mirror of https://github.com/koide3/small_gicp.git
fix typo
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@ -72,7 +72,7 @@ python3 plot_kdtree.py
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```
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```
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- Multi-threaded implementation (TBB and OMP) can be up to **4x faster** than the single-threaded one (All the implementations are based on nanoflann).
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- Multi-threaded implementation (TBB and OMP) can be up to **4x faster** than the single-threaded one (All the implementations are based on nanoflann).
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- Basically the processing speed get faster as the number of threads increases, but the speed gain is not monotonic sometimes (because of the scheduling algorithm or some CPU(AMD 5995WX)-specific issues?).
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- The processing speed gets faster as the number of threads increases, but the speed gain is not monotonic sometimes (because of the scheduling algorithm or some CPU(AMD 5995WX)-specific issues?).
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- This benchmark only compares the construction time (query time is not included).
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- This benchmark only compares the construction time (query time is not included).
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@ -87,7 +87,7 @@ python3 plot_odometry.py
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- Single-thread `small_gicp::GICP` is about **2.4x and 1.9x faster** than `pcl::GICP` and `fast_gicp::GICP`, respectively.
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- Single-thread `small_gicp::GICP` is about **2.4x and 1.9x faster** than `pcl::GICP` and `fast_gicp::GICP`, respectively.
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- `small_gicp::(GICP|VGICP)` shows a better multi-thread scalability compared to `fast_gicp::(GICP|VGICP)`.
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- `small_gicp::(GICP|VGICP)` shows a better multi-thread scalability compared to `fast_gicp::(GICP|VGICP)`.
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- `small_gicp::GICP` parallelized with [TBB flow graph](src/odometry_benchmark_small_gicp_tbb_flow.cpp) shows an excellent scalablity to many-threads situations (**~128 threads**) but with latency degradation.
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- `small_gicp::GICP` parallelized with [TBB flow graph](src/odometry_benchmark_small_gicp_tbb_flow.cpp) shows an excellent scalability to many-threads situations (**~128 threads**) but with latency degradation.
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