The API is easy to use, users only need to input executed task and data range and don't care about how they are executed. However they still have disadvantages. 1.The number of thread in thread pool isn't aligned to core number 2.Task executes an entry once, which isn't sufficient 3.A task is targeted to a thread, which isn't flexible
Better use for divide and conquer problem Previous issues (thread oversubscription and starvation, unbalancing) still exist Task dividing strategy is from users, isn't configured properly according to running condition
Other high-level parallel API Can add data set while executing it concurrently. concurrent _while Use divide_join based task to return calculation result. concurrent _reduce Sort data set concurrently. concurrent sort for example, a matrix multiply another matrix int matrix1, int matrix2 int matrix3 = matrix1 * matrix2 int matrix3 = concurrent_multiply(matrix1, matrix2) Math calculation
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