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Intel Threading Building Blocks
book

Intel Threading Building Blocks

by James Reinders
July 2007
Intermediate to advanced content levelIntermediate to advanced
332 pages
10h 4m
English
O'Reilly Media, Inc.
Content preview from Intel Threading Building Blocks

Synchronization Between Physics Threads

There are several ways to make scalable communication. Applying the right technique depends on the game’s rules. But with respect to scalability, there are two major cases. First, if there are a constant number of point-to-point interactions independent of the number of threads, the game would be scalable. Second, if there are effects that have a collective nature, such as gravity between objects—potentially n2 point-to-point operations—the game is not likely to scale. (We consider this to be worst.) There are a variety of techniques to improve the scalability of such n2 point-to-point operations. In selecting the right technique, you should also take into account that the serial computation of these effects can be more efficient (linear time) than the scalable point-to-point computation.

As an example, a real physics computation is rigid body physics. There are two cases. Each rigid body may lie within one or a few domains. In this case, it is scalable because the physics will be computed by each thread on bodies within its domain. If, however, the rigid body spans all domains substantially, an advanced technique must be used. In this case, you could consider the computations done in molecular dynamics (MD), which have similar characteristics. MD computations have been implemented in an extremely scalable manner in the NAMD application (http://en.wikipedia.org/wiki/NAMD), which won a Gordon Bell award for scalability. It is not likely that ...

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Publisher Resources

ISBN: 9780596514808Errata Page