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f0c3b23684
Previously, the thread ID was acquired and released on every iteration of the for loop. The C++11 concurrent queue implementation is much slower than TBB's version and consequently this was a huge bottleneck. This introduces another ParallelFor API which takes the thread ID as a parameter in the evaluation function. This allows us to acquire and release the thread ID for each block of work which drastically improves the performance. This change brings us on par with OpenMP and TBB. See below for a timing comparison. Note: in this example this CLs C++11 version is faster to compute the residuals because TBB still must acquire the thread ID on every iteration, which has some overhead. Tested by building and running tests for no threading, OpenMP, TBB, and C++11 threads. Also ran bazel tests. ./bin/bundle_adjuster --input=problem-744-543562-pre.txt --num_threads=8 C++11 @Head Time (in seconds): Residual only evaluation 7.819692 (5) Jacobian & residual evaluation 11.606063 (6) Linear solver 47.860195 (5) Minimizer 70.877072 Total 90.806338 --------------------------------------------------- C++11 (This CL) Time (in seconds): Residual only evaluation 1.217500 (5) Jacobian & residual evaluation 5.796112 (6) Linear solver 44.080873 (5) Minimizer 54.635524 Total 77.640072 --------------------------------------------------- OpenMP Time (in seconds): Residual only evaluation 0.797023 (5) Jacobian & residual evaluation 5.633916 (6) Linear solver 43.280020 (5) Minimizer 53.199058 Total 76.250861 --------------------------------------------------- TBB Time (in seconds): Residual only evaluation 1.911095 (5) Jacobian & residual evaluation 5.557807 (6) Linear solver 44.074680 (5) Minimizer 55.002688 Total 78.052687 --------------------------------------------------- No Threads Time (in seconds): Residual only evaluation 2.939212 (5) Jacobian & residual evaluation 18.519874 (6) Linear solver 74.017837 (5) Minimizer 98.980080 Total 122.216391 Change-Id: I3af959b0771bbdfe8cad8c13896191d6ac903181