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openmpi/ompi/mca/coll/ml/coll_ml_allreduce.c
2015-09-11 13:20:44 +09:00

554 строки
22 KiB
C

/* -*- Mode: C; c-basic-offset:4 ; indent-tabs-mode:nil -*- */
/*
* Copyright (c) 2009-2012 Oak Ridge National Laboratory. All rights reserved.
* Copyright (c) 2009-2012 Mellanox Technologies. All rights reserved.
* Copyright (c) 2013 Los Alamos National Security, LLC. All rights
* reserved.
* Copyright (c) 2015 Research Organization for Information Science
* and Technology (RIST). All rights reserved.
* $COPYRIGHT$
*
* Additional copyrights may follow
*
* $HEADER$
*/
/** @file */
#include "ompi_config.h"
#include <stdlib.h>
#include "ompi/constants.h"
#include "opal/threads/mutex.h"
#include "ompi/communicator/communicator.h"
#include "ompi/mca/coll/coll.h"
#include "ompi/mca/bcol/bcol.h"
#include "opal/sys/atomic.h"
#include "coll_ml.h"
#include "coll_ml_select.h"
#include "coll_ml_allocation.h"
static int mca_coll_ml_allreduce_small_unpack(mca_coll_ml_collective_operation_progress_t *coll_op)
{
int ret;
/* need to put in more */
int count = coll_op->variable_fn_params.count;
ompi_datatype_t *dtype = coll_op->variable_fn_params.dtype;
void *dest = (void *)((uintptr_t)coll_op->full_message.dest_user_addr +
(uintptr_t)coll_op->fragment_data.offset_into_user_buffer);
void *src = (void *)((uintptr_t)coll_op->fragment_data.buffer_desc->data_addr +
(size_t)coll_op->variable_fn_params.rbuf_offset);
ret = ompi_datatype_copy_content_same_ddt(dtype, (int32_t) count, (char *) dest,
(char *) src);
if (ret < 0) {
return OMPI_ERROR;
}
ML_VERBOSE(10, ("sbuf addr %p, sbuf offset %d, rbuf addr %p, rbuf offset %d.",
src, coll_op->variable_fn_params.sbuf_offset, dest,
coll_op->variable_fn_params.rbuf_offset));
return OMPI_SUCCESS;
}
static int mca_coll_ml_allreduce_task_setup(mca_coll_ml_collective_operation_progress_t *coll_op)
{
int fn_idx, h_level, my_index, root;
mca_sbgp_base_module_t *sbgp;
mca_coll_ml_topology_t *topo = coll_op->coll_schedule->topo_info;
fn_idx = coll_op->sequential_routine.current_active_bcol_fn;
h_level = coll_op->coll_schedule->component_functions[fn_idx].h_level;
sbgp = topo->component_pairs[h_level].subgroup_module;
my_index = sbgp->my_index;
/* In the case of allreduce, the local leader is always the root */
root = 0;
if (my_index == root) {
coll_op->variable_fn_params.root_flag = true;
coll_op->variable_fn_params.root_route = NULL;
} else {
coll_op->variable_fn_params.root_flag = false;
coll_op->variable_fn_params.root_route = &topo->route_vector[root];
}
/* NTH: This was copied from the old allreduce launcher. */
if (0 < fn_idx) {
coll_op->variable_fn_params.sbuf = coll_op->variable_fn_params.rbuf;
coll_op->variable_fn_params.userbuf = coll_op->variable_fn_params.rbuf;
}
return OMPI_SUCCESS;
}
static int mca_coll_ml_allreduce_frag_progress(mca_coll_ml_collective_operation_progress_t *coll_op)
{
/* local variables */
const void *buf;
size_t dt_size;
int ret, frag_len, count;
ptrdiff_t lb, extent;
mca_bcol_base_payload_buffer_desc_t *src_buffer_desc;
mca_coll_ml_collective_operation_progress_t *new_op;
mca_coll_ml_module_t *ml_module = OP_ML_MODULE(coll_op);
ret = ompi_datatype_get_extent(coll_op->variable_fn_params.dtype, &lb, &extent);
if (ret < 0) {
return OMPI_ERROR;
}
dt_size = (size_t) extent;
/* Keep the pipeline filled with fragments */
while (coll_op->fragment_data.message_descriptor->n_active <
coll_op->fragment_data.message_descriptor->pipeline_depth) {
/* If an active fragment happens to have completed the collective during
* a hop into the progress engine, then don't launch a new fragment,
* instead break and return.
*/
if (coll_op->fragment_data.message_descriptor->n_bytes_scheduled
== coll_op->fragment_data.message_descriptor->n_bytes_total) {
break;
}
/* Get an ml buffer */
src_buffer_desc = mca_coll_ml_alloc_buffer(OP_ML_MODULE(coll_op));
if (NULL == src_buffer_desc) {
/* If there exist outstanding fragments, then break out
* and let an active fragment deal with this later,
* there are no buffers available.
*/
if (0 < coll_op->fragment_data.message_descriptor->n_active) {
return OMPI_SUCCESS;
}
/* It is useless to call progress from here, since
* ml progress can't be executed as result ml memsync
* call will not be completed and no memory will be
* recycled. So we put the element on the list, and we will
* progress it later when memsync will recycle some memory*/
/* The fragment is already on list and
* the we still have no ml resources
* Return busy */
if (!(coll_op->pending & REQ_OUT_OF_MEMORY)) {
coll_op->pending |= REQ_OUT_OF_MEMORY;
opal_list_append(&((OP_ML_MODULE(coll_op))->waiting_for_memory_list),
(opal_list_item_t *)coll_op);
ML_VERBOSE(10,("Out of resources %p adding to pending queue", coll_op));
} else {
ML_VERBOSE(10,("Out of resources %p", coll_op));
}
return OMPI_ERR_TEMP_OUT_OF_RESOURCE;
}
/* Get a new collective descriptor and initialize it */
new_op = mca_coll_ml_alloc_op_prog_single_frag_dag(ml_module,
ml_module->coll_ml_allreduce_functions[coll_op->fragment_data.current_coll_op],
coll_op->fragment_data.message_descriptor->src_user_addr,
coll_op->fragment_data.message_descriptor->dest_user_addr,
coll_op->fragment_data.message_descriptor->n_bytes_total,
coll_op->fragment_data.message_descriptor->n_bytes_scheduled);
MCA_COLL_IBOFFLOAD_SET_ML_BUFFER_INFO(new_op,
src_buffer_desc->buffer_index, src_buffer_desc);
new_op->fragment_data.current_coll_op = coll_op->fragment_data.current_coll_op;
new_op->fragment_data.message_descriptor = coll_op->fragment_data.message_descriptor;
/* set the task setup callback */
new_op->sequential_routine.seq_task_setup = mca_coll_ml_allreduce_task_setup;
/* We need this address for pointer arithmetic in memcpy */
buf = coll_op->fragment_data.message_descriptor->src_user_addr;
/* calculate the number of data types in this packet */
count = (coll_op->fragment_data.message_descriptor->n_bytes_total -
coll_op->fragment_data.message_descriptor->n_bytes_scheduled <
(size_t) OP_ML_MODULE(coll_op)->small_message_thresholds[BCOL_ALLREDUCE] ?
(coll_op->fragment_data.message_descriptor->n_bytes_total -
coll_op->fragment_data.message_descriptor->n_bytes_scheduled) / dt_size :
(size_t) coll_op->variable_fn_params.count);
/* calculate the fragment length */
frag_len = count*dt_size;
ret = ompi_datatype_copy_content_same_ddt(coll_op->variable_fn_params.dtype, count,
(char *) src_buffer_desc->data_addr, (char *) ((uintptr_t) buf + (uintptr_t)
coll_op->fragment_data.message_descriptor->n_bytes_scheduled));
if (ret < 0) {
return OMPI_ERROR;
}
/* No unpack for root */
new_op->process_fn = mca_coll_ml_allreduce_small_unpack;
/* Setup fragment specific data */
new_op->fragment_data.message_descriptor->n_bytes_scheduled += frag_len;
new_op->fragment_data.buffer_desc = src_buffer_desc;
new_op->fragment_data.fragment_size = frag_len;
(new_op->fragment_data.message_descriptor->n_active)++;
ML_SET_VARIABLE_PARAMS_BCAST(
new_op,
OP_ML_MODULE(new_op),
count,
MPI_BYTE,
src_buffer_desc,
0,
0,
frag_len,
src_buffer_desc->data_addr);
/* Fill in bcast specific arguments */
/* TBD: remove buffer_size */
new_op->variable_fn_params.buffer_size = frag_len;
new_op->variable_fn_params.count = count;
new_op->variable_fn_params.hier_factor = coll_op->variable_fn_params.hier_factor;
new_op->variable_fn_params.op = coll_op->variable_fn_params.op;
new_op->variable_fn_params.dtype = coll_op->variable_fn_params.dtype;
new_op->variable_fn_params.root = 0;
new_op->variable_fn_params.sbuf = src_buffer_desc->data_addr;
new_op->variable_fn_params.rbuf = src_buffer_desc->data_addr;
new_op->sequential_routine.current_bcol_status = SEQ_TASK_PENDING;
MCA_COLL_ML_SET_NEW_FRAG_ORDER_INFO(new_op);
ML_VERBOSE(10,("FFFF Contig + fragmentation [0-sk, 1-lk, 3-su, 4-lu] %d %d %d",
new_op->variable_fn_params.buffer_size,
new_op->fragment_data.fragment_size,
new_op->fragment_data.message_descriptor->n_bytes_scheduled));
/* initialize first coll */
ret = new_op->sequential_routine.seq_task_setup(new_op);
if (OMPI_SUCCESS != ret) {
ML_VERBOSE(3,("Fragment failed to initialize itself"));
return ret;
}
/* append this collective !! */
OPAL_THREAD_LOCK(&(mca_coll_ml_component.sequential_collectives_mutex));
opal_list_append(&mca_coll_ml_component.sequential_collectives,
(opal_list_item_t *)new_op);
OPAL_THREAD_UNLOCK(&(mca_coll_ml_component.sequential_collectives_mutex));
}
return OMPI_SUCCESS;
}
static inline __opal_attribute_always_inline__
int parallel_allreduce_start(const void *sbuf, void *rbuf, int count,
struct ompi_datatype_t *dtype, struct ompi_op_t *op,
struct ompi_communicator_t *comm,
mca_coll_ml_module_t *ml_module,
ompi_request_t **req,
int small_data_allreduce,
int large_data_allreduce)
{
int ret, n_fragments = 1, frag_len,
pipeline_depth, n_dts_per_frag ;
ptrdiff_t lb, extent;
size_t pack_len, dt_size;
mca_bcol_base_payload_buffer_desc_t *src_buffer_desc;
mca_coll_ml_collective_operation_progress_t *coll_op;
mca_coll_ml_component_t *cm = &mca_coll_ml_component;
bool contiguous = ompi_datatype_is_contiguous_memory_layout(dtype, count);
if (MPI_IN_PLACE == sbuf) {
sbuf = rbuf;
}
ret = ompi_datatype_get_extent(dtype, &lb, &extent);
if (ret < 0) {
return OMPI_ERROR;
}
dt_size = (size_t) extent;
pack_len = count * dt_size;
ML_VERBOSE(1,("The allreduce requested %d enable fragmentation %d ",
pack_len,
cm->enable_fragmentation));
if (pack_len <= (size_t) ml_module->small_message_thresholds[BCOL_ALLREDUCE]) {
/* The len of the message can not be larger than ML buffer size */
assert(pack_len <= ml_module->payload_block->size_buffer);
ML_VERBOSE(1,("Using small data allreduce (threshold = %d)",
ml_module->small_message_thresholds[BCOL_ALLREDUCE]));
src_buffer_desc = mca_coll_ml_alloc_buffer(ml_module);
while (OPAL_UNLIKELY(NULL == src_buffer_desc)) {
opal_progress();
src_buffer_desc = mca_coll_ml_alloc_buffer(ml_module);
}
coll_op = mca_coll_ml_alloc_op_prog_single_frag_dag(ml_module,
ml_module->coll_ml_allreduce_functions[small_data_allreduce],
sbuf, rbuf, pack_len, 0);
coll_op->variable_fn_params.rbuf = src_buffer_desc->data_addr;
coll_op->variable_fn_params.sbuf = src_buffer_desc->data_addr;
coll_op->variable_fn_params.count = count;
ret = ompi_datatype_copy_content_same_ddt(dtype, count,
(void *) (uintptr_t) src_buffer_desc->data_addr, (char *) sbuf);
if (ret < 0){
return OMPI_ERROR;
}
/* unpack function */
coll_op->process_fn = mca_coll_ml_allreduce_small_unpack;
} else if (cm->enable_fragmentation || !contiguous) {
ML_VERBOSE(1,("Using Fragmented Allreduce"));
/* fragment the data */
/* check for retarded application programming decisions */
if (dt_size > (size_t) ml_module->small_message_thresholds[BCOL_ALLREDUCE]) {
ML_ERROR(("Sorry, but we don't support datatypes that large"));
return OMPI_ERROR;
}
/* calculate the number of data types that can fit per ml-buffer */
n_dts_per_frag = ml_module->small_message_thresholds[BCOL_ALLREDUCE] / dt_size;
/* calculate the number of fragments */
n_fragments = (count + n_dts_per_frag - 1) / n_dts_per_frag; /* round up */
/* calculate the actual pipeline depth */
pipeline_depth = n_fragments < cm->pipeline_depth ? n_fragments : cm->pipeline_depth;
/* calculate the fragment size */
frag_len = n_dts_per_frag * dt_size;
/* allocate an ml buffer */
src_buffer_desc = mca_coll_ml_alloc_buffer(ml_module);
while (NULL == src_buffer_desc) {
opal_progress();
src_buffer_desc = mca_coll_ml_alloc_buffer(ml_module);
}
coll_op = mca_coll_ml_alloc_op_prog_single_frag_dag(ml_module,
ml_module->coll_ml_allreduce_functions[small_data_allreduce],
sbuf, rbuf, pack_len, 0 /* offset for first pack */);
/* task setup callback function */
coll_op->sequential_routine.seq_task_setup = mca_coll_ml_allreduce_task_setup;
coll_op->process_fn = mca_coll_ml_allreduce_small_unpack;
coll_op->variable_fn_params.sbuf = (void *) src_buffer_desc->data_addr;
coll_op->variable_fn_params.rbuf = (void *) src_buffer_desc->data_addr;
coll_op->fragment_data.message_descriptor->n_active = 1;
coll_op->full_message.n_bytes_scheduled = frag_len;
coll_op->full_message.fragment_launcher = mca_coll_ml_allreduce_frag_progress;
coll_op->full_message.pipeline_depth = pipeline_depth;
coll_op->fragment_data.current_coll_op = small_data_allreduce;
coll_op->fragment_data.fragment_size = frag_len;
coll_op->variable_fn_params.count = n_dts_per_frag; /* seems fishy */
coll_op->variable_fn_params.buffer_size = frag_len;
/* copy into the ml-buffer */
ret = ompi_datatype_copy_content_same_ddt(dtype, n_dts_per_frag,
(char *) src_buffer_desc->data_addr, (char *) sbuf);
if (ret < 0) {
return OMPI_ERROR;
}
} else {
ML_VERBOSE(1,("Using zero-copy ptp allreduce"));
coll_op = mca_coll_ml_alloc_op_prog_single_frag_dag(ml_module,
ml_module->coll_ml_allreduce_functions[large_data_allreduce],
sbuf, rbuf, pack_len, 0);
coll_op->variable_fn_params.userbuf =
coll_op->variable_fn_params.sbuf = sbuf;
coll_op->variable_fn_params.rbuf = rbuf;
/* The ML buffer is used for testing. Later, when we
* switch to use knem/mmap/portals this should be replaced
* appropriately
*/
src_buffer_desc = mca_coll_ml_alloc_buffer(ml_module);
while (NULL == src_buffer_desc) {
opal_progress();
src_buffer_desc = mca_coll_ml_alloc_buffer(ml_module);
}
coll_op->variable_fn_params.count = count;
}
MCA_COLL_IBOFFLOAD_SET_ML_BUFFER_INFO(coll_op, src_buffer_desc->buffer_index,
src_buffer_desc);
/* set the offset */
coll_op->variable_fn_params.sbuf_offset = 0;
coll_op->variable_fn_params.rbuf_offset = 0;
/* Fill in the function arguments */
coll_op->variable_fn_params.sequence_num =
OPAL_THREAD_ADD32(&(ml_module->collective_sequence_num), 1);
coll_op->sequential_routine.current_active_bcol_fn = 0;
coll_op->variable_fn_params.dtype = dtype;
coll_op->variable_fn_params.op = op;
coll_op->variable_fn_params.root = 0;
coll_op->sequential_routine.seq_task_setup = mca_coll_ml_allreduce_task_setup; /* invoked after each level in sequential
* progress call
*/
MCA_COLL_ML_SET_ORDER_INFO(coll_op, n_fragments);
ret = mca_coll_ml_launch_sequential_collective (coll_op);
if (ret != OMPI_SUCCESS) {
ML_VERBOSE(10, ("Failed to launch"));
return ret;
}
*req = &coll_op->full_message.super;
return OMPI_SUCCESS;
}
int mca_coll_ml_allreduce(const void *sbuf, void *rbuf, int count,
struct ompi_datatype_t *dtype, struct ompi_op_t *op,
struct ompi_communicator_t *comm,
mca_coll_base_module_t *module)
{
mca_coll_ml_module_t *ml_module = (mca_coll_ml_module_t*)module;
ompi_request_t *req;
int ret;
if (OPAL_UNLIKELY(!ompi_op_is_commute(op))) {
/* coll/ml does not handle non-communative operations at this time. fallback
* on another collective module */
return ml_module->fallback.coll_allreduce (sbuf, rbuf, count, dtype, op, comm,
ml_module->fallback.coll_allreduce_module);
}
ret = parallel_allreduce_start(sbuf, rbuf, count, dtype, op, comm,
(mca_coll_ml_module_t *) module, &req,
ML_SMALL_DATA_ALLREDUCE,
ML_LARGE_DATA_ALLREDUCE);
if (OPAL_UNLIKELY(OMPI_SUCCESS != ret)) {
ML_ERROR(("Failed to launch"));
return ret;
}
ompi_request_wait_completion(req);
ompi_request_free(&req);
ML_VERBOSE(10, ("Blocking NB allreduce is done"));
return OMPI_SUCCESS;
}
int mca_coll_ml_allreduce_nb(const void *sbuf, void *rbuf, int count,
struct ompi_datatype_t *dtype, struct ompi_op_t *op,
struct ompi_communicator_t *comm,
ompi_request_t **req,
mca_coll_base_module_t *module)
{
mca_coll_ml_module_t *ml_module = (mca_coll_ml_module_t*)module;
int ret;
if (OPAL_UNLIKELY(!ompi_op_is_commute(op))) {
/* coll/ml does not handle non-communative operations at this time. fallback
* on another collective module */
return ml_module->fallback.coll_iallreduce (sbuf, rbuf, count, dtype, op, comm, req,
ml_module->fallback.coll_iallreduce_module);
}
ret = parallel_allreduce_start(sbuf, rbuf, count, dtype, op, comm,
(mca_coll_ml_module_t *) module, req,
ML_SMALL_DATA_ALLREDUCE,
ML_LARGE_DATA_ALLREDUCE);
if (OPAL_UNLIKELY(OMPI_SUCCESS != ret)) {
ML_ERROR(("Failed to launch"));
return ret;
}
ML_VERBOSE(10, ("Blocking NB allreduce is done"));
return OMPI_SUCCESS;
}
int mca_coll_ml_allreduce_dispatch(const void *sbuf, void *rbuf, int count,
struct ompi_datatype_t *dtype, struct ompi_op_t *op,
struct ompi_communicator_t *comm, mca_coll_base_module_t *module)
{
int rc;
bool use_extra_topo;
ompi_request_t *req;
mca_coll_ml_module_t *ml_module = (mca_coll_ml_module_t *) module;
use_extra_topo = (count > 1) ?
!ml_module->allreduce_matrix[op->op_type][dtype->id][BCOL_MULTI_ELEM_TYPE] :
!ml_module->allreduce_matrix[op->op_type][dtype->id][BCOL_SINGLE_ELEM_TYPE];
if (use_extra_topo) {
rc = parallel_allreduce_start(sbuf, rbuf, count, dtype,
op, comm, ml_module, &req,
ML_SMALL_DATA_EXTRA_TOPO_ALLREDUCE,
ML_LARGE_DATA_EXTRA_TOPO_ALLREDUCE);
} else {
rc = parallel_allreduce_start(sbuf, rbuf, count, dtype,
op, comm, ml_module, &req,
ML_SMALL_DATA_ALLREDUCE,
ML_LARGE_DATA_ALLREDUCE);
}
if (OPAL_UNLIKELY(OMPI_SUCCESS != rc)) {
ML_ERROR(("Failed to launch"));
return rc;
}
ompi_request_wait_completion(req);
ompi_request_free(&req);
return OMPI_SUCCESS;
}
int mca_coll_ml_allreduce_dispatch_nb(const void *sbuf, void *rbuf, int count,
ompi_datatype_t *dtype, ompi_op_t *op,
ompi_communicator_t *comm,
ompi_request_t **req,
mca_coll_base_module_t *module)
{
int rc;
bool use_extra_topo;
mca_coll_ml_module_t *ml_module = (mca_coll_ml_module_t *) module;
use_extra_topo = (count > 1) ?
!ml_module->allreduce_matrix[op->op_type][dtype->id][BCOL_MULTI_ELEM_TYPE] :
!ml_module->allreduce_matrix[op->op_type][dtype->id][BCOL_SINGLE_ELEM_TYPE];
if (use_extra_topo) {
rc = parallel_allreduce_start(sbuf, rbuf, count, dtype,
op, comm, ml_module, req,
ML_SMALL_DATA_EXTRA_TOPO_ALLREDUCE,
ML_LARGE_DATA_EXTRA_TOPO_ALLREDUCE);
} else {
rc = parallel_allreduce_start(sbuf, rbuf, count, dtype,
op, comm, ml_module, req,
ML_SMALL_DATA_ALLREDUCE,
ML_LARGE_DATA_ALLREDUCE);
}
if (OPAL_UNLIKELY(OMPI_SUCCESS != rc)) {
ML_ERROR(("Failed to launch"));
return rc;
}
return OMPI_SUCCESS;
}