product brief Intel® Vision Products OpenVINO™ Toolkit, Intel® Movidius™ VPUs, Intel® FPGAs
The OpenVINO™ toolkit streamlines vision solutions across A robust Intel® AI silicon portfolio
Fast-track enhanced deep learning inference at the edge
“Our partnership with Intel Edge-to-cloud vision—from deep learning to artificial allows us to bring the power intelligence of AI to clinical diagnostic Data is driving a massive paradigm shift in our understanding of how we use and learn from connected systems in a variety of industries—and much of this data scanning and other healthcare relies heavily on vision systems and their ability to capture immense amounts of workflows in a cost-effective information. Regardless of whether it’s gathered by connected sensors or smart cameras, or whether it’s analyzed at the edge or in the cloud, the data from these manner.” vision systems is enabling actionable intelligence for businesses everywhere. – David Chevalier, principal engineer, Consider machine vision-based predictive maintenance at a manufacturing GE Healthcare plant, facial recognition software supporting law enforcement in smart cities or transforming consumer retail experiences, or image-based research on the human genome. “Dell EMC’s surveillance labs Intel® Vision Products integrate advanced software and hardware to capture validation program and joint complex, dynamic visual content from the edge to the cloud, with exceptional collaboration with Intel allows richness and accuracy. By delivering data processing flexibility at the edge—both in cameras and on-premise servers—and scalability in the cloud, these solutions us to deliver proven solutions are driving next-generation artificial intelligence and analytics, and enabling with the top surveillance powerful deep learning inferencing capabilities across various industries. camera and video software And while these industries may be diverse in their business offerings, they have a few big things in common: the need for fast access to data at the edge, powerful companies.” performance to process and analyze bandwidth-intensive visual data, and the – Ken Mills, general manager, agility and manageability to quickly turn data into insight. This is where Intel’s Surveillance and Security Solutions, comprehensive AI portfolio comes into play. Dell EMC Product Brief | OpenVINO™ Toolkit, Intel® Movidius™ VPUs, Intel® FPGAs
A path to vision innovation: building on top of the OpenVINO™ toolkit Benefits of the OpenVINO™ toolkit Intel’s innovative technology portfolio enables OEMs, ODMs, • Accelerate application performance across a range ISVs, SIs, and developers to speed time to market and deliver of heterogeneous Intel® architectures to deliver fast, increased value to end customers seeking smart vision efficient deep learning and AI workloads solutions. The OpenVINO™ toolkit enables acceleration of • Speed up deep learning inferencing from the camera high-performance computer vision applications and deep to the cloud learning inferencing. The toolkit helps developers and data scientists speed computer vision workloads, streamline deep • Offers ease of use and speeds time to market for learning deployments, and enable easy execution across application developers Intel® platforms, from camera to cloud. As a primary component of Intel’s diverse AI portfolio, the You can think of the OpenVINO toolkit as the one suite that OpenVINO toolkit enhances vision system capabilities and enables end-to-end vision solutions—whether you want performance through deep learning acceleration silicon— the flexibility of programmable accelerators or to maximize on Intel® architecture (IA) and our Deep Learning (DL) VPU performance. Applications can be deployed on existing accelerators (FPGA, Movidius™ VPU). This gives innovators Intel®-based products and infrastructure, while offering added flexibility to choose the right combination of the flexibility to integrate efficient, high-performance performance, power, and cost efficiency for a specific accelerators without having to use new development vision solution. methodologies.
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Traditional computer vision for Intel® CPU/CPU with Model Optimi er integrated graphics—optimized computer vision libraries Convert and optimize OpenCV OpenVX
Helps increase processor graphics performance—Linux* only
IR = Intermediate Intel® Media SDK OpenCL™ IR representation format (Open source version) Intel® Integrated Graphics drivers and runtimes
Linux for FPGA only Trained FPGA runtime environment (RTE) Intel® FPGA Deep models Inference engine (from Intel® FPGA SD for OpenCL™) Learning Acceleration Optimized inference Bitstreams Suite (DLAS)
cpu gpu fpga Vpu
Innovation where and when you need it, so you can move forward with AI solutions that deliver edge-to-cloud visual intelligence
This toolkit enables developers to easily integrate deep redeployed on an Intel® FPGA in a server, the OpenVINO learning inference into their applications using industry- Model Optimizer seamlessly manages code deployment standard AI frameworks and standard or custom layers.1 across different target platforms. This allows developers These can then be deployed across the continuum of to create the application and choose the Intel architecture Intel-based product lines—from camera to cloud— compute capabilities necessary for the solution from across irrespective of the target platform on which they will be the continuum of Intel® technologies—saving significant time run.2 With OpenVINO, developers can write code once and and development resources. Using the OpenVINO toolkit, make it future-proof for fast, seamless deployment across developers write to an API for Intel’s inferencing engine. current and future Intel® hardware - eliminating application Intel’s innovative solution portfolio is not just about this redevelopment.3 high-performance software, however; it combines it with The toolkit’s Model Optimizer takes care of preparing industry-leading silicon so that you can more easily make the algorithm for various Intel® hardware platforms. For vision-based AI solutions part of your growth strategy. example, if the algorithm is originally developed for a And the opportunity is compelling. camera with an Intel Movidius VPU and later needs to be
2 Product Brief | OpenVINO™ Toolkit, Intel® Movidius™ VPUs, Intel® FPGAs
Up to $11 billion in edge to Global IP video traffic is expected to edge-to-cloudcloud industry industryexpenditure be 82 percent of all IP traffic (both expenditureis expected by is expected2021.3 by business and consumer) by 2021, up 2021.Video1 capturedVideo captured at the at fromfrom 7373 percentpercent inin 2016.2016. theedge edge by smart by smart devices, devices, This represents a threefold growth sensors, and connected $11b $6b and CAGR of 26 percent, with Internetinternet 11b 6b things represents a huge Edge-to-cloudEdge to cloud Video things represents a huge industry at the edge video traffic growing fourfold from industry at the edge portion—$6 billion—of 2016 to 2021 with a CAGR of 31 this IoT opportunity for 2 percent.4 everything from smart manufacturing to smart 1 2016 2021 cities. 3 2016 2021 InternetInternet videovideo traffictraffic
“The“Hikvision OpenVINO is collaborating toolkit enables with Intelus to on optimize end-to-end our deep AI/DL learning solutions, solution from front-endacross multiple Movidius platforms—and cameras to theback-end best part servers. is that We we are can excited do so byquickly the prospect and easily. of movingThe partnership to Myriad™ between X. We areIntel also and working GE has alwayswith Intel been strong,on Intel’s and newly it’s strengthened released OpenVINO™ by the fact toolkit that to this achieve new AI higher technology performance aligns so and well shorten to our thecorporate development vision ofcycle. delivering Hikvision cutting is looking edge forwardsolutions to to building all of our a strong,customers. long-term With the relationship OpenVINO with toolkit, Intel GE to isestablish now able tech to deliverleadership not onlyin AI/DL-based enhanced performancesolutions.” today, but also a path to future acceleration tomorrow.” — GE –Dr. Pu Shiliang, chief scientist, Hikvision
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3 Product Brief | OpenVINO™ Toolkit, Intel® Movidius™ VPUs, Intel® FPGAs
Intel® Movidius™ Myriad™ 2 and Intel® FPGAs Myriad™ X VPUs Intel® FPGAs offer a wide variety of configurable embedded These full-fledged system-on-chips (SoCs) are designed SRAM, high-speed transceivers, high-speed I/Os, logic specifically for on-device computer vision and neural blocks, and routing. Built-in intellectual property, network inferencing applications. Movidius VPUs have a combined with outstanding software tools, can lower dedicated architecture offering power efficiency for high- FPGA development time, power, and cost. quality image processing, computer vision, and deep neural At the edge, these versatile Intel FPGAs provide the flexibility networks, making them suitable to drive the demanding mix to program and reprogram the rate of acceleration as needs of vision-centric tasks in modern smart devices. evolve, while providing low latency implementation within The Intel® Movidius™ Myriad™ 2 VPU offers significant a small envelope. Intel FPGAs can combine AI algorithms computation performance and image processing capability with other functions into your system in a single chip, for low in a low-power footprint (~1 watt), making it suitable for latency, high throughput, and low total cost of ownership. many mobile IoT end uses. A highly programmable vision Because Intel FPGAs are reprogrammable, IoT designers processor, the Movidius VPU architecture is built for have the flexibility to respond to changing conditions (rapid teraflops of performance supporting multiple cameras with changes in sensor technologies that require new interfaces, flexible image signal processing pipes per camera and a HDR signal processing for image capture in mixed and dark robust overall dataflow design to mitigate any vision lighting conditions, support for a variety of computer vision processing bottlenecks. algorithms) and implement multiple behaviors within one edge device. Also, due to their parallel computing nature, Target applications include: FPGAs provide accelerated performance for surveillance and • Deep neural network-based classification other video-enabled applications. • Pose estimation • 3-D depth OpenVINO toolkit • Visual inertial odometry (navigation) • Gesture/eye tracking and recognition The OpenVINO toolkit is a free, downloadable toolkit that helps developers and data scientists fast-track development The Intel® Movidius™ Myriad™ X VPU is the most advanced of high-performance computer vision and deep learning into Movidius VPU and the first of its kind to feature the Neural vision applications. It enables deep learning on hardware Compute Engine—a dedicated hardware accelerator for accelerators and easy heterogeneous execution across deep neural network inferences. This accelerator delivers multiple types of Intel® platforms. It includes the Intel® Deep leading performance per watt (one trillion operations per Learning Deployment Toolkit with a model optimizer and second of deep neural network inferencing5), offering a level inference engine, along with optimized computer vision of on-device performance normally reserved for desktop- libraries and functions for OpenCV* and OpenVX*. class hardware. While the Myriad 2 VPU offers deep neural network support at low power, the Myriad X VPU can reach This comprehensive toolkit supports the full range of 10x higher performance for applications requiring multiple vision solutions, speeding computer vision workloads, neural networks running simultaneously.5 streamlining deep learning deployments, and enabling easy, heterogeneous execution across Intel® platforms from edge The Movidius Myriad X VPU also features 16 configurable to cloud. In combination with Intel’s diverse AI portfolio, the MIPI lanes capable of supporting up to eight HD-resolution OpenVINO toolkit provides the power to scale computer RGB sensors via direct connections. The high-throughput vision solutions. The wide range of advanced silicon allows inline ISP ensures streams are processed at high speeds, solution providers to match the performance, cost, and and new hardware encoders offer 4K support for both power-efficiency required at any node in an AI architecture. 30 Hz (H.264/H.265) and 60 Hz (M/JPEG) frame rates. And with 2.5 MB of homogeneous on-chip memory, the Movidius Myriad X VPU allows for up to 400 GB/sec of internal bandwidth, minimizing latency and reducing power consumption by minimizing off-chip data transfer. achIeVe The OpTImal balance Of pOWer effIcIencY and hIgh perfOrmance
use InTel mOVIdIus mYrIad 2 Vpu fOr use InTel mOVIdIus mYrIad Vpu fOr • igh-performance V U • Dedicated neural compute engine • Ultralow-power architecture • 16 high-performance S AVE cores • 12 programmable S AVE cores • Enhanced IS with support • Small footprint for embedded applications • New vision accelerators, including stereo depth • Support for multiple-V U configuration
4 Product Brief | OpenVINO™ Toolkit, Intel® Movidius™ VPUs, Intel® FPGAs
Sample use cases Intel® IoT vision technologies combine end-to-end intelligence and exceptional performance to help improve safety, operational efficiency, productivity, healthcare, and quality of life. Here are just a few of the real-world deployments based on Intel vision solutions.
SMART CITIES INDUSTRIAL MANUFACTURING RETAIL Traffic monitoring: Intel Industrial automation: Intel Responsive retail: Retailers FPGAs and Movidius vision solutions are helping using Intel computer vision VPUs on cameras can capture data enable intelligent factories solutions at the edge can and automatically send it to traffic to converge OT and IT—transforming quickly recognize specific customers intersections downstream for industrial business models and or customer behavior patterns and traffic optimization and planning. growth strategies. Solutions based deliver personalized, precision This information can be directly on AI technology produce more marketing. Fast, efficient processing by communicated with drivers via detailed, accurate, and meaningful in-store solutions based on Intel Core in-car systems or apps for route digital models of equipment and processors and Intel FPGAs delivers planning. License plate recognition processes for nuanced, data-informed sales information to associates in (LPR) on moving vehicles alerts law planning. Production controls become near-real time, empowering them with enforcement, while identification of autonomous and fluid, driving faster revenue-driving tools and the ability available parking spaces aids drivers time to market. to promote relevant products and in congested urban areas. services. Machine vision: Augmenting Public safety: With Myriad industrial machine vision with Operations management: With VPUs and algorithms developed AI is enabling more accurate Intel® AI technology, in-store using the OpenVINO toolkit, factory-automation applications. vision systems can alleviate the trained deep neural networks now Solutions are combining cameras, time constraint that many retailers face have the inferencing capabilities to computers, and algorithms to analyze as data being captured by video feeds analyze and identify missing children images and videos for actionable makes its way to a distant data center. through facial recognition. Cities intelligence at the edge. Intel FPGA- By using a computer vision solution equipped with the technology can be powered machine vision supports based on Intel architecture, retailers alerted when these trained datasets essential industrial functions, including can streamline operations, manage match a face in a crowd with a reported proactive equipment maintenance, inventory, optimize the supply chain, missing child, immediately alerting law defect detection, quality control, yield and improve merchandising. In turn, enforcement agencies. management, inventory verification, they can get more value from their product labeling, security monitoring, data through scalability, increased and worker training. efficiency and effectiveness, and lower total cost of ownership (TCO).
Your path to smart vision innovation Learn more about smart video from edge Accelerate high-performance computer vision, AI, to cloud machine learning, and deep learning solutions from Explore Intel IoT smart video solutions at camera to cloud, using Intel’s end-to-end solution intel.com/smartvideo. portfolio. Download the free OpenVINO™ toolkit at intel.com/visionproducts. Download the Myriad™ Development Kit (MDK) › For more information about Intel® IoT Technology and the Intel® IoT Solutions Alliance, please visit intel.com/iot.
1. The broad set of popular frameworks and topologies supported include, but are not limited to, Caffe*, Caffe2*, MXNet*, Neon*, TensorFlow*, Theano*, and Torch*. 2. While any standard algorithm will run on any Intel® silicon architecture, performance may vary from one architecture to another. In some cases, extra work may be needed using the OpenVINO™ toolkit to port an algorithm from one architecture to a different architecture. 3. “A Strategist’s Guide to the Internet of Things,” Frank Burkitt, strategy-business.com/article/00294?gko=a9303. 4. cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/vni-hyperconnectivity-wp.html 5. Maximum performance based on peak floating-point computational throughput of Neural Compute Engine. Actual results on deep neural networks may achieve less than peak throughput. Intel technologies’ features and benefits depend on system configuration and may require enabled hardware, software or service activation. Performance varies depending on system configuration. No computer system can be absolutely secure. Check with your system manufacturer or retailer or learn more atintel.com/iot . Cost reduction scenarios described are intended as examples of how a given Intel-based product, in the specified circumstances and configurations, may affect future costs and provide cost savings. Circumstances will vary. Intel does not guarantee any costs or cost reduction. Intel, the Intel logo, Arria, Intel Atom, Intel Core, Intel Movidius, Intel Movidius Myriad, OpenVINO, and Xeon are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. *Other names and brands may be claimed as the property of others. © Intel Corporation OpenCL and the OpenCL logo are trademarks of Apple Inc. used by permission by Khronos. 0518/DW/CMD/PDF 337634-001US 5