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Similar to NIPS - Deep learning @ Edge using Intel's NCS
NIPS - Deep learning @ Edge using Intel's NCS
- 1. Deep Learning @ Edgeusing Intel’s Neural Compute Stick Geeta Chauhan, CTO SVSG NIPS, Long Beach, Dec 4-10, 2017
- 2. Agenda Intelligence @Edge Intel Neural Compute Stick Deep Learning Overview Building IoT NCS App Use Cases for IoT References
- 3. Drivers for Intelligence@ Edge ~50 Billion IoT devices by 2020 Inefficient to “Ask Cloud” for every decision in field Power draining Bandwidth, resource hungry Long latencies Intelligence @ Edge for real- time smarts Local inferencing → compressed insights to cloud
- 4. Intelligent Devices Welcome Sara GoodKitty Mom fell down
- 5. Intel Neural Compute Stick Computer Vision & AI @ Edge Movidius Myraid X: DJI Drone, Flir, Google Clip, Tango… 6.5 mm X 6.5 mm 4Gb RAM, 1000 TFlops 600 Mpixels/sec throughput
- 6. What is Deep Learning? AINeural Networks composed of many layers Learn like humans Automated Feature Learning Layers are like Image Filters
- 7. Intel Neural Compute Stick 6.5 mm X 6.5 mm 12 SHAVE Vector Processors 600 MHz @ 1 Watt Int 8/16/32, Float 16/32 Open source NCSDK NCS Application Zoo Caffe, Tensorflow
- 8. NCS Developer Kit NCS SDK Profile, Compile, Check NCS API Device, Graph OpenDevice & AllocateGraph LoadTensor input image GetResults DeallocateGraph & CloseDevice
- 9. NCS Application Zoo Caffe GoogleNet AlexNet SqueezeNet Tiny Yolo Tensorflow Inception V1, V2, V3, V4 MobileNets
- 10. Transfer Learning Transfer Learning –New Classifier Inception V3
- 11. Demo Intel Neural ComputeStick Raspberry Pi + Pi Camera
- 12. Deep Learning IoTPipeline Inference on DeviceTrain Model in Cloud Optimize
- 13. What is Deep Learning? AINeural Networks composed of many layers Learn like humans Automated Feature Learning Layers are like Image Filters
- 14. Optimizations mvNCProfile, mvNCCompile,mvNCCheck Tensorflow Graph Transform Tool Intel’s Computer Vision SDK, Model Optimizer Quantize weights (20 M weights for IV3) Quantization (32 bit float → 8 bit int) Freeze Graph Inception v3 93 MB → 1.5 MB
- 15. Common Problem Solutions Usb configuration issues `lsusb –v`, `udevadm monitor –udev` Device heating up under heavy load Use thermal throttling Multiple NCS split workload Split the model, do part detection on device, rest in cloud Reduce the frequency eg only do on movement detection NCS Profile & Tensorboard are your friends – X-Ray vision Image size mismatch for the input tensor Output classifier specify correct number of classes from your model Tensorflow need meta data along with .pb files
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- 17. And Some More… Self Driving Car Wearable assistant for Blind (Horus) Smart Cameras, Security, Thermal Drones Sense & Avoid AR / VR Gesture Eye tracking, Depth Sensing Creative Arts, Music Generators Intelligent Robots Indoor Visual Navigation
- 18. References NCS GettingStarted: https://developer.movidius.com/start NCS Application Zoo: https://github.com/movidius/ncappzoo Intel Computer Vision SDK: https://software.intel.com/en-us/computer-vision-sdk Intel Deep Learning Inference Engine: https://software.intel.com/en- us/inference-engine-devguide-introduction Tensorflow Slim Pretrained Models: https://github.com/tensorflow/models/tree/master/research/slim#Pretrained Mobilenet models: https://research.googleblog.com/2017/06/mobilenets-open- source-models-for.html Transfer Learning: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/tutor ials/image_retraining.md Tensorboard Overview: https://www.youtube.com/watch?v=eBbEDRsCmv4 Cucumber Farmer Deep Learning Story
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