Graphics Cards & AI Accelerators

Our range of graphics cards and accelerators includes high-performance GPUs for industrial AI workloads. Including workstation-grade NVIDIA RTX, Quadro cards and edge AI accelerators like Jetson, we supply solutions optimised for visualisation, compute, and inferencing.

These accelerators are ideal for demanding applications such as 3D rendering, simulation, AI inference, deep learning, and real-time data processing.

We provide GPU and accelerator integration as part of our embedded and rackmount system builds, delivering performance where it matters most. Contact us today for more information.

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Showing 18 of 18 Graphics Cards and Accelerators items

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Nvidia SKY-QUAD-2000A-16

RTX 2000 ADA 16GB GDDR6 Workstation PCI-Express Graphics Card

Nvidia SKY-QUAD-5000A-32

RTX 5000 ADA 32GB GDDR6 Workstation PCI-Express Graphics Card

Nvidia SKY-QUAD-6000A-48

RTX 6000 ADA 48GB GDDR6 Workstation PCI-Express Graphics Card

Hailo AI-MXM-H84A

Aetina Ai Accelerator MXM Module – 4x Hailo-8 Ai Inference Processors

1 option available

Nvidia MXM-RTX-A4500 Series

NVIDIA A4500 Embedded 16GB GDDR6 MXM Graphics Card

1 option available

Nvidia MXM-RTX-A1000 Series

NVIDIA A1000 Embedded 4GB GDDR6 MXM Graphics Card

1 option available

Nvidia MXM-RTX-A2000 Series

NVIDIA A2000 Embedded 8GB GDDR6 MXM Graphics Card

1 option available

Nvidia MXM-RTX-A500 Series

NVIDIA A500 Embedded 4GB GDDR6 MXM Graphics Card

Our Team Is Here to Help

Get in touch with us today.

Speak to a member of our friendly team to discuss your project and find out how we can support you. Our technical sales team are ready to answer your questions.

Call: +44 (0)1782 337 800 | Email: sales@impulse-embedded.co.uk

Kneron Mini-AI-520 Series

Kneron Kl520 NPU AI Edge Mini PCIe Module

Kneron M2AI-2280-520 Series

Kneron Kl520 NPU AI Edge M.2 2280 Module

Intel VEGA-320 Series

Ai Edge Computing M.2 Module With 1X Intel Movidius Myriad X Vpu

Kneron M2AI-2242-520 Series

Kneron Kl520 NPU AI Edge M.2 2242 Module

Intel VEGA-330 Series

Ai Edge Computing Full-Size Minipcie Module With Intel Movidius Myriad X Vpu

Nvidia SKY-QUAD-4000A-20

RTX 4000 ADA 20GB GDDR6 Workstation PCI-Express Graphics Card

Nvidia SKY-QUAD-4000SA-20

RTX 4000 SFF ADA 20GB Workstation PCI-Express Graphics Card

Nvidia SKY-QUAD-4500A-24

RTX 4500 ADA 24GB GDDR6 Workstation PCI-Express Graphics Card

2 options available

Axelera AI Metis PCIe AI Accelerator Card Series

Axelera AI Metis AI Accelerator PCIe Card

2 options available

Axelera AI Metis M.2 AI Accelerator Card Series

Metis AI Accelerator M.2 Card

Frequently Asked Questions

Learn More About Graphics Cards & Accelerators

Graphics cards and accelerators are used to add extra processing capability to a compatible system, particularly for workloads that benefit from parallel compute performance. Common applications include AI inference, machine vision, video processing, graphics rendering, simulation and data-intensive analysis.

Graphics cards and accelerators are components that are installed within a host system, whereas a GPU computer is a complete platform built to deliver accelerated performance as a finished solution. They are typically chosen when a customer already has, or is selecting, a system that can support additional GPU or accelerator hardware.

Key considerations include application requirements, compatibility with the host system, physical size, power draw, thermal demands and software support. It is also important to check whether the target system has the right expansion interfaces, space and cooling capacity to support the chosen card.

Yes, many graphics cards and accelerators are well suited to AI and parallel processing tasks, especially where applications involve inference, image analysis, model execution or high-throughput data handling. The right option depends on the performance target, system constraints and the software environment being used.

In some cases, yes, but this depends on whether the existing system supports the required expansion slot, power provision and thermal design. Checking compatibility early is important, as not all industrial or embedded computers are designed to accommodate high-performance accelerator hardware.

An accelerator can be a good option when the goal is to enhance the performance of a compatible existing system without moving to a completely new platform. This can suit projects where the base system is already in place and only additional processing power is needed for a specific workload.