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AI Ready Solution

Rugged Laptop, Panel PC, and Edge Box PC

AI Ready Solution

Industry Challenges

In today's rapidly evolving technological landscape, the demand for AI-ready computing solutions is at an all-time high. Businesses across various industries are increasingly leveraging artificial intelligence to drive innovation, streamline operations, and gain competitive advantages. However, implementing AI effectively comes with its own set of challenges.

One of the primary challenges faced by industries adopting AI-ready computing is the complexity of integrating AI algorithms into existing systems. This often requires significant resources in terms of expertise, time, and infrastructure. Additionally, ensuring the compatibility and scalability of AI solutions across different platforms and devices can be daunting.

Moreover, data privacy and security concerns pose significant hurdles in the deployment of AI-ready computing solutions. With the abundance of sensitive data involved in AI applications, businesses must prioritize robust security measures to safeguard against potential breaches and unauthorized access.

Furthermore, the rapid pace of technological advancements means that businesses must constantly adapt and update their AI systems to remain competitive. This necessitates ongoing investments in research and development, as well as continuous training and upskilling of personnel.

Despite these challenges, the potential benefits of AI-ready computing solutions are undeniable. From enhancing decision-making processes to optimizing resource allocation and improving customer experiences, AI has the power to revolutionize industries across the board.

To address these challenges effectively, companies must partner with trusted technology providers like Winmate, who specialize in delivering cutting-edge AI-ready computing solutions. By leveraging innovative technologies and industry expertise, Winmate empowers businesses to overcome obstacles and unlock the full potential of artificial intelligence. While implementing AI-ready computing solutions may present challenges, the rewards far outweigh the risks. With the right strategies and partnerships in place, businesses can harness the transformative power of AI to drive growth, innovation, and success in today's dynamic marketplace.

AI-ready CPU
AI-ready GPU
AI-ready NVIDIA
AI-ready Elite Partner
AI-ready Embedded

Trusted Technology Providers:

Intel® Alder Lake Processor

Intel® Alder Lake Processor

  • Enhanced graphics performance for immersive, engaging video
  • Fast AI with hardware acceleration
  • Real-Time Capabilities
  • Provides high performance and low power consumption
Intel® Alder Lake processor has powerful computing performance
NVIDIA Processor

NVIDIA Processor

  • GPUs are increasingly utilized in AI and machine learning, where their parallel processing power significantly accelerates computational workloads, improving training and inference speeds.
  • Represent a significant advancement in AI-assisted defect inspection and various deep learning tasks.
  • Enhancing visual experiences in image projection, while simultaneously optimizing performance for AI machine and deep learning applications.
Powered with Hailo-8 AI Processor

Powered with Hailo-8 AI Processor

  • Winmate’s Edge AI Box PC integrated with the Hailo-8 AI processor represents the cutting edge of Edge AI Computing solutions.
  • Enable real-time data processing at the edge of the network, transforming data handling across various applications.
  • Increased efficiency, reduced latency, and improved decision-making.

Accelerator Card

Hailo-8

Peak Performance(INT8)

26 TOPS

Interface

PCIe Gen3, 2-lanes (x2)

Form Factor

M.2 Key A+E

Thermal design power

6.93W

Storage Temperature

-40°C~85°C

Operating Temperature

-40°C~85°C

Support

TensorFlow
TensorFlow Lite
Keras
PyTorch
ONNX

Overview

GPU Accelerated Computing

Modern central processing units (CPUs) typically feature 4, 8, or 16 cores, whereas graphics processing units (GPUs) can boast hundreds or even thousands of smaller cores. These specialized computing cores excel in task parallelism and are primarily designed for graphics processing, making them ideally suited for parallel computing tasks. Leveraging GPUs for general-purpose computing tasks, known as general-purpose computing on graphics processing units (GPGPU), enables the acceleration of compute-intensive applications by distributing computing workloads across numerous cores.

GPU Accelerated Computing

Image Processing and Analysis Applications

Image processing and analysis find applications across various domains, including:

  1. Air Traffic Control: Utilized for monitoring and managing air traffic, ensuring safety and efficiency in airspace operations.
  2. Electronic Chart Display and Information System (ECDIS): Employed in maritime navigation for displaying electronic navigational charts and crucial vessel information.
  3. Video Walls: Utilized for displaying large-scale visual content across multiple screens, often in control rooms, entertainment venues, or advertising spaces.
  4. Digital Signage: Used for dynamic and interactive advertising and information display in public spaces, retail environments, and transportation hubs.
  5. Gaming: Integral for rendering realistic graphics, enhancing gameplay experiences, and optimizing performance in video game development and gaming platforms.
  6. Healthcare: Applied for medical imaging, diagnosis, and treatment planning, aiding in the interpretation of medical images such as X-rays, MRIs, and CT scans.

These applications rely on image processing and analysis techniques to extract meaningful information, enhance visual quality, and facilitate decision-making processes in various industries.

Air Traffic Control
Electronic Chart Display and Information System (ECDIS)
Video Walls
Digital Signage
Gaming
Healthcare

Compute Acceleration in High-Performance Applications

Compute acceleration plays a vital role in various high-performance applications, including:

  1. Radar/Sonar Systems: Enhancing the processing capabilities of radar and sonar systems, enabling real-time analysis of data for detecting, tracking, and identifying objects in the air or underwater.
  2. Ultrasound Imaging: Optimizing the computational power for ultrasound imaging systems, facilitating the rapid processing of ultrasound signals to generate high-quality images for medical diagnosis and research purposes.

In both scenarios, compute acceleration enhances the efficiency and speed of data processing, enabling faster and more accurate analysis in critical applications such as military defense, maritime navigation, and medical imaging.

Radar/Sonar Systems
Ultrasound Imaging

AI Engines for System Training and Inferencing

AI engines are instrumental in facilitating system training and inferencing in various sectors, including:

  1. Smart Manufacturing: AI engines are employed to train systems for predictive maintenance, quality control, production optimization, and supply chain management in smart manufacturing environments. These engines analyze large datasets to identify patterns, anomalies, and opportunities for process improvement.
  2. Aerospace and Defense: AI engines play a crucial role in aerospace and defense applications by training systems for tasks such as autonomous navigation, target recognition, threat detection, and mission planning. In addition, they enable real-time inferencing on board aircraft, unmanned aerial vehicles (UAVs), and other defense platforms for decision-making in dynamic and mission-critical environments.

By leveraging AI engines for system training and inferencing, industries such as smart manufacturing, aerospace, and defense can enhance operational efficiency, safety, and competitiveness through advanced data-driven capabilities.

Smart Manufacturing
Aerospace and Defense

User Scenario

GPU Acceleration in Vertical Applications

Graphics processing units (GPUs) play a pivotal role in enhancing the performance of various workloads, spanning image processing and analysis, compute acceleration, and artificial intelligence (AI). By integrating GPUs into edge systems, enhanced responsiveness and superior performance are achieved in real-world scenarios. Applications benefiting from GPU-enabled edge systems include medical imaging, defect inspection in manufacturing, traffic flow analysis in smart cities, and numerous other embedded segments. Additionally, GPU acceleration significantly enhances gaming experiences, particularly in the context of 4K displays.

User Scenario

Core Capabilities / Advantages

Optional GPU Graphic Cards

Winmate's Rugged Laptop L156 Series offers optional graphic cards from industry leaders NVIDIA and Intel, such as the NVIDIA T1000, A2000, and Intel A370M. These cards excel in driving advanced laptop workstations for various sectors. They ensure optimal connectivity and superior performance, catering to diverse professional needs.

Winmate’s GPU Solutions

Winmate is a global provider of leading edge computing solutions and an NVIDIA® Quadro® Embedded Partner. To enable edge systems to tap into the power that can be provided by GPU computing, Winmate offers a comprehensive portfolio of optimized heterogeneous computing solutions including embedded MXM GPU modules and PCI Express graphics cards based on NVIDIA Quadro GPUs, GPU computing platforms and other embedded form factors that can accelerate edge computing and AI workloads to satisfy a wide range of embedded requirements based on performance, long life cycle, power consumption, and form factor.

Product Type

Product Series

Graphic

Edge AI Mobility

L156 Series Rugged Laptop Intel A370M
Nvidia T1000
Nvidia A2000
M156 Series Rugged Tablet

Edge AI Panel PCs

Edge AI Panel PC T1000
A2000
A4000

Edge AI Computing

Edge AI Computing T1000
NRTX A2000
NRTX A4000
NRTX A5000
NRTX A6000
2U Rack Server

Frequently Asked Questions about GPUs

  1. What is a GPU?

    A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device.

  2. How does a GPU differ from a CPU?

    A CPU (Central Processing Unit) is a general-purpose processor responsible for executing instructions and performing tasks in a computer system. In contrast, a GPU is specifically optimized for rendering graphics and parallel processing tasks, featuring numerous cores designed to handle multiple tasks simultaneously.

  3. What are the primary uses of GPUs?

    In the modern world, the AI revolution has opened up exciting opportunities for embedded graphics in various applications. Here are some areas where embedded graphics play a crucial role:

    • Industrial Automation: Embedded graphics enhance human-machine interfaces (HMIs) in factories and manufacturing plants. They provide real-time visual feedback, control panels, and data visualization for operators. Graphics processors (GPUs) enable faster rendering of complex visuals, improving efficiency and safety.
    • Autonomous Vehicles: Graphics are essential for autonomous vehicles, including dashboards, infotainment systems, and navigation displays. Real-time rendering of maps, sensor data, and augmented reality overlays relies on powerful GPUs.
    • Video Analytics: Surveillance cameras, smart cities, and retail analytics benefit from embedded graphics. GPUs accelerate video processing, object detection, and tracking. Real-time analytics can identify anomalies, monitor traffic, and enhance security.
    • Healthcare: Medical devices, patient monitors, and diagnostic equipment use embedded graphics. High-resolution displays, 3D imaging, and virtual simulations aid medical professionals in diagnosis, surgery planning, and training.
    • Gaming and Entertainment: GPUs are at the heart of gaming consoles, arcade machines, and digital signage. Realistic graphics, smooth animations, and immersive experiences rely on powerful embedded graphics solutions.
    • Edge AI: Graphics processing units accelerate AI workloads at the edge. Edge devices, such as cameras, drones, and robots, benefit from embedded GPUs for image recognition, natural language processing, and predictive maintenance.
    • Digital Signage: Dynamic displays in retail, transportation, and public spaces use embedded graphics. GPUs enable high-definition content, interactive touchscreens, and personalized advertising.
    • Smart Home Devices: Graphics enhance user interfaces in smart home devices like thermostats, doorbells, and appliances. Touchscreens, voice assistants, and visual feedback rely on embedded graphics.
    • Education and Training: Interactive e-learning platforms, simulators, and virtual labs use embedded graphics. GPUs enable realistic simulations, 3D models, and engaging educational content.
    • Aviation and Aerospace: Cockpit displays, flight simulators, and satellite communication systems benefit from embedded graphics. GPUs ensure accurate visualization, navigation, and situational awareness.
  4. Can GPUs be used for tasks other than graphics processing?

    Yes, modern GPUs are highly versatile and can be utilized for a wide range of parallel processing tasks beyond graphics rendering. These tasks include scientific computing, data analysis, machine learning, deep learning, cryptography, and more.

  5. What is the difference between integrated and dedicated GPUs?

    Integrated GPUs are built into the same chip as the CPU and share system memory, whereas dedicated GPUs are separate processing units with their own dedicated memory. Dedicated GPUs typically offer higher performance and are preferred for demanding graphics and compute-intensive tasks.

  6. How do I choose the right GPU for my needs?

    When selecting a GPU, consider factors such as your budget, the specific tasks you intend to perform (e.g., gaming, content creation, machine learning), compatibility with your system (including power supply and motherboard), and any specific features or software requirements you may have.

Get a Free AI Ready Solution Consultation

Whatever your goals, Winmate is here to help. If your focus is increasing the speed of service, improving your bottom line, expanding through new channels, adding locations, exploring franchising, or maximizing customer loyalty. Winmate AI ready solutions are enabling users to streamline operations, enhance productivity, and make data-driven decisions in real-time. Winmate Edge AI Computing is instrumental in realizing the promises of Industry 4.0 and the Industrial Internet of Things (IIoT). Please speak to one of our experts to explore the hardware that would best help you achieve your goals.