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orchestration capabilities for fine-grained intraprocess work, but i s limited in that true concurrency is not used in the resulting programs (see Further Reading, Shukla, Schmidt) Message Passing Interface (MPI) is a common programming model used in distributed HPC situations There is other frag mented support throughout the Windows platform for message based par allelism, such as the windows messaging subsystem COM RPC and NET Remoting, but in the absence of one true way, we will avoid in-depth discussions of any of these In message based parallelism systems, concurrency is driven by sending and receiving messages To the extreme, the only way to generate concur rency is by creating separate agents with enforced isolation, and the only way to perform synchronization is through messages Specialized languages such as Erlang take this approach (see Further Reading, Armstrong) In addition to the basic capability to send and receive messages, these sys tems usually offer sophisticated pattern matching capabilities, much like those available in functional programming languages such as F# This often includes an ability to filter messages based on a predicate, to form conjunc tions and disjunctions in the wait clauses (eg, wait for a message from [A and B] or C, and so forth), and to have multiple end points to handle suc cess and failure messages differently The CCR also supports similar capa bilities through library calls Other programming models exhibit much of the same style of pro gramming of message based parallelism but without the sophisticated capabilities For example, GUI programming-as we'll discuss more in 1 6-is based on sending messages from worker threads to the GUI thread The GUI thread has a top-level event loop where its sole purpose is to receive and dispatch messages via event handlers This is a messag ing system at its core
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There have been a few topics mentioned throughout this chapter that cut across all the different kinds of parallelism discussed This includes hand ling exceptions in a parallel computation and cancellation of asynchronous operations
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Concurrent Exceptions Windows structured exception handling (SEH) was built for sequential programs It is fundamentally based on thread stacks and uses them to store handler frames, search for handlers during a throw, and so on As a result, there are many conceptual mismatches that need to be addressed when dealing with exceptions in a concurrent program To see the effect this has, consider the DoA l l method shown earlier It runs a set of delegates in parallel, but we completely ignored the fact that any of the delegates may throw an exception when invoked If one of them were to throw an excep tion with the DoAl l code as written, the exception will occur on a com pletely separate thread from the one that called DoA ll; in this case, that will be a thread pool thread And this will crash the program This might be OK For instance, if we required that each delegate passed to DoAll were responsible for catching and dealing with any exceptions, this could be a perfectly reasonable choice But it requires extra discipline for users of our API, discipline that can be cumbersome and error prone (and feels very different from sequential programming) An alternative approach is to rethrow any such exceptions in the context of the caller of DoAl l But to enable this, there is extra work we must do Several important topics arise, such as whether we must wait for all of the concurrent work to complete before propagating the exception, impacts of rethrowing to debuggability, and so forth Even trickier, it might be the case that multiple exceptions are thrown (simultaneously), which begs the question, "How are multiple exceptions exposed to the programmer calling DoAl l " We could excuse ourselves from the business of caring about exceptions altogether, but users of DoAll would have to build these facilities themselves Doing it once and in a consistent way would seem to be a good idea
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