prg_prgncs

PRG's Setup of Intel Neural Compute Stick

Installation

• Step 1
• Step 2 (Needs PC Restart after this!)
• Step 3: sudo bash /opt/intel/openvino/deployment_tools/demo/setupvars.sh
• Step 4: cd /opt/intel/openvino/deployment_tools/demo && ./demo_benchmark_app.sh -d MYRIAD
• NOTE: All tests were run at USB 2.0

Custom Model Conversion

• Step 1: cd NCS-2 && python tf_model.py -s [1,256,256,1] -l [4,8,16]
• Step 2: python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_meta_graph mnist_model.meta --input_shape [1,256,256,1] --data_type FP16
• Step 3: source /opt/intel/openvino/bin/setupvars.sh
• Step 4: python3 movi2.py

Speed Test

Image size is [BWHC] [ batch size x width x height x color channels] and ResNet architecture. Num Output layers = 4.

Image size	Filters in subsequent layers	FPS	NumParams	NumFLOPs
1 x 256 x 256 x 1	[16,32,64,128]	7.5	745364	3559699941
1 x 512 x 512 x 1	[16,32,64,128]	2.0	745364	14234334693
1 x 256 x 256 x 2	[16,32,64,128]	7.25	745524	3580671781
1 x 256 x 256 x 6	[16,32,64,128]	6.01	746164	3664559141
1 x 256 x 256 x 1	[8,16,32,64]	11.2	186828	917679877
1 x 512 x 512 x 1	[8,16,32,64]	3.0	186828	3669602053
1 x 256 x 256 x 2	[8,16,32,64]	10.7	186908	928165797
1 x 256 x 256 x 6	[8,16,32,64]	8.2	187228	970109477
1 x 256 x 256 x 1	[10,15,23,35,53,80,120]	10.3	917033	824121066
1 x 512 x 512 x 1	[10,15,23,35,53,80,120]	2.8	917033	3290991978
1 x 256 x 256 x 2	[10,15,23,35,53,80,120]	9.9	917133	837228466
1 x 256 x 256 x 6	[10,15,23,35,53,80,120]	7.7	917533	889658066
1 x 256 x 256 x 6	[8,12,18,27,41,61,92]	8.4	540871	580564264

• Increasing Depth has small effect on speed
• Increasing Width has a huge effect on speed
• Input dimension size has a huge effect on speed