![]() If you have 4 tasks to do on a single CPU, doing them serially is 1 * 4. ![]() You are changing how the work is split up, but no changes in capacity. If you have a single CPU, multi-threading probably wouldn't speed that process up (though you never know until you test). If you have no idle resources, multi-threading has no advantages, so the overhead would actually make your overall runtime longer.įor example, if you have a collection of tasks to perform and they are CPU-intensive calculations. Threading is about taking advantage of idle resources to handle more work. If there is only small gain by using multiple threads you could argue that the increased maintenance cost that are usually caused by multi-threaded applications are not worth the speedup. When deciding between single and multithreading, the time needed to change the implementation and the added complexity for developers should be taken into account. When should we decide to give up multithreading and only use a single thread to accomplish our goal? If you ignore thread/process creation and direct inter-process communication overhead, there can still be other limiting factors when using shared resources like IO bottlenecks or increased paging caused by higher memory consumption. If there is no obvious way to parallelize an algorithm so that it will get a speedup, you may need to choose another similar parallel algorithm that solves the same problem but can be more or less efficient. Other algorithms are more suitable for parallel execution (extreme cases are called "embarrassingly parallel").Ī naive implementation of a parallel algorithm can be less efficient in terms of complexity or space compared to a similar sequential algorithm. Not all algorithms can be processed in parallel (algorithms that are strictly sequential where P=0 in Amdahl's law) or at least not efficiently (see P-complete). public class MulithreadingEffects extends Application incrementing a commonly shared integer (AtomicInteger or synchronized) will dramatically change the performance of many threads. Running two threads, count(0,2) and count(1,2) in parallel needs 920msĬhanging the way to count, e.g.Running one thread, count(0,1) needs 1326ms to count all 399993625 bits.count(0,4) will count the 0', 4', 8' byte bits allowing a parallel interleaved counting.The method allow to count every 'nth' bytes bits.Provides a method, counting the number of bits set in this array.Allocates a byte array of 100.000.000 size, filled with random bytes. ![]() Here a small programm (javafx) to play with.
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