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NVIDIA Data Centre GPUs


NVIDIA® Data Centre GPUs bring the latest parallel GPU processing to a range of applications – from data science, to research, artificial intelligence, machine learning and more. XENON can design a server with proper power, cooling and memory to power single or multiple GPUs. XENON also builds workstation solutions with these GPUs – unleashing the power of GPU computing into a desktop form factor, at home in ambient room temperatures and with standard power supplied. Contact the XENON solutions team to discover which NVIDIA GPU is right for your requirements.

For a limited time, a four hour, self-paced course – AI in the Data Centre – is available for up to 3 team members with each NVIDIA Data Centre GPU purchased. Spaces are limited. Contact us to learn more.

Download a summary of the NVIDIA Data Center GPU Platform here.

model no.
description
key features
model no. NVIDIA L40S GPU «NEW»
description

The NVIDIA L40S GPU is the most powerful universal GPU for the data centre, delivering end-to-end acceleration for the next generation of AI-enabled applications—from generative AI and model training and inference to 3D graphics, rendering, and video applications.

key features
  • NVIDIA Ada Lovelace Architecture
  • GPU Memory 48GB GDDR6 with ECC
  • 864GB/s GPU memory bandwidth
  • Includes fourth-generation Tensor Cores and an FP8 Transformer Engine, delivering over 1.45 petaflops of tensor processing power

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model no. NVIDIA L4 GPU «NEW»
description

The NVIDIA L4 Tensor Core GPU delivers a versatile platform to accelerate Deep Learning, Graphics and Video processing applications in the Cloud and at the Edge.

GPU Architecture NVIDIA Ada Lovelace Architecture
.

key features
  • NVIDIA Ada Lovelace Architecture
  • Featuring 24 GB of GDDR6 memory, x16 PCIe Gen4 connectivity at a 72 W maximum power envelope
  • 300 GB/s GPU memory bandwidth
  • Equipped with L4 enable up to 120X higher AI Video performance

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model no. NVIDIA L40 GPU «NEW»
description

The NVIDIA L40 brings the highest level of power and performance for visual computing workloads in the data center.

key features
  • NVIDIA Ada Lovelace Architecture
  • 48 GB GDDR6 with ECC
  • Fourth-generation Tensor Cores
  • NVIDIA vPC/vApps, NVIDIA RTX Virtual Workstation (vWS)

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model no. NVIDIA H100 Tensor Core GPU «NEW»
description

The NVIDIA H100 Tensor Core GPU powered by the NVIDIA Hopper GPU architecture delivers the next massive leap in accelerated computing performance for NVIDIA’s data center platforms.

key features
  • A new Transformer Engine enables H100 to deliver up to 9x faster AI training and up to 30x faster AI inference speedups on large language models compared to the prior generation A100
  • Combination of fourth-generation NVlink offers 900 gigabytes per second (GB/s) of GPU-to-GPU interconnect
  • Delivers 60 teraFLOPS of FP64 computing for HPC
  • Delivers 3 terabytes per second (TB/s) of memory bandwidth per GPU and scalability with NVLink and NVSwitch

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model no. NVIDIA DGX H100 CNX PCIe «NEW»
description

NVIDIA H100 CNX combines the power of the NVIDIA H100 with the advanced networking capabilities of the NVIDIA ConnectX®-7 smart network interface card (SmartNIC) in a single, unique platform.

key features
  • GPU Memory: 80GB HBM2e
  • Memory Bandwidth: > 2.0TB/s
  • PCIe Gen5 128GB/s
  • NVIDIA H100 and ConnectX-7 are connected via an integrated PCIe Gen5 switch

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model no. NVIDIA A100 Tensor Core GPU PCIe
description

New NVIDIA A100 Tensor Core GPU in a PCIe form factor. Third generation Tensor Cores with 20x performance increase. Multi-Instance GPU capable, the A100 can be configured into 7 vGPU’s individually or in combinations to provide maximum flexibility in data analytics, training and inference.

key features
  • GPU Memory: 80GB
  • GPU Memory Bandwidth: 1,935 GB/s
  • Up to 7 Multi-instance GPU (MIG), with 5GB memory each
  • PCIe form factor
  • 300W total power draw

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model no. NVIDIA A40 Tensor Core GPU PCIe
description

New NVIDIA A40 Tensor Core GPU in PCIe Form Factor. Virtualisation ready to deliver flexibility and agility along with the lightening fast performance of NVIDIA Ampere Architecture. All new design to optimise Tensor Cores, memory and PCIe Gen4. The worlds most powerful data centre GPU for visual computing, VR, AI, HPC workloads.

 

key features
  • GPU Memory: 48GB
  • GPU Memory Bandwidth: 696 GB/s
  • vGPU capable with multiple config options
  • PCIe Generation 4 form factor
  • 300W power draw, passive thermal

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model no. NVIDIA A30 Tensor Core GPU «NEW»
description

Versatile compute acceleration for mainstream enterprise servers.

key features
  • features FP64 NVIDIA Ampere architecture Tensor Cores
  • Up to 3X higher throughput than v100 and 6X higher than T4
  • 24 gigabytes (GB) of GPU memory
  • GPU memory bandwidth of 933 gigabytes per second (GB/s)

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model no. NVIDIA A16 Tensor Core GPU «NEW»
description

Unlock an unprecedented VDI user experience.

key features
  • 4x 16GB GDDR6 with error-correcting code (ECC)
  • GPU memory bandwidth of 4x 232GB/s
  • More than 2x the Encoder Throughput
  • Supports multiple, high-resolution monitors (up to two 4K or a single 5K)

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model no. NVIDIA A10 Tensor Core GPU «NEW»
description

Accelerated graphics and video with AI for mainstream enterprise servers.

key features
  • Ultra-fast GDDR6 memory, delivering 600 GB/s of bandwidth
  • 24GB GDDR6 GPU memory
  • Compact, single-slot, 150W GPU
  • Tensor Float 32 (TF32) precision provides up to 5X the training throughput

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model no. NVIDIA A2 Tensor Core GPU «NEW»
description

NVIDIA A2’s versatility, compact size, and low power exceed the demands for edge deployments at scale, instantly upgrading existing entry level CPU servers to handle inference.

key features
  • Features a low-profile PCIe Gen4 card and a low 40-60W configurable thermal design power (TDP) capability
  • Features 16 GB of GDDR6 memory
  • Supports x8 PCIe Gen4 connectivity
  • Powered by the NVIDIA Ampere Architecture

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model no. NVIDIA Tesla T4
description

Powered by NVIDIA Turing™ architecture and purpose-built to boost efficiency for scale-out servers running deep learning workloads.

key features
  • Small form-factor, 50/75-Watt design fits any scale-out server.
  • INT8 operations slash latency by 15X.
  • Hardware-decode engine capable of transcoding and inferencing 35 HD video streams in real time.

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