b89f8fabc9
The project includes following components and frameworks: - ML Collective component - NETPATTERNS and COMMPATTERNS common components - BCOL framework - SBGP framework Note: By default the ML collective component is disabled. In order to enable new collectives user should bump up the priority of ml component (coll_ml_priority) ============================================= Primary Contributors (in alphabetical order): Ishai Rabinovich (Mellanox) Joshua S. Ladd (ORNL / Mellanox) Manjunath Gorentla Venkata (ORNL) Mike Dubman (Mellanox) Noam Bloch (Mellanox) Pavel (Pasha) Shamis (ORNL / Mellanox) Richard Graham (ORNL / Mellanox) Vasily Filipov (Mellanox) This commit was SVN r27078.
105 строки
3.8 KiB
C
105 строки
3.8 KiB
C
/*
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* Copyright (c) 2009-2012 Oak Ridge National Laboratory. All rights reserved.
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* Copyright (c) 2009-2012 Mellanox Technologies. All rights reserved.
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* $COPYRIGHT$
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*
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* Additional copyrights may follow
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*
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* $HEADER$
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*/
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#include "ompi/mca/coll/ml/coll_ml.h"
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/*
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* This routine is used to progress a series of communication
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* primitives.
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*
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* Assumptions:
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* - A message is described by a message descriptor
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* - Each message has a setup function associated with it, which is
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* algorithm specific. When a fragment is being prepared, this
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* progress is used to setup the arguments that will be passed into
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* each routine called to complete a given function. The idea here
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* is that when the progress routines is called, the full communication
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* pattern has already been described in the setup function, with
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* progress function being generic.
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* - Each fragment is described by a fragment descriptor
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* - Each message descriptor has a fragment descriptor permanently
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* associated with it.
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* - The message will be proressed as long as the individul
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* functions complete. When an indivicual funciton does not
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* complete, the current state will be saved, for future
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* restart.
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* - return status
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* OMPI_COMPLETE: funciton completed
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* OMPI_INCOMPLETE: need to continue progressing the funciton
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* any other return value - error condition
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*/
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int coll_ml_progress_individual_message(mca_coll_ml_fragment_t *frag_descriptor)
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{
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/* local variables */
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int fn_index, ret = OMPI_SUCCESS;
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uint32_t n_frags_complete;
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int starting_fn_index=frag_descriptor->current_fn_index;
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coll_ml_collective_description_t *local_comm_description=
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frag_descriptor->full_msg_descriptor->local_comm_description;
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/* loop over functions */
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for( fn_index=starting_fn_index ; fn_index < local_comm_description->n_functions;
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fn_index ++ ) {
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mca_bcol_base_module_t *bcol_module=
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local_comm_description->functions[fn_index].bcol_module;
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ret =(bcol_module->bcol_function_table[local_comm_description->functions[fn_index].fn_idx])
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(&(frag_descriptor->fn_args[fn_index]), &local_comm_description->functions[fn_index]);
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if( ML_OMPI_COMPLETE != ret ) {
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/* since function incomplete, need to decide what to do */
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if( ML_OMPI_INCOMPLETE == ret ) {
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/* need to return to this later */
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/* mark where to continue */
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frag_descriptor->current_fn_index=fn_index;
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/* RLG - is this really best ? Only advantage is that
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* if we exit the loop, we can assume message is
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* complete
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*/
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return OMPI_SUCCESS;
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} else {
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/* some sort of error condition */
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frag_descriptor->current_fn_index=fn_index;
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return ret;
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}
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}
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}
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/* looks like we are done */
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/* increment counter for number of completed fragments */
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n_frags_complete=OPAL_THREAD_ADD64(
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&(frag_descriptor->full_msg_descriptor->frags_complete),1);
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/*
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* release resrouces
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*/
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/* fragment resources */
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/* full message resources */
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if ( n_frags_complete == frag_descriptor->full_msg_descriptor->n_fragments)
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{
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/* free any fragments that still need to be freed
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* NOTE: at this level we do not handle any resrouces
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* aside from the pre-registered buffers, all these
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* are handled in the bcol level */
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/* return the buffers to the ml free list */
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/* mark as complete - so MPI can complete
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* the message descriptor will be freed by a call
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* to mpi_test/mpi_wait/... as the message descriptor
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* also holds the mpi request object */
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}
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return OMPI_SUCCESS;
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}
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