Machine Vision With The Hailo-8 AI Accelerator
TLDRAt Embedded World 2024, a demonstration showcased the Hailo-8 AI accelerator's capabilities in machine vision. The system, powered by Super Micro hardware with an Intel Alder Lake processor and Hailo's m.2 inferencing chip, efficiently processes images in 60 milliseconds with low power consumption. Ideal for pick-and-place and smart city applications, it highlights the synergy between software and hardware for edge AI solutions.
Takeaways
- 😀 The demonstration showcases the Hailo-8 AI accelerator's capabilities in machine vision applications.
- 🤖 The system is designed to handle tasks like pick and place with high efficiency, evaluating images in about 60 milliseconds.
- 🔌 The hardware setup includes Super Micro's compact and efficient system, featuring an Intel Alder Lake processor and the Hailo AI accelerator via an m.2 connector.
- 🏭 The solution is particularly beneficial for embedded systems, which are not commonly found in the market.
- 🌐 The technology is applicable in various fields such as smart cities, where it can handle tasks like people counting and identification.
- 💡 The system's low power consumption and fanless design make it suitable for machinery and automation, where dust and heat are concerns.
- 🔗 The Hailo chip acts as an accelerator, complementing the Intel chip by handling the AI workload, making the system efficient and powerful.
- 🔍 The system is capable of inference at the edge, which is crucial for real-time processing in applications like computer vision.
- 🛠️ Super Micro's role is to validate the entire system, ensuring it's ready for 24/7 operation as an embedded system.
- 🔬 The partnership between the processor and the accelerator is essential, with the CPU handling general compute tasks while the accelerator focuses on AI-specific tasks.
Q & A
What is the main focus of the demonstration at the Super Micro booth?
-The demonstration focuses on showcasing the capabilities of Hailo's AI hardware accelerator in conjunction with hardware and software partners, particularly its application in machine vision tasks.
How does the Hailo AI accelerator assist in a pick and place scenario?
-The Hailo AI accelerator is used to evaluate images quickly, taking about 60 milliseconds to process an image, which is crucial for high-performance systems in pick and place operations.
What is the power efficiency of the system running the Hailo AI accelerator?
-The system running the Hailo AI accelerator is highly efficient, consuming only around 5 watts, which is significant for embedded systems that require low power consumption.
Which hardware components are used in the demonstration by Super Micro?
-The hardware used in the demonstration includes an Intel Alder Lake processor and an inferencing chip from Hailo, connected via the m.2 connector.
What form factor is the Super Micro system presented in?
-The Super Micro system is presented in a compact, 3.5-inch form factor, which is suitable for embedded applications.
How does Super Micro ensure the reliability of their systems for customers?
-Super Micro validates the entire system, including hardware and software, to provide customers with a working sample that is assured to run 24/7 as an embedded system.
Besides pick and place applications, what other use cases does the Hailo AI accelerator support?
-The Hailo AI accelerator is primarily used for computer vision tasks such as smart city applications, including people counting and identification.
How does the low power consumption of the Hailo AI accelerator benefit machinery?
-The low power consumption of the Hailo AI accelerator makes it flexible for use in machinery, and its fanless design is advantageous as it prevents dust, which is electrically conductive, from causing issues within the machines.
Where does the Hailo chip fit into the system in terms of its position between the camera and the main processor?
-The Hailo chip can be positioned flexibly within the system architecture. It works in conjunction with the main processor, and its placement is not strictly defined as being between the camera and the processor.
What is the role of the Intel chip in the system demonstrated by Super Micro?
-The Intel chip provides the computational power for the system, while the Hailo chip acts as the AI accelerator, handling the inferencing tasks. The two work in tandem to perform the required AI workloads.
How does the architecture of the system using the Hailo AI accelerator differ from other AI solutions?
-The system using the Hailo AI accelerator differs by having a separate memory not on board of the module but on the single board computer itself, utilizing an OT interface, which is a different architecture compared to other AI solutions where memory might be integrated differently.
Outlines
🤖 AI Hardware Accelerator Demo at embedded World 2024
This paragraph introduces a demonstration of Halo's AI hardware accelerator at embedded World 2024. Joshua from Super Micro and Dominic from Denite discuss the integration of Halo's AI technology with hardware and software partners. The demo showcases the AI's ability to evaluate images for a pick-and-place task in just 60 milliseconds on a Super Micro system that consumes only about 5 watts. The conversation highlights the importance of vision technology and the efficiency of running AI on Halo's hardware, which is particularly beneficial for embedded systems. The hardware includes an Intel processor and an inferencing chip from Halo, demonstrating a compact and low-power solution for computer vision tasks.
🔌 Role of the Halo Chip in AI Solutions
The second paragraph delves into the positioning and function of the Halo chip within AI solutions. It clarifies that the chip can be placed anywhere in the system as it is the accelerator that primarily determines the speed of AI processing, rather than the main processor. The discussion points out that the Halo chip is crucial for tasks like computer vision, smart city applications, and people counting, due to its low power consumption and fanless design, making it suitable for machinery integration. The conversation also touches on the flexibility of the system architecture, where the memory is not on the module board but on the single board computer, and the use of an OTTO interface for the demo.
Mindmap
Keywords
💡Machine Vision
💡Hailo-8 AI Accelerator
💡Embedded World 2024
💡Super Micro
💡Intel Old Lake Processor
💡Inferencing
💡Smart Cities
💡PTZ Cameras
💡Edge Computing
💡Fanless System
Highlights
Demonstration of Hailo-8 AI hardware accelerator at Embedded World 2024.
Collaboration with hardware and software partners showcased.
Efficient pick and place machine vision task using the Hailo-8 accelerator.
AI technology running on the Hailo system takes about 60 milliseconds to evaluate an image.
The system operates on a Super Micro hardware platform with an Intel Alder Lake processor.
Hailo's m.2 connector inferencing chip is responsible for AI workloads.
Super Micro validates the entire system to ensure 24/7 operation as an embedded solution.
Hailo-8 is ideal for computer vision tasks such as smart city applications.
Support for PTZ cameras allows for people counting and identification.
The system is fanless, making it suitable for machinery with concerns about dust and electrical conductivity.
The compact size of the system allows for integration into complex machinery.
The AI workload is processed by the Hailo chip, complementing the Intel chip's computational power.
The accelerator chip's performance is crucial for AI solutions, regardless of the CPU.
The system's architecture is unique, with memory not on the module but on the single board computer.
The Hailo chip can be integrated at various points in the system, depending on the application's needs.
The demo highlights the importance of efficient hardware and software integration for AI applications.
The partnership between the processor and the accelerator chip is essential for the system's performance.
