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nikos1
Valued Contributor I
214 Views

MKLDNN in R4 cannot max all CPU cores (50% CPU utilization)

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When testing YOLO3 I can only utilize 50% of the CPU cores on a i7-8700K CPU ( Ubuntu 16.04 LTS linux kernel 4.15.0-33-generic )

./object_detection_demo_yolov3_async -i test.mp4 -m fp32/yolo_v3.xml -d CPU
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Severine_H_Intel
Employee
214 Views

Dear Nikos,

I could reproduce your issue. You need to run the following command before calling your code: export OMP_WAIT_POLICY=PASSIVE

And OpenMP will use all the cores when running the code. 

Best, 

Severine

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5 Replies
nikos1
Valued Contributor I
213 Views

Same issue with SSD

./object_detection_demo_ssd_async -i test.mp4  -m SSD_fp32.xml  -d CPU

 

Severine_H_Intel
Employee
215 Views

Dear Nikos,

I could reproduce your issue. You need to run the following command before calling your code: export OMP_WAIT_POLICY=PASSIVE

And OpenMP will use all the cores when running the code. 

Best, 

Severine

View solution in original post

nikos1
Valued Contributor I
213 Views

Thank you Severine, the following worked, fps still remain the same though.

export OMP_WAIT_POLICY=PASSIVE
Afrath__Mohamed
Beginner
213 Views

Hi Nikos, i would like to convert yolov3 daraknet weights to openvino ir format using model optimizer? can you give you model optimizer command options for the same? or the procedure that you used for  "fp32/yolo_v3.xml" ?

Afrath__Mohamed
Beginner
213 Views

Hi Severine, i face the same low fps issue with openvino R4 release. Where R3 release was faster. After migrated to R4 release the fps dropped by half. Even tried export OMP_WAIT_POLICY=PASSIVE command, there is minimal increase, while running inference my CPU loaded  upto 89%(4 cores).

My PC configurarion:

Model : Intel(R) Core(TM) i5-4460  CPU @ 3.20GHz

OS: Linux 4.10.0-28-generic 16.04.2-Ubuntu 

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