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Desktops for Faster Deep Learning Training

NVIDIA Multi-GPU Systems for Deep Learning and AI Research

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Multi-GPU Performance

Leverage the latest NVIDIA GPUs including the RTX 4090/4080/4070, RTX 6000 Ada, RTX A6000 and more to accelerate AI development.

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Pre-Installed Frameworks

Our systems come pre-loaded with TensorFlow, PyTorch, Keras, Caffe, RAPIDS, Docker, Anaconda, MXnet, and more upon request.

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Standard 3 Year Warranty

We value your peace of mind so you can focus on what matters most. Every Exxact system is backed by our 3-year warranty and support.

Built on Intel Xeon W, Xeon Scalable Platform

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Dual GPU Intel XeonW-2400

VWS-173807702

Starting at

$4,829.00

Highlights
CPU1x Intel Xeon W-2400 Series
GPUSupports 2x NVIDIA RTX 6000 Ada or 1x RTX 4090/4080 GPUs
MEMUp to 2TB DDR5 ECC Memory
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Quad GPU Intel XeonW-3400

VWS-105726817

Starting at

$7,007.00

Highlights
CPU1x Intel Xeon W-3400 Series
GPUSupports 4x NVIDIA RTX 6000 Ada or 2x RTX 4090/4080 GPUs
MEMUp to 2TB DDR5 ECC Memory
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Quad GPU Intel XeonScalable

TWS-115999024

Starting at

$9,649.20

Highlights
CPU2x 3rd Gen Intel Xeon Scalable Series
GPUSupports 4x NVIDIA RTX 6000 Ada, L40S, or H100 GPUs
MEMUp to 2TB DDR4 ECC Memory

Built on AMD Ryzen, Threadripper, EPYC Platform

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Dual GPU AMD Ryzen7000X

VWS-117809462

Starting at

$3,806.00

Highlights
CPU1x AMD Ryzen 7000 Series Processor
GPUUp to 2x NVIDIA RTX 6000/5000 Ada or 1x RTX 4090/4080 GPUs, and more
MEMUp to 192GB DDR5 Memory
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Quad GPU AMD Threadripper PRO5000WX

VWS-148320247

Starting at

$7,326.00

Highlights
CPU1x AMD Ryzen Threadripper PRO 5000WX
GPUUp to 4x NVIDIA RTX 6000/5000 Ada or 2x 4090/4080, and more
MEMUp to 1TB DDR4 ECC Memory
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Quad GPU AMD Threadripper PRO7000WX

VWS-157259920

Starting at

$7,353.50

Highlights
CPU1x AMD Ryzen Threadripper PRO 7000WX
GPUUp to 4x NVIDIA RTX 6000/5000 Ada, A800, or 2x 4090/4080, and more
MEMUp to 2TB DDR5 ECC Memory

Build your ideal system

Need a bit of help? Contact our sales engineers directly.

EMLI Software
Exxact Machine Learning Images

Flexible Development Environments with Up-to-Date Frameworks

Our deep learning systems ship with the latest AI development tools installed in a way that best suits your development needs, whether you prefer containerized environments or natively installed frameworks.

An EMLI Environment for Every Developer

Conda EMLI

Conda EMLI

Separated Frameworks

For developers who want pre-installed deep learning frameworks and their dependencies in separate Python environments installed natively on the system.


Container EMLI

Container EMLI

Flexible. Reconfigurable.

For developers who want pre-installed frameworks utilizing the latest NGC containers, GPU drivers, and libraries in ready to deploy DL environments with the flexibility of containerization.


DIY EMLI

DIY EMLI

Simple. Clean. Custom.

For experienced developers who want a minimalist install to set up their own private deep learning repositories or custom builds of deep learning frameworks.

ai inference cycle
Deep Learning Lifecycle

NVIDIA Powered Data Center Platforms

Training

With deep neural networks becoming more complex, training times have increased dramatically, resulting in lower productivity and higher costs. Exxact's deep learning infrastructure technology featuring NVIDIA GPUs significantly accelerates AI training, resulting in deeper insights in less time, significant cost savings, and faster time to ROI.

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Inference

Data center managers must make tradeoffs between performance and efficiency. A single inference server from Exxact can replace multiple commodity CPU servers for deep learning inference applications and services, reducing energy requirements and delivering both acquisition and operational cost savings.

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Accelerate Deep Learning Initiatives

NVIDIA DGX

The universal system for all AI workloads, offering unprecedented compute density, performance, and flexibility in the world’s first portfolio of purpose-built deep learning systems! Leverage over 32 petaFLOPS of AI performance.

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Partnerships

nvidia
pny
panasas
ansys
Bright Computing
BeeGFS