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Use Intel TBB's parallel_sort even for nested parallelism.

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TBB has a global task scheduler (that's one of the reason TBB is not
linked statically but dyanmically instead). This allows control over all
running threads, enabling us to use nested parallelism and the scheduler
doing all the task allocation itself.

That is, nested parallel execution such as in

    parallel_for(seq, [](const auto& rng){
      parallel_sort(rng);
    });

is no problem at all, as the scheduler still claims control over the
global environment.

Therefore, use `parallel_sort` Range overload where possible.

References:

- https://www.threadingbuildingblocks.org/docs/help/hh_goto.htm#reference/algorithms.htm
- https://www.threadingbuildingblocks.org/docs/help/hh_goto.htm#reference/algorithms/parallel_sort_func.htm
- https://www.threadingbuildingblocks.org/docs/help/hh_goto.htm#reference/task_scheduler.htm
- https://www.threadingbuildingblocks.org/docs/help/hh_goto.htm#reference/task_scheduler/task_scheduler_init_cls.htm
- https://www.threadingbuildingblocks.org/docs/help/hh_goto.htm#tbb_userguide/Initializing_and_Terminating_the_Library.htm
This commit is contained in:
Daniel J. Hofmann
2015-09-09 17:22:51 +02:00
parent dfac34beac
commit 9231335eef
11 changed files with 93 additions and 71 deletions
Download Patch File Download Diff File Expand all files Collapse all files
plugins/match.hpp
+28 -18
View File
@@ -42,6 +42,8 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include "../util/json_util.hpp"
#include "../util/string_util.hpp"
#include <tbb/parallel_sort.h>
#include <cstdlib>
#include <algorithm>
@@ -97,7 +99,8 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
osrm::matching::CandidateLists &candidates_lists)
{
double query_radius = 10 * gps_precision;
double last_distance = coordinate_calculation::great_circle_distance(input_coords[0], input_coords[1]);
double last_distance =
coordinate_calculation::great_circle_distance(input_coords[0], input_coords[1]);
sub_trace_lengths.resize(input_coords.size());
sub_trace_lengths[0] = 0;
@@ -106,7 +109,8 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
bool allow_uturn = false;
if (0 < current_coordinate)
{
last_distance = coordinate_calculation::great_circle_distance(input_coords[current_coordinate - 1], input_coords[current_coordinate]);
last_distance = coordinate_calculation::great_circle_distance(
input_coords[current_coordinate - 1], input_coords[current_coordinate]);
sub_trace_lengths[current_coordinate] +=
sub_trace_lengths[current_coordinate - 1] + last_distance;
@@ -127,20 +131,24 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
std::vector<std::pair<PhantomNode, double>> candidates;
facade->IncrementalFindPhantomNodeForCoordinateWithMaxDistance(
input_coords[current_coordinate], candidates, query_radius);
input_coords[current_coordinate], candidates, query_radius);
// sort by foward id, then by reverse id and then by distance
std::sort(candidates.begin(), candidates.end(),
[](const std::pair<PhantomNode, double>& lhs, const std::pair<PhantomNode, double>& rhs) {
tbb::parallel_sort(
candidates, [](const std::pair<PhantomNode, double> &lhs,
const std::pair<PhantomNode, double> &rhs)
{
return lhs.first.forward_node_id < rhs.first.forward_node_id ||
(lhs.first.forward_node_id == rhs.first.forward_node_id &&
(lhs.first.reverse_node_id < rhs.first.reverse_node_id ||
(lhs.first.reverse_node_id == rhs.first.reverse_node_id &&
lhs.second < rhs.second)));
(lhs.first.forward_node_id == rhs.first.forward_node_id &&
(lhs.first.reverse_node_id < rhs.first.reverse_node_id ||
(lhs.first.reverse_node_id == rhs.first.reverse_node_id &&
lhs.second < rhs.second)));
});
auto new_end = std::unique(candidates.begin(), candidates.end(),
[](const std::pair<PhantomNode, double>& lhs, const std::pair<PhantomNode, double>& rhs) {
auto new_end = std::unique(
candidates.begin(), candidates.end(), [](const std::pair<PhantomNode, double> &lhs,
const std::pair<PhantomNode, double> &rhs)
{
return lhs.first.forward_node_id == rhs.first.forward_node_id &&
lhs.first.reverse_node_id == rhs.first.reverse_node_id;
});
@@ -165,10 +173,11 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
}
// sort by distance to make pruning effective
std::sort(candidates.begin(), candidates.end(),
[](const std::pair<PhantomNode, double>& lhs, const std::pair<PhantomNode, double>& rhs) {
return lhs.second < rhs.second;
});
tbb::parallel_sort(candidates, [](const std::pair<PhantomNode, double> &lhs,
const std::pair<PhantomNode, double> &rhs)
{
return lhs.second < rhs.second;
});
candidates_lists.push_back(std::move(candidates));
}
@@ -270,7 +279,8 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
const auto &input_timestamps = route_parameters.timestamps;
if (input_timestamps.size() > 0 && input_coords.size() != input_timestamps.size())
{
json_result.values["status"] = "Number of timestamps does not match number of coordinates .";
json_result.values["status"] =
"Number of timestamps does not match number of coordinates .";
return 400;
}
@@ -289,8 +299,8 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
return 400;
}
const bool found_candidates =
getCandiates(input_coords, route_parameters.gps_precision, sub_trace_lengths, candidates_lists);
const bool found_candidates = getCandiates(input_coords, route_parameters.gps_precision,
sub_trace_lengths, candidates_lists);
if (!found_candidates)
{
json_result.values["status"] = "No suitable matching candidates found.";