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t ry { a c t ion s [ ( int ) obj ] ( ) ; } f i n a l ly { l a t c h Signa l ( ) ; } }, i); } ret u rn lat c h ; }
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This i s pretty straightforward All o f the difficult synchronization is abstracted away inside the C o u n t down E v e n t primitive We queue up a sin gle thread pool work item for each delegate supplied by the caller, and return a handle that can be used to wait for all of the work items to com plete A nicer, more NET-ish API might have returned an IAsyn c Re s u l t for this purpose, but this is left as an exercise for the reader (Building it isn't too difficult given the S i m p l eAsyn c R e s u lt < T > class in 8, Asyn chronous Programming Models) Additionally, it might be useful to allow F u n c < > delegates to be supplied in cases where the parallel operations pro duce values of interest Finally, exceptions during the invocation of the operations are not currently handled in any way-they will instead crash the thread pool thread on which the operation runs Exceptions are discussed in depth at the end of this chapter With the CoBeg i n API, we can start a bunch of work and wait for it Imagine we have a sequential program with independent function invoca tions of B , C, and E, and with dependent function invocations of A, D, and F , as follows
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T My F u n ct ion ( ) { v a r a_v a l A( ) ; BO; CO; v a r d_val D ( a_va l ) ; EO; ret u r n F ( d_va l ) ;
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With a small amount of restructuring, we can offer the parallelism at the top of My F u n c t ion's definition, and wait for it before returning
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T My F u n ction ( ) { Countdown Event l a t c h = CoBeg i n ( o => BO , o => CO, o => EO )j T f_va l = F ( D ( A ( ) j lat c h Wa it O j ret u r n f_v a l j }
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Some assumptions have been made in this process We assume the origi nal ordering of function invocations, A, B , , F, was mostly irrelevant The original fictional program was not functional because the return values of B, (, and E have been ignored This implies there is a good chance they are being executed for effect, and these effects may have subtle dependencies that
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are not evident from My F u n ct ion's definition alone It could be the case that running them in parallel will expose race conditions, and / or that disturbing the ordering will change the behavior of the other function definitions, including the sequential ones A, D, and F Because this is a purely fictional example, it matters very little, but it is brought up to reinforce the point that parallelizing a program goes far beyond the mechanisms required to do so It's quite common for fork /join parallelism to be lexically scoped In other words, the fork and join happen at the same level in the program's lexical blocking, something called structured fork/j oin This encourages a cleaner program design and reduces the chance of runaway parallelism and forgotten joins, which can lead to debugging problems This would happen if the thread responsible for forking and joining happened to fail after the fork but before the join There is no language construct that enforces this structure However, we can build one easily by using our API and just doing the fork and join at once
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