By Joanna Berlińska (auth.), Roman Wyrzykowski, Jack Dongarra, Konrad Karczewski, Jerzy Wasniewski (eds.)
This e-book constitutes the court cases of the eighth foreign convention on Parallel Processing and utilized arithmetic, PPAM 2009, held in Wroclaw, Poland, in September 2009.
Read Online or Download Parallel Processing and Applied Mathematics: 8th International Conference, PPAM 2009, Wroclaw, Poland, September 13-16, 2009, Revised Selected Papers, Part II PDF
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Extra info for Parallel Processing and Applied Mathematics: 8th International Conference, PPAM 2009, Wroclaw, Poland, September 13-16, 2009, Revised Selected Papers, Part II
3. Up to which amount of grid jobs and resources does the EA improve the best heuristically generated schedule? 26 W. Jakob et al. As the two benchmark scenarios based on large degrees of dependencies have turned out to be harder than those using small degrees [2,13], they are used here for the experiments. They are denoted sRlD and lRlD (small or large Resource alternatives / large Dependencies). As pointed out in  and , their time and cost limits were set so tightly that the heuristics could not solve them without violating these soft constraints.
We know that basic inequalities are satisﬁed by equality: (z1 ) O1 = q1 /S = α3 /D (z2,2 ) (q1 + q2 )/S = O2 (z3,3 ) (q1 + q2 + q3 )/S = O3 (z2 ) O2 = q2 /s1 = α2 /D = O3 = q3 /s1 = α/D = (z3 ) (z4,4 ) (z4 ) O4 = q4 /s1 = 1/D = (q1 + q2 + q3 + q4 )/S = O4 . The equal signs are labeled by labels of used equalities. Similarly the inequality signs are labeled by labels of suﬃcient conditions in following text. We can also easily verify that the equation (znorm ) holds. , nonbasic) inequalities: (z2,3 ) q2 + q3 = (α + α2 )s1 /D ≤A α(s1 + s2 )/D = (s1 + s2 )O3 2 (z2,4 ) q2 + q3 + q4 = (1 + α + α )s1 /D ≤B (s1 + s2 + s3 )/D = (s1 + s2 + s3 )O4 (z3,4 ) q3 + q4 = (1 + α)s1 /D ≤A (s1 + s2 )/D = (s1 + s2 )O4 .
All other inequalities are turned into equations. The upper bound coeﬃcients are values of nonzero dual variables. These give the matching upper bound on the competitive ratio, which is obtained by summing up the corresponding inequalities multiplied by these coeﬃcients. Note that all nonbasic dual variables have coeﬃcients of zero value (and thus are not listed), because of the dual complementary slackness of linear programing. Now we show how to check the correctness of Case I. The correctness of all other cases and all other restrictions in this paper can be checked in the same way.
Parallel Processing and Applied Mathematics: 8th International Conference, PPAM 2009, Wroclaw, Poland, September 13-16, 2009, Revised Selected Papers, Part II by Joanna Berlińska (auth.), Roman Wyrzykowski, Jack Dongarra, Konrad Karczewski, Jerzy Wasniewski (eds.)