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Search Many parallel algorithms take the form of search algorithms I'm not talking about the kind of search that you use to find content on the Internet, but rather the more general idea of search in terms of data structures, as is com monly used in AI programming Here are some examples of search prob lems for which parallelism might apply
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Matching documents from a sample set containing certain related terms Or, matching documents with common structural characteris tics as determined through natural language processing style analy sis Many parallel workers might work at the problem until a global search condition is established, such as the presence of a certain number of paired documents
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Similar to searching documents to find a particular pattern, we may search a list of images in order to perform facial recognition All images can be processed in parallel, but as soon as a match is found all workers should quit
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Solving an NP-hard problem with some kind of exhaustive search or heuristics based technique For example, many puzzles require such solving techniques (Sudoku, n-Queens, etc) In this case, usually all parties will search entirely different parts of the search space; the first to find a solution terminates the computation and reports success
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Simulating or finding optimal solutions to a game using game tree searches, such as an alpha-beta search (see Further Reading, Knuth, Moore) Alpha-beta searches use a technique called alpha-beta pruning, which allows the search space to be trimmed as new infor mation is found, leading to less wasted work This is amenable to parallelism (see Further Reading, Russell, Norvig) Since many par allel workers can search different parts of the game tree at a time, they can also communicate to each other when potential cuts can be made This leads to finding the set of solutions more quickly and increases the possibility of a more optimal solution, because more of the tree can be searched in less time
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All of these examples share common characteristics, specifically that many threads do work in parallel to locate a matching solution When a solution is found, this is communicated to other workers (eg, by setting a shared flag polled by all), and they halt the search right away By throwing more workers at the problem, we hope to find the solution more quickly Two terms can be used to summarize this: cooperative and speculative These algorithms are cooperative because all threads share information as needed to help each other; and they are speculative because threads search more of the space, possibly doing wasted work, often leading to more CPU cycles spent on the problem but less wall-clock time Other kinds of spec ulation are possible outside of the search space, such as the kind used by processors during branch prediction Search algorithms also routinely enjoy something called super-linear speedups We describe speedups in more detail in the next chapter, but it's a pretty self-descriptive term: the parallel speedup may grow superlinearly as more processors are added The reason is due to the speculative nature, that is, more of the search space is covered in less time, increasing the prob ability of finding a solution more quickly in a nonlinear fashion With that said, some problems may see no benefit from throwing parallelism at it, or even see sub linear speedups Much of the performance analysis we will encounter in the next chapter doesn' t apply in the same way to coopera tive search algorithms
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Out of the three categories, we will spend the least amount of time dis cussing message based parallelism There are many books available on how to build coarse-grained message passing systems (eg, using Windows Communication Foundation [WCF] and Workflow Foundation [WF] ) But there is little in the way of fine-grained, intraprocess message passing in Windows and NET today The Microsoft Robotics SDK contains a technol ogy called the Coordination and Concurrency Runtime (CCR), which pro vides a programming model and tooling that support of these patterns (see Further Reading, Richter) Windows Workflow (WF) enables sophisticated
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