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HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACH 9TABLE 6. Observed times (in seconds) for grid search al-gorithm, with a Howard step every
10 HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACHAt the moment there is still a drawback to using double precision com-putation. For the
Research Papers 2012 2011-52: Lars Stentoft: What we can learn from pricing 139,879 Individual Stock Options 2011-53: Kim Christensen, Mark Podolsk
HETEROGENEOUS COMPUTING IN ECONOMICS: ASIMPLIFIED APPROACHMATT P. DZIUBINSKI AND STEFANO GRASSICREATES, Department of Economics and Business, Aarhus U
2 HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACHparallel problems, such as graphical applications, video games, and im-age processing.2Th
HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACH 3compare the source codes given in Listing 1 (CUDA) and Listing 2 (C++AMP). In each listin
4 HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACH1 / / "A" and "B" a r e s q u a r e m a t r i c e s2 / / " s i z
HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACH 5the RBC model used in Aldrich et al. (2011). Section 4 reports some nu-merical results an
6 HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACHwhere E0denotes the conditional expectation operator, β the discount fac-tor, and η risk
HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACH 7the second experiment we use the Howard improvement method and gridsearch; as pointed out
8 HETEROGENEOUS COMPUTING IN ECONOMICS: A SIMPLIFIED APPROACHone is the tiling (blocking) optimization, as in the CUDA version, whichis more complex,
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