prod_env_mat: allocate GPU memory out of frame loop #2832
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Signed-off-by: Jinzhe Zeng <[email protected]>
Signed-off-by: Jinzhe Zeng <[email protected]>
Signed-off-by: Jinzhe Zeng <[email protected]>
Signed-off-by: Jinzhe Zeng <[email protected]>
Signed-off-by: Jinzhe Zeng <[email protected]>
Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## devel #2832 +/- ##
==========================================
- Coverage 75.52% 75.26% -0.26%
==========================================
Files 242 242
Lines 24370 24466 +96
Branches 1571 1580 +9
==========================================
+ Hits 18405 18414 +9
- Misses 5037 5121 +84
- Partials 928 931 +3
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Signed-off-by: Jinzhe Zeng <[email protected]>
wanghan-iapcm
approved these changes
Sep 18, 2023
Signed-off-by: Jinzhe Zeng <[email protected]>
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Allocating GPU memory is not a cheap operator. This PR allocates memory for
int_temp,uint64_temp, andtensor_list[0, 1, 3, 4, 5, 6]out of the frame loop, so they can be reused in each loop without allocating many times.In the original code,
tensor_list[3],tensor_list[4], andtensor_list[6]may need to reallocate if the memory is not enough. This behavior still exists.The shape of
tensor_list[2]is dynamic, so it is not refactored in this PR.With CUDA enabled, unit tests for C++ and Python can pass. The examples can be performed.
The speedup can be observed when the number of frames (samples) in a batch is not small.