Executing Iterations in Parallel in Visual C#.NET

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Executing Iterations in Parallel
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Listing 188: For Loop Synchronously Calculating Pi in Sections
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using System; const int TotalDigits = 100; const int BatchSize = 10; class Program { void Main() { string pi = null; int iterations = TotalDigits / BatchSize; for (int i = 0; i < iterations; i++) { pi += PiCalculatorCalculate( BatchSize, i * BatchSize); } ConsoleWriteLine(pi); } }
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using System; class PiCalculator { public static string Calculate(int digits, int startingAt) { // } // }
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OUTPUT 186:
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>3141592653589793238462643383279502884197169399375105820974944592307816 406286208998628034825342117067982148086513282306647093844609550582231725 359408128481117450284102701938521105559644622948954930381964428810975665 933446128475648233786783165271201909145648566923460348610454326648213393 607260249141273724587006606315588174881520920962829254091715364367892590 360011330530548820466521384146951941511609433057270365759591953092186117 38193261179310511854807446237996274956735188575272489122793818301194912
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The for loop executes each iteration synchronously and sequentially However, since the pi calculation algorithm splits the pi calculation into
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18: Multithreading
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independent pieces, it is not necessary to complete the pieces sequentially as long as they are still all appended sequentially Therefore, imagine if you could have iterations run simultaneously, overlapping each other because each processor could take an iteration and execute it in parallel with other processors executing other iterations Given the simultaneous execution of iterations, we could decrease the execution time more and more based on the number of processors
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ParallelFor()
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NET 4 includes such a parallel for capability through an API on System ThreadingTasksParallel, as shown in Listing 189
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Listing 189: For Loop Calculating Pi in Sections in Parallel
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using System; using SystemThreading; // class Program { void Main() { string pi = null; int iterations = TotalDigits / BatchSize; string[] sections = new string[iterations]; ParallelFor(0, iterations, (i) => { sections[i] += PiCalculatorCalculate( BatchSize, i * BatchSize); }); pi = stringJoin("", sections); ConsoleWriteLine(pi); }
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The output for Listing 189 is identical to Output 186; however, the execution time is significantly faster (assuming multiple CPUs) The ParallelFor() API is designed to look similar to a standard for loop The first parameter is the fromInclusive value, the second is the toExclusive value, and the last is the Action<int> to perform When using an expression statement (with curly brackets) for the action, the code looks similar to a for loop statement except now each iteration may execute in parallel
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Executing Iterations in Parallel
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As with the for loop, the call to ParallelFor() will not complete until all iterations are complete In other words, by the time execution reaches the stringJoin() statement, all sections of pi will have been calculated It is important to note that the code for combining the various sections of pi no longer occurs inside the iteration (action) Since sections of the pi calculation will very likely not complete sequentially, appending a section whenever an iteration completes will likely append them out of order Even if sequence was not a problem, there is still a potential race condition because the += operator is not atomic To address both of these problems, each section of pi is stored into an array and no two or more iterations will access a single element within the array simultaneously Only once all sections of pi are calculated does stringJoin() combine them In other words, we postpone concatenating the sections until after the ParallelFor() loop has completed This avoids any race condition caused by sections not yet calculated or sections concatenating out of order
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ParallelForEach()
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Parallel execution of a loop is not limited to the construct of for ParallelForEach() provides similar capabilities for the foreach loop, as shown in Listing 1810
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Listing 1810: Parallel Execution of a foreach Loop
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using using using using System; SystemCollectionsGeneric; SystemIO; SystemThreadingTasks;
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class Program { // static void EncryptFiles( string directoryPath, string searchPattern) { IEnumerable<string> files = DirectoryGetFiles( directoryPath, searchPattern, SearchOptionAllDirectories); ParallelForEach(files, (fileName) => { Encrypt(fileName); });
18: Multithreading
} // }
In this example, we call a method that encrypts each file within the files collection and it does so in parallel, executing as many threads as the API determines is efficient Efficiency is determined by a hill climbing algorithm in which additional threads are created until the overhead of additional threads begins to decrease overall performance at which point the most efficient number of threads is determined (dynamically) The degree of parallelism corresponds to the number of threads that run simultaneously at any particular time
Parallel Exception Handling with SystemAggregateException While executing the query in parallel, there is the potential for multiple exceptions one for each started iteration Notice, therefore, that if an exception throws while the loop is executing, the exception type is a SystemAggregateException an exception that contains multiple inner exceptions In this way, all exceptions within the loop are handled with a single try/catch block The SystemThreadingTask namespace uses the SystemAggregateException consistently for grouping together unhandled exceptions because, with parallel operations, there is frequently the potential for multiple exceptions Consider the example in Listing 1811 and its output in Output 187