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Neural Network Graph
Resource processing breakdown
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Resource Graph
Physical resource mapping
During the build flow, the Hailo dataflow compiler decomposes each network layer into the necessary computational elements. This process generates a resource graph that represents the target network.
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Hailo Processor
Dynamic configuration and execution
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Hailo-8™ Benchmarks
The Hailo-8™ AI accelerator brings industry-leading neural processing throughput and power efficiency to support a wide range of AI applications. The table below demonstrates some of Hailo-8’s best-in-class capabilities in the foundational neural tasks of object detection and classification. It achieves very high FPS and power efficiency (FPS/W) across a number of industry-standard neural network models, while also offloading post-processing from the host processor it is working with.
| NN Model | Input Resolution | FPS | Power [W] | FPS/ W |
|---|---|---|---|---|
| Classification | ||||
| ResNet-50 v1 | 224×224 | 1,332 | 3.45 | 386 |
| MobileNet_v2_1.0 | 224×224 | 2,444 | 2.152 | 1,135 |
| Object Detection | ||||
| SSD_MobileNet_v1 | 300×300 | 1,055 | 2.2 | 479 |
| YOLOv5m | 640×640 | 218 | 4.6 | 47.3 |
| Segmentation | ||||
| stdc1 | 1024×1920 | 54 | 2.9 | 18.6 |
| Multi stream object detection (8 streams) | ||||
| YOLOv3 | 608×608 | 69 | 4.9 | 14 |
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Automotive
Security
Industrial Automation
Retail
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Read more about what we do
Hailo offers breakthrough AI accelerators and Vision processors
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Read more about what we do
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Our Partners
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Our Investors
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Benefits
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Breathe life into your edge products with Hailo’s AI Accelerators and Vision Processors
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Breathe life into your edge products with Hailo’s AI Accelerators and Vision Processors
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Breathe life into your edge products with Hailo’s AI Accelerators and Vision Processors
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Join the talent pool
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AI vision processors
The Hailo-15™ family of AI vision processors combines Hailo’s patented and field proven AI inferencing capabilities with advanced computer vision engines, enabling unprecedented video processing and analytics at a premium image quality.
AI accelerators
The Hailo-8™ AI accelerator allows edge devices to run deep learning applications at full scale more efficiently, effectively, and sustainably, with an architecture that takes advantage of the core properties of neural networks.
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Blog
The Evolution of AI on the Edge: From Perception to Creation
In the vast landscape of artificial intelligence (AI), one of the most intriguing journeys has been the evolution of AI on the edge. This journey has taken us from classic machine vision to the realms of discriminative AI, enhancive AI, and now, the groundbreaking frontier of generative AI. Each step has brought us closer to a future where intelligent systems seamlessly integrate with our daily lives, offering an immersive experience of not just perception but also creation at the palm of our hand.
Blog
Scaling Up Video Management Systems
Video Management Systems, also known as VMS, collect inputs from multiple cameras and other sensors, addressing all related aspects of video handling, such as storage, retrieval, analysis and display. VMS are typically used in the security and surveillance space, enhancing personal safety in public areas, office buildings, transportation terminals, medical institutes, and more. Other typical…
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Partner with us
We invite you to join our rapidly expanding ecosystem of world-class partners and become a part of our global community.
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Breathe life into your edge products with the Hailo AI Processors
Hailo presents a unique technology, designed to enable AI applications across a broad range of industries.
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Japan
2-15-1 Konan, Minato-ku, Tokyo 108-6028 Shinagawa Intercity Building-A 28F Japan
[email protected]
China & Taiwan
11F, No. 335, Building B, Ruiguang Road, Neihu District, Taipei 114063
[email protected]
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Gated Inner
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Fill in the form to meet our team
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Gated Inner
Join us at Electronica China in Shanghai, China.
Discover how you can boost your video analytics systems with the best-performing Hailo-8™ AI Processor for accurate and high-performance processing in real-time within an embedded power envelope.
Visit the Renesas booth # 7.2D202 where you will be able to see a live demo of 360° High-End Object Detection for L2+/L3 Automated Driving.
We are looking forward to scheduling a meeting or demo with you.
Fill in the form to meet our team!
Speakers
Artem Kroupenev
DevOps in Hailo
Artem Kroupenev
DevOps in Hailo
Artem Kroupenev
DevOps in Hailo
Fill in the form to meet our team
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Partners Ecosystem
A wide ecosystem of partners to help you design a complete solution
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About
Hailo is an AI chip manufacturing company for edge devices. Our mission is to create a better, safer, more productive and more convenient world.
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Join the Hailo team to change the world of AI
Hailo is a gamechanger in the industry of AI chips for the edge. Since we’re at the beginning of our journey, every new hire shapes and forms our company.
That’s why we care so much about bringing in great, talented people. We’re always looking for skilled people from diverse backgrounds and with unique perspectives to join our team.
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Innovative control scheme based on a combination of hardware and software reaching very low joules/operation with a high degree of flexibility
Innovative control scheme
Distributed memory fabric with purpose-built pipeline elements that allow very low-power memory access in neural network processing
Extremely efficient computational elements that can be applied variably, as needed
Dataflow-oriented interconnect adapts to the structure of the neural network and allows high resource utilization
Hailo Dataflow Compiler – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Lorem ipsum – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Dataflow-oriented interconnect adapts to the structure of the neural network and allows high resource utilization
Hailo Dataflow Compiler – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Distributed memory fabric with purpose-built pipeline
Lorem ipsum – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
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Lorem ipsum dolor sit amet
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Innovative control scheme based on a combination of hardware and software reaching very low joules/operation with a high degree of flexibility
Innovative control scheme
Distributed memory fabric with purpose-built pipeline elements that allow very low-power memory access in neural network processing
Extremely efficient computational elements that can be applied variably, as needed
Dataflow-oriented interconnect adapts to the structure of the neural network and allows high resource utilization
Hailo Dataflow Compiler – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Lorem ipsum – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Dataflow-oriented interconnect adapts to the structure of the neural network and allows high resource utilization
Hailo Dataflow Compiler – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Distributed memory fabric with purpose-built pipeline
Lorem ipsum – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
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Lorem ipsum dolor sit amet
Amet risus nullam eget felis eget nunc lobortis mattis aliquam. In iaculis nunc sed augue lacus viverra vitae
Innovative control scheme based on a combination of hardware and software reaching very low joules/operation with a high degree of flexibility
Innovative control scheme
Distributed memory fabric with purpose-built pipeline elements that allow very low-power memory access in neural network processing
Extremely efficient computational elements that can be applied variably, as needed
Dataflow-oriented interconnect adapts to the structure of the neural network and allows high resource utilization
Hailo Dataflow Compiler – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
Lorem ipsum – full-stack software co-designed with the hardware architecture of the neural network processor, enabling efficient deployment of neural network models with seamless integration to existing frameworks
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Model Explorer
The Model Explorer is intended for users who are in the process of selecting which Neural Network (NN) architecture to use on the Hailo AI processors. Selecting an appropriate model to use in your application can be hard. There are many considerations like inference speed, model availability, desired accuracy, license, and more. Inference speed is unique since it cannot be easily estimated without the underlying hardware used.
The Model Explorer is intended for users who are in the process of selecting which Neural Network (NN) architecture to use on the Hailo AI processors. Selecting an appropriate model to use in your application can be hard. There are many considerations like inference speed, model availability, desired accuracy, license, and more. Inference speed is unique since it cannot be easily estimated without the underlying hardware used.
AI Processor
Notes:
- System host: Intel® Core™ i5-9400 CPU @ 2.90GHz
- Hailo Dataflow Compiler version 3.23.0
- Measurements were taken at room temperature
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Advanced Driver
Assistance (ADAS)
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The Hailo Architecture
Hailo’s revolutionary architecture is a clean-slate approach to the design of a specialized technology stack. It has created a domain-specific processor that significantly outperforms the Von Neumann architecture for deep learning tasks.
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Last updated: 01/01/23
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Automotive
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Thank you for your inquiry
We’ll be in touch shortly
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Our Motivation
Artificial Intelligence and Deep Learning are revolutionary technologies that transform the way we use machines to perceive and analyze the world around us and respond in real-time to constantly evolving environments.
Back in 2017, when we founded Hailo, those disruptive technologies were limited to data centers, as they are costly, require high compute power and extensive hardware, and consume a significant amount of power.
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Our Motivation
Artificial Intelligence and Deep Learning are revolutionary technologies that transform the way we use machines to perceive and analyze the world around us and respond in real-time to constantly evolving environments.
Back in 2017, when we founded Hailo, those disruptive technologies were limited to data centers, as they are costly, require high compute power and extensive hardware, and consume a significant amount of power.
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Object detection
Detecting and classifying objects within an image is a crucial task in computer vision, known as object detection. Deep learning models trained on the COCO dataset, which is a popular dataset for object detection, offer varying tradeoffs between performance and accuracy. For instance, by running inference on Hailo-8, the YOLOv5m model achieves 218 FPS and 42.46mAP accuracy, while the SSD-MobileNet-v1 model attains 1055 FPS and 23.17mAP accuracy. The COCO dataset includes 80 unique classes of objects for general usage scenarios, including both indoor and outdoor scenes.
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Object detection
Detecting and classifying objects within an image is a crucial task in computer vision, known as object detection. Deep learning models trained on the COCO dataset, which is a popular dataset for object detection, offer varying tradeoffs between performance and accuracy. For instance, by running inference on Hailo-8, the YOLOv5m model achieves 218 FPS and 42.46mAP accuracy, while the SSD-MobileNet-v1 model attains 1055 FPS and 23.17mAP accuracy. The COCO dataset includes 80 unique classes of objects for general usage scenarios, including both indoor and outdoor scenes.
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Hailo Software Suite includes the following key components
Model Build Environment
Model Build Computer
Model Zoo, a variety of common and state-of-the-art pre-trained models and tasks in TensorFlow and ONNX.Hailo Dataflow Compiler, for offline compilation and optimization of user’s models for Hailo devices
Runtime Environment
Host processor
User Applications
TAPPAS Application Examples
OS IP Stack
Hailo RT
Hailo TAPPAS, set of full application examples, implementing pipeline elements and pre-trained AI tasksHailoRT production-grade and light runtime software package, running on the host processor for real-time inferencing the deep learning models compiled by the Dataflow Compiler
Runtime Environment 2
Hailo-15™
Hailo TAPPAS, set of full application examples, implementing pipeline elements and pre-trained AI tasksHailoRT production-grade and light runtime software package, running on the host processor for real-time inferencing the deep learning models compiled by the Dataflow Compiler 2
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Leadership Team
Andreas Lambauer
General Manager Europe
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Testimonials
Hailo-8 is achieving overwhelmingly high performance compared to conventional products.
The chip surpassed our expectations in all measured parameters, outperforming even with complex NN models and real-life conditions
This processor helps us overcome all the limitations
Hailo enables us to perform more sophisticated operations with more complex networks, and thus, offer more solutions to the wide array of manufacturers we work with
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Hailo’s Orr Danon Shares Lessons Learned from Deep Learning Deployments In Edge Devices
Practical answers to compiance challanges
Or Danon, Founder and CEO of Hailo, presents the “Lessons Learned from the Deployment of Deep Learning Applications In Edge Devices” tutorial at the September 2020 Embedded Vision Summit.
October 6, 2022
When choosing an object detection network for edge devices, there are many factors you should consider: compute power, memory resources, and many more. Which ones? This blogpost outlines everything you need to know when choosing an object detection network for your edge application. But remember, the Hailo-8™ processor provides high-performance computing on the edge and can have a prominent role in improving the accuracy of the network.