16, . 9955 64 (5) (. 9957) 3 . 8629 (. 8632) . 9520 (. 9520) . 9527 (. 9528) 4 . 9644 (. 9663) . 9789 (. 9793) . 9870 (. 9872) 7 . 7156 (. 7159) . 8475 (. 8476) . 8713 (. 8702) 8 . 8888 (. 8906) . 9585 (. 9605) . 9707 (. 9707) 15 . 4756 (. 4750) . 6541 (. 6542) . 7579 (. 7576) 16 . 7691 (. 7700) . 8466 (. 8484) .... 9523 (. 9538) 31 . 3974 (. 3974) . 4383 (. 4379) . 6135 (. 6131) 32 . 3850 (. 3850) . 6866 (. 6878) . 7864 (. 7871) 48 (. 2566) (. 4584) (. 5248) 64 (. 1925) (. 3438) (. 5833) Table 6. 2 6. 4. Estimating efficiency for large size problems can not be done by using formulas (5. 3) and (6. 4) directly since #iter is not known. If one substitutes (5. 5), (5. 6) into (5. 3) then efficiency appears as a rational function E(#iter) of the form E(#iter) = A X //iter + B C X ^;iter + D where the coefficients A, B, C, D depend on the problem size parameters -33- and on P.
What to read after Parallelizing An Algorithm of Charles S Peskin for Describing Incompressible Fl?
You can find similar books in the "Read Also" column, or choose other free books by B D Lubachevsky to read onlineMoreLess
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