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ADLINK DLAP Series Edge AI Acceleration Platform Selection and Deployment Practical Guide

F: | Au:FANS | DA:2026-07-10 | 584 Br: | 🔊 点击朗读正文 ❚❚ ▶ | Share:

DLAP-8000: Introducing Intel Xeon E-2278GE (8-core 16 thread, 80W), paired with C246 chipset, supports ECC memory, and meets data integrity requirements for critical tasks.

2. Selection Guide for Graphics Acceleration Module

MxM module (3000/3100/3200): adopting Type A/B standard, with a maximum power consumption of 120W. ADLINK offers four pre installed options - P1000 (entry-level), P2000 (mid-range), T1000 (new generation), RTX 3000 (high-end). The RTX 3000 is based on the Turing architecture and features Tensor Core, which can accelerate INT8 inference. If you need flexible selection, you can also order the CF-PL2 version without MXM and install it yourself.

PCIe PEG card (4000/8000): The Quadro series supports virtualization (vGPU) and ECC (RTX series), making it suitable for high-precision scientific computing. The RTX 6000/8000 has 24GB/48GB of video memory and can load extremely large models. Attention should be paid to the cooling and power requirements of different graphics cards. The 4000 series with a 300W power supply can support up to RTX 4000 (160W), while 500W can cover RTX 8000 (295W). The 8000 series dual card configuration must use AC power supply (above 500W).

3. Comparison of storage and expansion capabilities

Model 2.5-inch SATA M.2 slot Other

DLAP-3000 2 (external) 1 x E key (Wi Fi/BT)+1 x B key (SATA)-

DLAP-3100/3200 2 (SATA power supply) Same as above+1 x M key (PCIe x4/SATA) 3200 Extra 2 x PCIe x4 FHFL

DLAP-4000 2 (internal) 1 x M key (SATA) 1 x Mini PCIe

DLAP-8000 4 hot swappable 1 x M.2 2280 (B+M key) 1 x Mini PCIe+2 x USIM+CFast

The Jetson series relies on SD cards or mSATA/M.2 with M.2 B key and supports Mini PCIe

For NVR scenarios that require a large amount of local video storage (such as DLAP-301-JNX), equipped with 8 PoE ports (15W per port) and 2.5-inch SATA hard drives, it can simultaneously complete camera power supply, video recording, and real-time inference.


Industrial grade reliability and environmental adaptability

All DLAP products are designed for embedded environments, with key indicators including:

Working temperature: Most Jetson models support -20 ℃~70 ℃, DLAP-3000/3100/3200 ranges from 0 ℃~50 ℃, DLAP-4000 may drop to 0 ℃~40 ℃ depending on the graphics card configuration (high-power card), and DLAP-8000 is also adjusted according to the graphics card.

Anti vibration: DLAP-4000/8000 has undergone 1Grms (5-500Hz) random vibration testing (with SSD and PEG card), meeting the requirements of on-board and rail transit.

Safety certification: All have passed UL/cUL, CB, and EN55032/35 electromagnetic compatibility standards, FCC Class B。

Power supply design: 3000/3100/3200 use Molex 12V DC in with 240W adapter; 4000 built-in Flex ATX AC power supply; 8000 optional AC or DC (24V) input, supporting on-board DC power supply.

Protection level: Jetson small models are IP40, suitable for indoor cleaning or environments with slight dust. If higher protection is required, an external chassis is needed.


Software Ecology and Development Support

ADLINK provides mainstream operating system support:

Windows 10 IoT Enterprise SAC 64-bit(3000/3100/3200/4000/8000)

Ubuntu 18.04 LTS 64-bit(3000/3100/3200/8000),Ubuntu 16.04(4000)

The Jetson series defaults to using NVIDIA JetPack SDK (based on Ubuntu), which supports acceleration libraries such as CUDA, cuDNN, TensorRT, etc.

Of particular note is that ADLINK also provides deep learning consulting and performance analysis services. Through internal profiling tools, it models inference throughput (FPS), energy efficiency ratio (FPS/W), and cost-effectiveness (FPS/$) in a large accelerator database based on user specified neural networks (such as AlexNet, MobileNet, ResNet), batch size, and accuracy requirements, helping engineers quantitatively evaluate before selection and avoid "over design" or "under design". This service is of great practical value for teams lacking hardware comparison experience.

Typical deployment scenarios and model recommendations

1. Unmanned retail/fast food automatic settlement

Requirement: Identify multiple types of products (such as plates, sushi plates) and complete the detection and payment interaction within 1.5 seconds.

Recommendation: DLAP-211-JNX or DLAP-301-JNX (Jetson Xavier NX), with its 384 core Volta GPU and 48 Tensor Cores, can efficiently run lightweight object detection networks such as YOLOv4 tiny. If 8 cameras need to be processed simultaneously, DLAP-301-JNX integrates PoE and NVR functions, which is the most suitable match.

2. Mobile medical imaging (C-arm)

Requirement: Real time processing of X-ray images for enhancement and lesion labeling, requiring portability and low latency.

Recommendation: DLAP-201-JT2 (Jetson TX2) or DLAP-401 Xavier (AGX Xavier). TX2 has low power consumption and is suitable for battery power supply; AGX Xavier offers higher computing power (32TOPS INT8), suitable for more complex reconstruction algorithms. Both are wide temperature and fanless, suitable for mobile carts.

3. Autonomous driving/snow plow obstacle avoidance

Requirement: Identify living objects or obstacles on the road, issue timely warnings, and require high reliability and wide temperature range.

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