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RLX COMPONENTS s.r.o. , Electronic Components Distributor.
RLX COMPONENTS s.r.o. , Electronic Components Distributor.
Hailo-8 M.2 AI Accelerator Module, Based On The 26TOPS Hailo-8 AI Processor, For Raspberry Pi 5 (WS-27841)
Hailo-8 M.2 module + PCIe TO M.2 Adapter
Hailo-8 M.2 AI Accelerator Module, Based On The 26TOPS Hailo-8 AI Processor, Supports Linux/Windows Systems, Suitable For Raspberry Pi 5
Equipped With 26TOPS Hailo-8 M.2 AI Accelerator Module
This AI kit is launched by Waveshare to provide a more cost-effective and high-performance AI solution for the Raspberry Pi 5, optional for PCIe To M.2 adapter, suitable for applications such as process control, safety, home automation and robotics, etc.
Hailo-8
the Hailo-8 AI M.2 module only
Hailo-8 Acce A
Hailo-8 M.2 module + PCIe TO M.2 adapter and accessories (can be directly accessed to Raspberry Pi 5)
AI PERFORMANCE | 26 TOPS |
---|---|
FORM FACTOR | M.2 Key M |
POWER SUPPLY | 3.3V ± 5% |
POWER CONSUMPTION | 2.5W (Typ.) 8.65W (Max.) |
INTERFACE | PCIe Gen3, 4-lane |
CERTIFICATE | CE, FCC Class A |
STORAGE TEMPERATURE | -40 ~ 85°C |
OPERATING TEMPERATURE | -40 ~ 85°C |
OPERATING HUMIDITY | 5% ~ 90%RH (no frosting) |
DIMENSIONS | 22×80mm with breakable extensions to 22×42mm and 22×60mm |
The Hailo-8 M.2 module is an AI accelerator module for AI applications, based on the 26 tera-operations per second (TOPS) Hailo-8 AI processor with high power efficiency. The M.2 AI accelerator features a full PCIe Gen-3.0 4-lane interface, delivering unprecedented AI performance for edge devices.
The M.2 module can be plugged into an existing edge device with M.2 socket to provide low-power deep neural network inferencing. Leveraging Hailo's comprehensive Dataflow Compiler and its support for standard AI frameworks, customers can easily port their Neural Network models to the Hailo-8 and introduce high-performance AI products to the market quickly.
NN MODEL | INPUT RESOLUTION | MAP | HAILO-8L FPS (BATCH8) |
---|---|---|---|
yolov4_tiny | yolov4_tiny | 18.98 | 610 |
yolov6n | yolov6n | 34.3 | 345 |
yolov7 | yolov7 | 49.8 | 45 |
yolox_s_wide | yolox_s_wide | 42.4 | 75 |
yolov3 | yolov3 | 38 | 26 |
yolov8n | yolov8n | 37.23 | 270 |
yolov8s | yolov8s | 44.75 | 128 |
yolov8m | yolov8m | 50.08 | 55 |
TYPE | NN MODEL | INPUT RESOLUTION | FPS | POWER(W) | FPS/W |
---|---|---|---|---|---|
CLASSIFICATION | ResNet-50 v1 | 224x224 | 1332 | 3.45 | 386 |
MobileNet_v2_1.0 | 224x224 | 2444 | 2.152 | 1135 | |
EfficientNet_M | 240x240 | 889 | 3.5 | 254 | |
OBJECT DETECTION | SSD_MobileNet_v1 | 300x300 | 1055 | 2.2 | 479 |
YOLOv5m | 640x640 | 218 | 4.6 | 47.3 | |
SEGMENTATION | stdc1 | 1024x1920 | 54 | 2.9 | 18.6 |
MULTI STREAM OBJECT DETECTION (8 STREAMS) | YOLOv3 | 608x608 | 69 | 4.9 | 14 |
Based On 16PIN PCIe Interface Of Raspberry Pi 5
Standard Raspberry Pi 40PIN Header, Comes With 2*20 Pin Header For Stacking With Other HATs. Compact Size, More Space-Saving, Supports Installing Cooling Fan
Can Be Used Together With The Pi5 Active Cooler B To Achieve Better Heat Dissipation Effect For The Pi5 And AI Accelerator Module, Keeping It Cool Even Under Heavy Processing And Maximizing The Module Performance
Real-Time Monitoring Of Device Power Status For More Stable Operation
* for reference only, the cooling fan is NOT included.
Balenie Obsahuje / Package Content