omp parallel vs omp parallel for

Question

What is the difference between these two    A    pragma omp parallel         pragma omp for     for int i   1  i  lt  100    i                               B    pragma omp parallel for for int i   1  i  lt  100    i

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These are equivalent    pragma omp parallel spawns a group of threads  while  pragma omp for divides loop iterations between the spawned threads  You can do both things at once with the fused  pragma omp parallel for directive

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There are obviously plenty of answers  but this one answers it very nicely  with source       pragma omp for only delegates portions of the loop for   different threads in the current team  A team is the group of threads   executing the program  At program start  the team consists only of a   single member  the master thread that runs the program       To create a new team of threads  you need to specify the parallel   keyword  It can be specified in the surrounding context    pragma omp parallel       pragma omp for    for int n   0  n  lt  10    n     printf    d   n        and      What are  parallel  for and a team      The difference between parallel    parallel for and for is as follows        A team is the group of threads   that execute currently  At the program beginning  the team consists of   a single thread  A parallel construct splits the current thread into a   new team of threads for the duration of the next block statement    after which the team merges back into one  for divides the work of the   for-loop among the threads of the current team       It does not create   threads  it only divides the work amongst the threads of the currently   executing team  parallel for is a shorthand for two commands at once    parallel and for  Parallel creates a new team  and for splits that   team to handle different portions of the loop  If your program never   contains a parallel construct  there is never more than one thread    the master thread that starts the program and runs it  as in   non-threading programs    https   bisqwit iki fi story howto openmp

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I don t think there is any difference  one is a shortcut for the other  Although your exact implementation might deal with them differently       The combined parallel worksharing constructs are a shortcut for   specifying a parallel construct containing one worksharing construct   and no other statements  Permitted clauses are the union of the clauses   allowed for the parallel and worksharing contructs    Taken from http   www openmp org mp-documents OpenMP3 0-SummarySpec pdf  The specs for OpenMP are here   https   openmp org specifications

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Although both versions of the specific example are equivalent  as already mentioned in the other answers  there is still one small difference between them  The first version includes an  unnecessary implicit barrier  encountered at the end of the  omp for   The other implicit barrier can be found at the end of the parallel region  Adding  nowait  to  omp for  would make the two codes equivalent  at least from an OpenMP perspective  I mention this because an OpenMP compiler could generate slightly different code for the two cases

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I am seeing starkly different runtimes when I take a for loop in g   4 7 0  and using   std  vector lt double gt  x  std  vector lt double gt  y  std  vector lt double gt  prod   for  int i   0  i  lt  5000000  i         double r1     double rand     double RAND MAX     5     double r2     double rand     double RAND MAX     5     x push back r1      y push back r2      int sz   x size      pragma omp parallel for  for  int i   0  i lt  sz  i       prod i    x i    y i     the serial code  no openmp   runs in 79 ms  the  parallel for  code runs in 29 ms  If I omit the for and use  pragma omp parallel  the runtime shoots up to 179ms  which is slower than serial code   the machine has hw concurrency of 8   the code links to libgomp

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Here is example of using separated parallel and for here  In short it can be used for dynamic allocation of OpenMP thread-private arrays before executing for cycle in several threads  It is impossible to do the same initializing in parallel for case   UPD  In the question example there is no difference between single pragma and two pragmas  But in practice you can make more thread aware behavior with separated parallel and for directives  Some code for example    pragma omp parallel        double  data    double  malloc          this data is thread private       pragma omp for     for 1   100     first parallelized cycle                   pragma omp single            make some single thread processing       pragma omp for    second parallelized cycle     for 1   100                    pragma omp single            make some single thread processing again      free data      free thread private data

[openmp] omp parallel vs. omp parallel for

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