Intel® Distribution of OpenVINO™ Toolkit
Community assistance about the Intel® Distribution of OpenVINO™ toolkit, OpenCV, and all aspects of computer vision-related on Intel® platforms.
6510 Discussions

NSC2 Stages optimization problem

nago
Beginner
‎01-07-2019 07:57 AM
524 Views

Hello,

I generated .xml and. bin file from Tiny yolov2 voc by following intel guide.

And i'm able to make it work with the NCS1.

To get valid results with the NCS2. I have to add the following option :

plugin.SetConfig({ {"VPU_HW_STAGES_OPTIMIZATION","NO"}});

By doing this the frame rate is divided by 3.

With printPerformanceCounts we can see the differents optimization done for the NCS2 :

With VPU_HW_STAGES_OPTIMIZATION = NO:

0-convolutional               EXECUTED       layerType: Convolution        realTime: 2689       cpu: 2689           execType: Conv
0-convolutional@biases        EXECUTED       layerType: Convolution        realTime: 1480       cpu: 1480           execType: Bias
11-maxpool                    EXECUTED       layerType: Pooling            realTime: 173        cpu: 173            execType: MaxPool
12-convolutional              EXECUTED       layerType: Convolution        realTime: 7336       cpu: 7336           execType: Conv
12-convolutional@biases       EXECUTED       layerType: Convolution        realTime: 138        cpu: 138            execType: Bias
14-maxpool                    EXECUTED       layerType: Pooling            realTime: 160        cpu: 160            execType: MaxPool
15-convolutional              EXECUTED       layerType: Convolution        realTime: 7232       cpu: 7232           execType: Conv
15-convolutional@biases       EXECUTED       layerType: Convolution        realTime: 89         cpu: 89             execType: Bias
17-maxpool                    EXECUTED       layerType: Pooling            realTime: 176        cpu: 176            execType: MaxPool
18-convolutional              EXECUTED       layerType: Convolution        realTime: 37231      cpu: 37231          execType: Conv
18-convolutional@biases       EXECUTED       layerType: Convolution        realTime: 145        cpu: 145            execType: Bias
2-maxpool                     EXECUTED       layerType: Pooling            realTime: 954        cpu: 954            execType: MaxPool
20-convolutional              EXECUTED       layerType: Convolution        realTime: 38027      cpu: 38027          execType: Conv
20-convolutional@biases       EXECUTED       layerType: Convolution        realTime: 142        cpu: 142            execType: Bias
22-convolutional              EXECUTED       layerType: Convolution        realTime: 1308       cpu: 1308           execType: Conv
22-convolutional@biases       EXECUTED       layerType: Convolution        realTime: 60         cpu: 60             execType: Bias
3-convolutional               EXECUTED       layerType: Convolution        realTime: 5416       cpu: 5416           execType: Conv
3-convolutional@biases        EXECUTED       layerType: Convolution        realTime: 764        cpu: 764            execType: Bias
5-maxpool                     EXECUTED       layerType: Pooling            realTime: 514        cpu: 514            execType: MaxPool
6-convolutional               EXECUTED       layerType: Convolution        realTime: 4741       cpu: 4741           execType: Conv
6-convolutional@biases        EXECUTED       layerType: Convolution        realTime: 404        cpu: 404            execType: Bias
8-maxpool                     EXECUTED       layerType: Pooling            realTime: 269        cpu: 269            execType: MaxPool
9-convolutional               EXECUTED       layerType: Convolution        realTime: 14747      cpu: 14747          execType: Conv
9-convolutional@biases        EXECUTED       layerType: Convolution        realTime: 227        cpu: 227            execType: Bias
LeakyReLU_                    EXECUTED       layerType: ReLU               realTime: 778        cpu: 778            execType: LeakyRelu
LeakyReLU_372                 EXECUTED       layerType: ReLU               realTime: 123        cpu: 123            execType: LeakyRelu
LeakyReLU_373                 EXECUTED       layerType: ReLU               realTime: 401        cpu: 401            execType: LeakyRelu
LeakyReLU_374                 EXECUTED       layerType: ReLU               realTime: 125        cpu: 125            execType: LeakyRelu
LeakyReLU_375                 EXECUTED       layerType: ReLU               realTime: 124        cpu: 124            execType: LeakyRelu
LeakyReLU_376                 EXECUTED       layerType: ReLU               realTime: 198        cpu: 198            execType: LeakyRelu
LeakyReLU_377                 EXECUTED       layerType: ReLU               realTime: 97         cpu: 97             execType: LeakyRelu
LeakyReLU_378                 EXECUTED       layerType: ReLU               realTime: 1489       cpu: 1489           execType: LeakyRelu
Receive-Tensor                EXECUTED       layerType: Receive-Tensor     realTime: 0          cpu: 0              execType: Receive-Tensor
input@FP16                    EXECUTED       layerType: <Extra>            realTime: 588        cpu: 588            execType: Convert_f32f16
output/YoloRegion             EXECUTED       layerType: RegionYolo         realTime: 359        cpu: 359            execType: RegionYolo
output/YoloRegion@FP16        EXECUTED       layerType: <Extra>            realTime: 41         cpu: 41             execType: Convert_f16f32
Total time: 128745   microseconds

Without VPU_HW_STAGES_OPTIMIZATION = NO:

0-convolutional@soh=1/5       EXECUTED       layerType: Convolution        realTime: 1727       cpu: 1727           execType: MyriadXHwConvolution
0-convolutional@soh=2/5 + ... EXECUTED       layerType: Convolution        realTime: 1721       cpu: 1721           execType: MyriadXHwConvolution + injected[Copy]
0-convolutional@soh=3/5 + ... EXECUTED       layerType: Convolution        realTime: 1722       cpu: 1722           execType: MyriadXHwConvolution + injected[Copy]
0-convolutional@soh=4/5 + ... EXECUTED       layerType: Convolution        realTime: 1725       cpu: 1725           execType: MyriadXHwConvolution + injected[Copy]
0-convolutional@soh=5/5 + ... EXECUTED       layerType: Convolution        realTime: 414        cpu: 414            execType: MyriadXHwConvolution + injected[Copy]
0-convolutional@soh=5/5@co... EXECUTED       layerType: Convolution        realTime: 22         cpu: 22             execType: Copy
11-maxpool                    OPTIMIZED_OUT  layerType: Pooling            realTime: 0          cpu: 0              execType: Pooling
12-convolutional              EXECUTED       layerType: Convolution        realTime: 1390       cpu: 1390           execType: MyriadXHwConvolution
14-maxpool                    OPTIMIZED_OUT  layerType: Pooling            realTime: 0          cpu: 0              execType: Pooling
15-convolutional              EXECUTED       layerType: Convolution        realTime: 1718       cpu: 1718           execType: MyriadXHwConvolution
17-maxpool                    EXECUTED       layerType: Pooling            realTime: 139        cpu: 139            execType: MyriadXHwPooling
17-maxpool@padding            EXECUTED       layerType: Pooling            realTime: 1245       cpu: 1245           execType: CopyMakeBorder
18-convolutional@soc=1/2      EXECUTED       layerType: Convolution        realTime: 3350       cpu: 3350           execType: MyriadXHwConvolution
18-convolutional@soc=2/2      EXECUTED       layerType: Convolution        realTime: 3284       cpu: 3284           execType: MyriadXHwConvolution
18-convolutional@soc=2/2@ReLU EXECUTED       layerType: Convolution        realTime: 204        cpu: 204            execType: LeakyRelu
2-maxpool                     OPTIMIZED_OUT  layerType: Pooling            realTime: 0          cpu: 0              execType: Pooling
20-convolutional@soc=1/3      EXECUTED       layerType: Convolution        realTime: 4478       cpu: 4478           execType: MyriadXHwConvolution
20-convolutional@soc=2/3      EXECUTED       layerType: Convolution        realTime: 4412       cpu: 4412           execType: MyriadXHwConvolution
20-convolutional@soc=3/3 +... EXECUTED       layerType: Convolution        realTime: 4430       cpu: 4430           execType: MyriadXHwConvolution + injected[Sum]
20-convolutional@soc=3/3@ReLU EXECUTED       layerType: Convolution        realTime: 199        cpu: 199            execType: LeakyRelu
22-convolutional              EXECUTED       layerType: Convolution        realTime: 168        cpu: 168            execType: MyriadXHwConvolution
3-convolutional@soh=1/3       EXECUTED       layerType: Convolution        realTime: 1385       cpu: 1385           execType: MyriadXHwConvolution
3-convolutional@soh=2/3 + ... EXECUTED       layerType: Convolution        realTime: 1396       cpu: 1396           execType: MyriadXHwConvolution + injected[Copy]
3-convolutional@soh=3/3 + ... EXECUTED       layerType: Convolution        realTime: 185        cpu: 185            execType: MyriadXHwConvolution + injected[Copy]
3-convolutional@soh=3/3@co... EXECUTED       layerType: Convolution        realTime: 18         cpu: 18             execType: Copy
5-maxpool                     OPTIMIZED_OUT  layerType: Pooling            realTime: 0          cpu: 0              execType: Pooling
6-convolutional               EXECUTED       layerType: Convolution        realTime: 1427       cpu: 1427           execType: MyriadXHwConvolution
8-maxpool                     OPTIMIZED_OUT  layerType: Pooling            realTime: 0          cpu: 0              execType: Pooling
9-convolutional               EXECUTED       layerType: Convolution        realTime: 1283       cpu: 1283           execType: MyriadXHwConvolution
LeakyReLU_                    OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_372                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_372@soc=2/2@accum   EXECUTED       layerType: Convolution        realTime: 274        cpu: 274            execType: Sum
LeakyReLU_373                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_374                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_375                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_375@soc=3/3@accum   EXECUTED       layerType: Convolution        realTime: 211        cpu: 211            execType: Sum
LeakyReLU_376                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_377                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
LeakyReLU_378                 OPTIMIZED_OUT  layerType: ReLU               realTime: 0          cpu: 0              execType: ReLU
Receive-Tensor                EXECUTED       layerType: Receive-Tensor     realTime: 0          cpu: 0              execType: Receive-Tensor
input@FP16                    EXECUTED       layerType: <Extra>            realTime: 909        cpu: 909            execType: Convert_f32f16
output/YoloRegion             EXECUTED       layerType: RegionYolo         realTime: 527        cpu: 527            execType: RegionYolo
output/YoloRegion@FP16        EXECUTED       layerType: <Extra>            realTime: 42         cpu: 42             execType: Convert_f16f32
Total time: 40005    microseconds

 

I don't know how to make it work at max perf.

Best regards,

nago

 

 

 

 

 

0 Kudos

Link Copied

0 Replies
Reply

Community support is provided Monday to Friday. Other contact methods are available here.

Intel does not verify all solutions, including but not limited to any file transfers that may appear in this community. Accordingly, Intel disclaims all express and implied warranties, including without limitation, the implied warranties of merchantability, fitness for a particular purpose, and non-infringement, as well as any warranty arising from course of performance, course of dealing, or usage in trade.

For more complete information about compiler optimizations, see our Optimization Notice.