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- Processor Support: Compatible with 8th and 9th Generation Intel® Core™ i7, i5, and i3 CPUs (LGA1151 socket), offering up to 8 cores and 12 threads depending on model.
- GPU Acceleration: Supports NVIDIA® Quadro® PEG cards, including P2200, P4000, P5000, RTX 4000, RTX 5000, RTX 6000, and RTX 8000, enabling advanced AI inference and deep learning workloads.
- Memory Capacity: Dual SO-DIMM slots supporting up to 32GB DDR4 non-ECC memory at 2666/2400 MHz (dependent on CPU).
- Display Outputs: Integrated 1x DVI, 1x HDMI, and 1x DisplayPort from CPU graphics, with additional outputs available from installed PEG cards.
- Expansion Options: 1x Mini PCIe slot for Wi-Fi/Bluetooth or LTE modules and 1x M.2 M-key slot supporting 2280 SATA SSD modules.
- Storage Flexibility: Two internal 2.5" SATA 6Gb/s drive bays plus one SATA 6Gb/s signal via M.2 M-key slot.
- Power Supply Options: Available with 300W, 400W, or 500W Flex ATX power supplies to accommodate various GPU configurations.
- Software Compatibility: Supports Windows 10 IoT Enterprise CBB 64-bit and Ubuntu 16.04 LTS operating systems.
- Industrial Reliability: Operating temperature range from 0°C to 50°C (model-dependent), with compliance to EMC and safety standards (EN55032/EN55035, UL/cUL, CB, CCC).
- Compact Design: Mini-ITX chassis with dimensions of 220 x 300 x 150 mm (W x D x H), optimized for embedded and edge deployments.
- GPU Acceleration: Supports NVIDIA® Quadro® PEG cards, including P2200, P4000, P5000, RTX 4000, RTX 5000, RTX 6000, and RTX 8000, enabling advanced AI inference and deep learning workloads.
- Memory Capacity: Dual SO-DIMM slots supporting up to 32GB DDR4 non-ECC memory at 2666/2400 MHz (dependent on CPU).
- Display Outputs: Integrated 1x DVI, 1x HDMI, and 1x DisplayPort from CPU graphics, with additional outputs available from installed PEG cards.
- Expansion Options: 1x Mini PCIe slot for Wi-Fi/Bluetooth or LTE modules and 1x M.2 M-key slot supporting 2280 SATA SSD modules.
- Storage Flexibility: Two internal 2.5" SATA 6Gb/s drive bays plus one SATA 6Gb/s signal via M.2 M-key slot.
- Power Supply Options: Available with 300W, 400W, or 500W Flex ATX power supplies to accommodate various GPU configurations.
- Software Compatibility: Supports Windows 10 IoT Enterprise CBB 64-bit and Ubuntu 16.04 LTS operating systems.
- Industrial Reliability: Operating temperature range from 0°C to 50°C (model-dependent), with compliance to EMC and safety standards (EN55032/EN55035, UL/cUL, CB, CCC).
- Compact Design: Mini-ITX chassis with dimensions of 220 x 300 x 150 mm (W x D x H), optimized for embedded and edge deployments.
1. Product Overview
Product Name: DLAP-4000
Model Series: DLAP-4000 Series
Article Number: DLAP-4000
Manufacturer: ADLINK Technology, Inc.
Product Type: Mini-ITX Embedded Computer System for Deep Learning Applications
The ADLINK DLAP-4000 Series is a high-performance embedded computing platform designed for AI inference, deep learning, and edge computing workloads. Built on the Mini-ITX form factor, it integrates 8th and 9th Generation Intel® Core™ i7/i5/i3 processors in an LGA1151 socket and supports NVIDIA® Quadro® professional GPU cards via a full-height, full-length (FHFL) dual-width PEG slot. The system is engineered for industrial-grade reliability, compact deployment, and scalable GPU acceleration, making it suitable for machine vision, robotics, autonomous systems, and intelligent edge analytics.
2. Key Features
- Processor Support: Compatible with 8th and 9th Generation Intel® Core™ i7, i5, and i3 CPUs (LGA1151 socket), offering up to 8 cores and 12 threads depending on model.
- GPU Acceleration: Supports NVIDIA® Quadro® PEG cards, including P2200, P4000, P5000, RTX 4000, RTX 5000, RTX 6000, and RTX 8000, enabling advanced AI inference and deep learning workloads.
- Memory Capacity: Dual SO-DIMM slots supporting up to 32GB DDR4 non-ECC memory at 2666/2400 MHz (dependent on CPU).
- Display Outputs: Integrated 1x DVI, 1x HDMI, and 1x DisplayPort from CPU graphics, with additional outputs available from installed PEG cards.
- Expansion Options: 1x Mini PCIe slot for Wi-Fi/Bluetooth or LTE modules and 1x M.2 M-key slot supporting 2280 SATA SSD modules.
- Storage Flexibility: Two internal 2.5" SATA 6Gb/s drive bays plus one SATA 6Gb/s signal via M.2 M-key slot.
- Power Supply Options: Available with 300W, 400W, or 500W Flex ATX power supplies to accommodate various GPU configurations.
- Software Compatibility: Supports Windows 10 IoT Enterprise CBB 64-bit and Ubuntu 16.04 LTS operating systems.
- Industrial Reliability: Operating temperature range from 0°C to 50°C (model-dependent), with compliance to EMC and safety standards (EN55032/EN55035, UL/cUL, CB, CCC).
- Compact Design: Mini-ITX chassis with dimensions of 220 x 300 x 150 mm (W x D x H), optimized for embedded and edge deployments.
3. Technical Specifications
Processor Options:
- Intel® Core™ i7-9700E, 2.6GHz, 12M Cache, 65W TDP (8C/8T)
- Intel® Core™ i5-9500E, 3.0GHz, 9M Cache, 65W TDP (6C/6T)
- Intel® Core™ i3-9100E, 3.1GHz, 6M Cache, 65W TDP (4C/4T)
- Intel® Core™ i7-9700TE, 1.8GHz, 12M Cache, 35W TDP (8C/8T)
- Intel® Core™ i5-9500TE, 2.2GHz, 9M Cache, 35W TDP (6C/6T)
- Intel® Core™ i3-9100TE, 2.2GHz, 6M Cache, 35W TDP (4C/4T)
- Intel® Core™ i7-8700, 3.2GHz, 12M Cache, 65W TDP (6C/12T)
- Intel® Core™ i5-8500, 3.0GHz, 9M Cache, 65W TDP (6C/6T)
- Intel® Core™ i3-8100, 3.6GHz, 6M Cache, 65W TDP (4C/4T)
- Intel® Core™ i7-8700T, 2.4GHz, 12M Cache, 35W TDP (6C/12T)
- Intel® Core™ i5-8500T, 2.1GHz, 9M Cache, 35W TDP (6C/6T)
- Intel® Core™ i3-8100T, 3.1GHz, 6M Cache, 35W TDP (4C/4T)
Chipset: Intel® H310 Chipset
Memory:
- 2x SO-DIMM DDR4 2666/2400 MHz
- Up to 32GB non-ECC system memory (dependent on CPU)
Graphics (PEG Card Options):
- NVIDIA® Quadro® P2200: 75W, 1280 CUDA® cores, 5GB GDDR5
- NVIDIA® Quadro® P4000: 105W, 1792 CUDA® cores, 8GB GDDR5
- NVIDIA® Quadro® P5000: 180W, 2560 CUDA® cores, 16GB GDDR5
- NVIDIA® Quadro® RTX 4000: 160W, 2304 CUDA® cores, 8GB GDDR6
- NVIDIA® Quadro® RTX 5000: 265W, 3072 CUDA® cores, 16GB GDDR6
- NVIDIA® Quadro® RTX 6000: 295W, 4608 CUDA® cores, 24GB GDDR6
- NVIDIA® Quadro® RTX 8000: 295W, 4608 CUDA® cores, 48GB GDDR6
Display Interfaces:
- 1x DVI
- 1x HDMI
- 1x DisplayPort (from CPU)
- Additional outputs from PEG card
Networking:
- 2x Gigabit Ethernet (Realtek RTL8111G)
Serial Communication:
- 1x RS-232/422/485
- 4x RS-232
USB Interfaces:
- 4x USB 3.1 Gen1 ports
- 2x USB 2.0 ports
Audio:
- Mic-in, Line-out, Line-in
Expansion Slots:
- 1x Mini PCIe slot (for Wi-Fi/Bluetooth or LTE module)
- 1x M.2 M-key slot (supports 2280 SATA SSD module)
Storage:
- 2x 2.5" SATA 6Gb/s internal drive bays
- 1x SATA 6Gb/s signal via M.2 M-key slot
Trusted Platform Module:
- TPM 2.0 (optional)
Mechanical Dimensions:
- 220 mm (W) x 300 mm (D) x 150 mm (H)
Power Supply:
- AC Input: 100–240 VAC
- Output Options: 300W, 400W, or 500W Flex ATX PSU
Environmental Conditions:
- Operating Temperature: 0°C to 50°C (varies by GPU configuration)
- Storage Temperature: -20°C to 60°C
- Humidity: 5% to 90%, non-condensing
Certifications:
- EMC: EN55032 / EN55035
- Safety: UL/cUL, CB, CCC
4. Functionality
The DLAP-4000 functions as a compact, high-performance embedded computing platform optimized for AI inference and deep learning at the edge. It integrates Intel® Core™ processors with NVIDIA® Quadro® GPUs to deliver accelerated parallel processing for machine learning, computer vision, and data analytics tasks.
Use Cases and Applications:
- Industrial AI and Machine Vision: Real-time image recognition, defect detection, and quality inspection.
- Autonomous Systems: Robotics control, navigation, and sensor fusion.
- Smart Cities and Surveillance: Video analytics, object tracking, and event detection.
- Healthcare Imaging: AI-assisted diagnostics and medical image processing.
- Edge Computing: Localized data processing for latency-sensitive applications.
Compatibility:
- Compatible with Windows 10 IoT Enterprise CBB 64-bit and Ubuntu 16.04 LTS.
- Supports standard Mini-ITX mounting and peripheral interfaces for integration into industrial enclosures or AI edge servers.
5. Components & Accessories
Included Components:
- DLAP-4000 main system unit
- Flex ATX power supply (300W/400W/500W depending on configuration)
- CPU and GPU cooling assemblies
- Standard I/O shield and mounting hardware
Optional Accessories:
- 3.5" SATA HDD, 2.5" SATA SSD/HDD, or M.2 2280 SATA SSD
- Wireless module kits (Wi-Fi/Bluetooth or 4G LTE) with antenna
- TPM 2.0 security module
- Additional GPU options (P2200–RTX 8000 series)
Connectors and Interfaces:
- Front and rear I/O ports for USB, Ethernet, audio, and display
- Internal connectors for SATA drives and expansion modules
6. Installation & Setup
Requirements:
- AC power input (100–240 VAC)
- Compatible operating system (Windows 10 IoT Enterprise or Ubuntu 16.04 LTS)
- Adequate ventilation for GPU cooling
Mounting Options:
- Standard Mini-ITX chassis mounting
- Rack or wall-mount integration for industrial environments
Configuration Steps:
1. Install CPU and memory modules (if not pre-installed).
2. Mount the selected NVIDIA® Quadro® PEG card in the FHFL dual-width slot.
3. Connect storage devices (SATA or M.2).
4. Attach optional wireless modules via Mini PCIe or M.2 slots.
5. Connect display, network, and peripheral cables.
6. Power on and install the desired operating system and drivers.
7. Performance & Capabilities
The DLAP-4000 delivers scalable performance tailored to AI and deep learning workloads. With Intel® Core™ processors offering up to 8 cores and 12 threads, combined with NVIDIA® Quadro® GPUs featuring up to 4608 CUDA® cores and 48GB of GDDR6 memory, the system supports high-throughput parallel computation.
Performance Highlights:
- CPU Performance: Up to 8 cores and 12 threads, supporting DDR4 2666 MHz memory bandwidth.
- GPU Acceleration: Up to 295W GPU power draw, enabling real-time inference and training for complex neural networks.
- Storage Throughput: SATA 6Gb/s interface for high-speed SSDs and HDDs.
- Networking: Dual Gigabit Ethernet ports for redundant or segmented network configurations.
- I/O Flexibility: Multiple USB and serial ports for peripheral integration and device communication.
Efficiency and Limitations:
- Optimized for inference rather than large-scale training due to single-GPU configuration.
- Operating temperature limited to 40–50°C depending on GPU model; adequate cooling is required for high-power GPUs.
8. Standards & Compliance
Regulatory Compliance:
- EMC: EN55032 (emission) and EN55035 (immunity)
- Safety: UL/cUL, CB, CCC certifications ensure adherence to international safety standards.
Industry Standards:
- Mini-ITX form factor compliance
- PCI Express PEG slot for GPU integration
- SATA 6Gb/s and M.2 2280 interface standards
- TPM 2.0 security module compatibility
Environmental Standards:
- Designed for industrial environments with wide temperature and humidity tolerance.
- Non-condensing humidity operation from 5% to 90%.
9. Additional Information
Warranty:
- Standard manufacturer warranty provided by ADLINK Technology, Inc. (terms vary by region).
Support:
- Technical documentation, driver downloads, and software updates available at [www.adlinktech.com](https://www.adlinktech.com).
- Customer support includes configuration assistance, firmware updates, and RMA services.
Maintenance:
- Regular cleaning of air vents and fans recommended for optimal thermal performance.
- Firmware and BIOS updates available through ADLINK’s support portal.
Software Updates:
- Compatible with long-term supported OS versions (Windows 10 IoT Enterprise CBB, Ubuntu 16.04 LTS).
- GPU driver updates available from NVIDIA for Quadro® series cards.
Revision History:
- Document updated December 2, 2019.
- Specifications subject to change without prior notice.
Summary
The ADLINK DLAP-4000 Series represents a robust, scalable embedded computing solution purpose-built for AI inference and deep learning at the edge. Combining Intel® 8th/9th Gen Core™ processors with NVIDIA® Quadro® GPUs, it delivers exceptional computational density in a compact Mini-ITX form factor. With flexible I/O, multiple storage options, and industrial-grade reliability, the DLAP-4000 is ideal for machine vision, robotics, and intelligent automation applications requiring high-performance GPU acceleration and long-term operational stability.
Product Name: DLAP-4000
Model Series: DLAP-4000 Series
Article Number: DLAP-4000
Manufacturer: ADLINK Technology, Inc.
Product Type: Mini-ITX Embedded Computer System for Deep Learning Applications
The ADLINK DLAP-4000 Series is a high-performance embedded computing platform designed for AI inference, deep learning, and edge computing workloads. Built on the Mini-ITX form factor, it integrates 8th and 9th Generation Intel® Core™ i7/i5/i3 processors in an LGA1151 socket and supports NVIDIA® Quadro® professional GPU cards via a full-height, full-length (FHFL) dual-width PEG slot. The system is engineered for industrial-grade reliability, compact deployment, and scalable GPU acceleration, making it suitable for machine vision, robotics, autonomous systems, and intelligent edge analytics.
2. Key Features
- Processor Support: Compatible with 8th and 9th Generation Intel® Core™ i7, i5, and i3 CPUs (LGA1151 socket), offering up to 8 cores and 12 threads depending on model.
- GPU Acceleration: Supports NVIDIA® Quadro® PEG cards, including P2200, P4000, P5000, RTX 4000, RTX 5000, RTX 6000, and RTX 8000, enabling advanced AI inference and deep learning workloads.
- Memory Capacity: Dual SO-DIMM slots supporting up to 32GB DDR4 non-ECC memory at 2666/2400 MHz (dependent on CPU).
- Display Outputs: Integrated 1x DVI, 1x HDMI, and 1x DisplayPort from CPU graphics, with additional outputs available from installed PEG cards.
- Expansion Options: 1x Mini PCIe slot for Wi-Fi/Bluetooth or LTE modules and 1x M.2 M-key slot supporting 2280 SATA SSD modules.
- Storage Flexibility: Two internal 2.5" SATA 6Gb/s drive bays plus one SATA 6Gb/s signal via M.2 M-key slot.
- Power Supply Options: Available with 300W, 400W, or 500W Flex ATX power supplies to accommodate various GPU configurations.
- Software Compatibility: Supports Windows 10 IoT Enterprise CBB 64-bit and Ubuntu 16.04 LTS operating systems.
- Industrial Reliability: Operating temperature range from 0°C to 50°C (model-dependent), with compliance to EMC and safety standards (EN55032/EN55035, UL/cUL, CB, CCC).
- Compact Design: Mini-ITX chassis with dimensions of 220 x 300 x 150 mm (W x D x H), optimized for embedded and edge deployments.
3. Technical Specifications
Processor Options:
- Intel® Core™ i7-9700E, 2.6GHz, 12M Cache, 65W TDP (8C/8T)
- Intel® Core™ i5-9500E, 3.0GHz, 9M Cache, 65W TDP (6C/6T)
- Intel® Core™ i3-9100E, 3.1GHz, 6M Cache, 65W TDP (4C/4T)
- Intel® Core™ i7-9700TE, 1.8GHz, 12M Cache, 35W TDP (8C/8T)
- Intel® Core™ i5-9500TE, 2.2GHz, 9M Cache, 35W TDP (6C/6T)
- Intel® Core™ i3-9100TE, 2.2GHz, 6M Cache, 35W TDP (4C/4T)
- Intel® Core™ i7-8700, 3.2GHz, 12M Cache, 65W TDP (6C/12T)
- Intel® Core™ i5-8500, 3.0GHz, 9M Cache, 65W TDP (6C/6T)
- Intel® Core™ i3-8100, 3.6GHz, 6M Cache, 65W TDP (4C/4T)
- Intel® Core™ i7-8700T, 2.4GHz, 12M Cache, 35W TDP (6C/12T)
- Intel® Core™ i5-8500T, 2.1GHz, 9M Cache, 35W TDP (6C/6T)
- Intel® Core™ i3-8100T, 3.1GHz, 6M Cache, 35W TDP (4C/4T)
Chipset: Intel® H310 Chipset
Memory:
- 2x SO-DIMM DDR4 2666/2400 MHz
- Up to 32GB non-ECC system memory (dependent on CPU)
Graphics (PEG Card Options):
- NVIDIA® Quadro® P2200: 75W, 1280 CUDA® cores, 5GB GDDR5
- NVIDIA® Quadro® P4000: 105W, 1792 CUDA® cores, 8GB GDDR5
- NVIDIA® Quadro® P5000: 180W, 2560 CUDA® cores, 16GB GDDR5
- NVIDIA® Quadro® RTX 4000: 160W, 2304 CUDA® cores, 8GB GDDR6
- NVIDIA® Quadro® RTX 5000: 265W, 3072 CUDA® cores, 16GB GDDR6
- NVIDIA® Quadro® RTX 6000: 295W, 4608 CUDA® cores, 24GB GDDR6
- NVIDIA® Quadro® RTX 8000: 295W, 4608 CUDA® cores, 48GB GDDR6
Display Interfaces:
- 1x DVI
- 1x HDMI
- 1x DisplayPort (from CPU)
- Additional outputs from PEG card
Networking:
- 2x Gigabit Ethernet (Realtek RTL8111G)
Serial Communication:
- 1x RS-232/422/485
- 4x RS-232
USB Interfaces:
- 4x USB 3.1 Gen1 ports
- 2x USB 2.0 ports
Audio:
- Mic-in, Line-out, Line-in
Expansion Slots:
- 1x Mini PCIe slot (for Wi-Fi/Bluetooth or LTE module)
- 1x M.2 M-key slot (supports 2280 SATA SSD module)
Storage:
- 2x 2.5" SATA 6Gb/s internal drive bays
- 1x SATA 6Gb/s signal via M.2 M-key slot
Trusted Platform Module:
- TPM 2.0 (optional)
Mechanical Dimensions:
- 220 mm (W) x 300 mm (D) x 150 mm (H)
Power Supply:
- AC Input: 100–240 VAC
- Output Options: 300W, 400W, or 500W Flex ATX PSU
Environmental Conditions:
- Operating Temperature: 0°C to 50°C (varies by GPU configuration)
- Storage Temperature: -20°C to 60°C
- Humidity: 5% to 90%, non-condensing
Certifications:
- EMC: EN55032 / EN55035
- Safety: UL/cUL, CB, CCC
4. Functionality
The DLAP-4000 functions as a compact, high-performance embedded computing platform optimized for AI inference and deep learning at the edge. It integrates Intel® Core™ processors with NVIDIA® Quadro® GPUs to deliver accelerated parallel processing for machine learning, computer vision, and data analytics tasks.
Use Cases and Applications:
- Industrial AI and Machine Vision: Real-time image recognition, defect detection, and quality inspection.
- Autonomous Systems: Robotics control, navigation, and sensor fusion.
- Smart Cities and Surveillance: Video analytics, object tracking, and event detection.
- Healthcare Imaging: AI-assisted diagnostics and medical image processing.
- Edge Computing: Localized data processing for latency-sensitive applications.
Compatibility:
- Compatible with Windows 10 IoT Enterprise CBB 64-bit and Ubuntu 16.04 LTS.
- Supports standard Mini-ITX mounting and peripheral interfaces for integration into industrial enclosures or AI edge servers.
5. Components & Accessories
Included Components:
- DLAP-4000 main system unit
- Flex ATX power supply (300W/400W/500W depending on configuration)
- CPU and GPU cooling assemblies
- Standard I/O shield and mounting hardware
Optional Accessories:
- 3.5" SATA HDD, 2.5" SATA SSD/HDD, or M.2 2280 SATA SSD
- Wireless module kits (Wi-Fi/Bluetooth or 4G LTE) with antenna
- TPM 2.0 security module
- Additional GPU options (P2200–RTX 8000 series)
Connectors and Interfaces:
- Front and rear I/O ports for USB, Ethernet, audio, and display
- Internal connectors for SATA drives and expansion modules
6. Installation & Setup
Requirements:
- AC power input (100–240 VAC)
- Compatible operating system (Windows 10 IoT Enterprise or Ubuntu 16.04 LTS)
- Adequate ventilation for GPU cooling
Mounting Options:
- Standard Mini-ITX chassis mounting
- Rack or wall-mount integration for industrial environments
Configuration Steps:
1. Install CPU and memory modules (if not pre-installed).
2. Mount the selected NVIDIA® Quadro® PEG card in the FHFL dual-width slot.
3. Connect storage devices (SATA or M.2).
4. Attach optional wireless modules via Mini PCIe or M.2 slots.
5. Connect display, network, and peripheral cables.
6. Power on and install the desired operating system and drivers.
7. Performance & Capabilities
The DLAP-4000 delivers scalable performance tailored to AI and deep learning workloads. With Intel® Core™ processors offering up to 8 cores and 12 threads, combined with NVIDIA® Quadro® GPUs featuring up to 4608 CUDA® cores and 48GB of GDDR6 memory, the system supports high-throughput parallel computation.
Performance Highlights:
- CPU Performance: Up to 8 cores and 12 threads, supporting DDR4 2666 MHz memory bandwidth.
- GPU Acceleration: Up to 295W GPU power draw, enabling real-time inference and training for complex neural networks.
- Storage Throughput: SATA 6Gb/s interface for high-speed SSDs and HDDs.
- Networking: Dual Gigabit Ethernet ports for redundant or segmented network configurations.
- I/O Flexibility: Multiple USB and serial ports for peripheral integration and device communication.
Efficiency and Limitations:
- Optimized for inference rather than large-scale training due to single-GPU configuration.
- Operating temperature limited to 40–50°C depending on GPU model; adequate cooling is required for high-power GPUs.
8. Standards & Compliance
Regulatory Compliance:
- EMC: EN55032 (emission) and EN55035 (immunity)
- Safety: UL/cUL, CB, CCC certifications ensure adherence to international safety standards.
Industry Standards:
- Mini-ITX form factor compliance
- PCI Express PEG slot for GPU integration
- SATA 6Gb/s and M.2 2280 interface standards
- TPM 2.0 security module compatibility
Environmental Standards:
- Designed for industrial environments with wide temperature and humidity tolerance.
- Non-condensing humidity operation from 5% to 90%.
9. Additional Information
Warranty:
- Standard manufacturer warranty provided by ADLINK Technology, Inc. (terms vary by region).
Support:
- Technical documentation, driver downloads, and software updates available at [www.adlinktech.com](https://www.adlinktech.com).
- Customer support includes configuration assistance, firmware updates, and RMA services.
Maintenance:
- Regular cleaning of air vents and fans recommended for optimal thermal performance.
- Firmware and BIOS updates available through ADLINK’s support portal.
Software Updates:
- Compatible with long-term supported OS versions (Windows 10 IoT Enterprise CBB, Ubuntu 16.04 LTS).
- GPU driver updates available from NVIDIA for Quadro® series cards.
Revision History:
- Document updated December 2, 2019.
- Specifications subject to change without prior notice.
Summary
The ADLINK DLAP-4000 Series represents a robust, scalable embedded computing solution purpose-built for AI inference and deep learning at the edge. Combining Intel® 8th/9th Gen Core™ processors with NVIDIA® Quadro® GPUs, it delivers exceptional computational density in a compact Mini-ITX form factor. With flexible I/O, multiple storage options, and industrial-grade reliability, the DLAP-4000 is ideal for machine vision, robotics, and intelligent automation applications requiring high-performance GPU acceleration and long-term operational stability.
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DLAP-4000_Series-20191202-Preliminary.pdf
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