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Download Our Solution Guide For Embedded Computer and Industrial Touch Display Solutions

Premio 2020 Solution Guide
Edge Computers Needing Higher Performance

High Performance Edge Computing

By moving computing and data closer to the user, edge computing can provide significantly improved throughput, better performance, and real-time processing. The ability to analyze data closer to the source will minimize latency, reduce network traffic, and lower data management costs while improving privacy and security.
Read More on the benefits of Edge Computing ...

Faster response time More security Lower cost
  • network

    Reduce network traffic
    and cloud reliance

  • time

    Accelerate time to action
    and control

  • cost

    Cost efficiency

Built on NVIDIA® Pascal™ GPU architecture

Premio GPU Computing Systems are built on the highly efficient NVIDIA® Pascal™ architecture featuring 4GB GDDR5 and 768 CUDA® cores that delivers amazing performance with impressive power-efficiency. The GTX 1050Ti features 1.73 TFLOPS with a max TDP of 75W, making it the best fit for industrial computers that require optimal performance and wide range operating temperature.

GPU Architecture Pascal
NVIDIA® CUDA® Cores 768
Frame Buffer 4 GB GDDR5
Memory Speed 7 Gbps
Boost Clock 1392 MHz

Support up to 8K Resolution & 6 Independent Displays


Through combining discrete NVIDIA GTX 1050Ti and integrated Intel HD Graphics units, Premio GPU computers enable support for up to 8K resolution and six independent displays.

Versatile Industrial I/O Interfaces & Diverse Expandability


Rich multi-functional I/O ports including Dual GbE (additional 4x LAN port on RCO-6020-1050TI), 4x COM, up to 8x USB, and 8 digital I/O ports allow Premio’s industrial GPU computer for better expansion and future utility. An additional up to 4 mini PCIe slots provide more flexibility for multiple applications.

Robust system design enabling GPU computing in harsh environment


Flexibility and performance are packed into a robust and durable design for incomparable user experience. Premio GPU computing systems go through a rigorous design cycle with strict quality assurance procedures and extensive product testing. These industrial computers are the ideal solution for versatile operations in rough and harsh environments.

Successful Deployment Applications For Industrial GPU Computer

Inference Processing
and Machine Learning At The Edge

Reducing Airport Security Check to Just 20 Seconds using powerful GPU computing for machine learning and facial recognition

Industrial Metrology and Quality Inspection at the Edge

High Performance Industrial GPU Computer Helps Industrial Metrology Increase Scan Speeds up to 10X Faster

Machine vision

Machine learning

Medical imaging


An Industrial GPU computer is a rugged, edge computing solution that utilizes a dedicated GPU (Graphics Processing Unit) card for computational intensive applications requiring advanced image processing and machine vision/intelligence. In addition to a performance boost from the GPU, an industrial GPU computer will also have all the key requirements of what makes up an industrial computer, such as support for high shock/vibration ratings, wide operating temperatures, and over voltage/reverse polarity protection. The industrial GPU computer is transforming how factory automation and smart manufacturing verticals are utilizing computational analysis and machine intelligence in real-time.

  • Computer / Machine Vision

    • Production line inspection
    • Medical imaging
    • Metrology imaging
    • Facial recognition
  • Navigation

    • Autonomous vehicle
    • Pathfinding
  • Automation

    • Factory automation
    • Pathfinding
  • Artificial Intelligence

    • Deep learning
    • Machine learning

Both GPUs (Graphics Processing Unit) and CPUs (Central Processing Unit) have many traits in common; they are both specifically designed microprocessors to handle various tasks. The key difference is HOW they process these tasks. In a computer, the CPU is often referred to as the brain of the system; it is the central processing unit which handles all computing tasks. A GPU, while similar to a CPU, is engineered specifically to process or render graphics. As such, a GPU can work in conjunction with the CPU to help it offload graphics intensive tasks, while freeing up the CPU for other non-graphics related jobs.


The CPU is ideal for serialized, generic tasks, which makes it well-suited for common business or productive applications such as Word, Excel, or a web browser. The number of cores in a given CPU is limited, up to 28 cores for the latest Xeon server class CPU. Conversely, the GPU comes with hundreds or even thousands of cores, which is designed for parallelized, specific tasks; the GPU is optimized for intensive computational applications such as image processing or AI.

As an example, let's examine the fundamentals of image processing. The 4K image of the clock consists of 8.2 million discrete pixels (4K resolution is 3,840 x 2,160, which gives us 8.2 million pixels). From a high level, in order to process the image, we will need to perform some type of computation to each individual pixel. If this task is given to a CPU, with its limited number of cores, the processing time will take very long, as the CPU does not have enough cores to handle the task in parallel. The GPU, which its thousands of specialized cores, can complete the task up to 50-100X faster due to its parallel architecture. This makes the GPU the optimal microprocessor to handle tasks that require parallelism with a high degree of computation.

We begin with a proven embedded system that is engineered to withstand extreme shock and vibration, along with a wide operating temperature range; the inclusion of an industrial class GPU will enable the system to operate reliability in industrial/manufacturing sectors, with the GPU handling AI or image processing applications that require massive parallelism.

One way to compare the performance of various GPUs is by their TFLOP rating. TFLOP stands for "teraflop," which is a measurement of the GPU to performance one trillion floating point operations per second. By adding a GPU to an industrial system, another critical variable we need to consider is the TDP (Thermal Design Power) rating of the GPU. The TDP rating tells us the maximum heat, in watts, generated by the GPU when operating at maximum capacity. This is key in determining the operational temperature range of an industrial GPU system, which should be optimally in the range of -25C to 60C for factory/manufacturing averse conditions. By looking at the Performance versus TDP chart below, we can see the direct correlation between these two values: as the GPU performance increases, so does its corresponding TDP value. When designing an industrial GPU system, there is a fine balance to strike between GPU performance versus overall system operating temperature.

Ports Accessibility All front facing ports
Ideal for factory line mounting
Front and rear facing ports
Vibration Rating 3 Grms
Ideal for staionary factory line mount
Higher 5 Grms
Ideal for mobile mount in cars or carts
Wide Range Temperature -25C to 70C (-13F to 158F) -25C to 70C (-13F to 158F)
Wide Range Voltage 9 ~ 50 VDC 9 ~ 48 VDS
Expandability 2x mini PCIe slots 2x universal slots for additional ports, 2x mini PCIe slots
Communication Wifi optional; 2x antenna holes Wifi and Cellular (4G/LTE) optional; 4x antenna holes
Mounting Wallmount, Bookmount, or DIN rail Wallmount
Shared Features
Processor Intel Skylake 6th gen / Kaby Lake 7th gen i3, i5, i7, quad core
Chipset Intel Q170
Digital I/O ports 8 in / 8 out isolated
Video Ports 2x DVI-I, 1x HDMI, 3x DisplayPort