NVIDIA Powered AI Servers

Built for AI research and engineered with the right mix of GPU, CPU, storage, and memory to crush deep learning workloads.

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Multi-GPU Performance

Leverage the latest in accelerator technology from NVIDIA, including the NVIDIA RTX A6000, A5000, NVIDIA A100, NVIDIA A40, A30 and more.

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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

Have peace of mind, focus on what matters most, knowing your system is backed by a 3 year warranty and support.

Deep Learning Servers with AMD EPYC CPUs

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Base Specs
CPU1x AMD EPYC 7003 CPU
GPUUp to 4x NVIDIA A100, A40, A30, RTX A6000, or RTX A5000 GPUs
MEMUp to 2TB DDR4 Memory
STOUp to 60TB NVMe Storage
NETPCI-E 4.0 Compatible
Solution image
Base Specs
CPU2x AMD EPYC 7003 CPUs
GPUUp to 4x NVIDIA A100, A40, A30, RTX A6000, or RTX A5000, GPUs
MEMUp to 1TB DDR4 Memory
STOUp to 60TB NVMe Storage
NETPCI-E 4.0 Compatible
Solution image
Base Specs
CPU2x AMD EPYC 7003 CPUs
GPUUp to 10x NVIDIA A100, A40, A30, RTX A6000, or RTX A5000 GPUs
MEMUp to 4TB DDR4 Memory
STOUp to 96TB Storage
NETPCI-E 4.0 Compatible

Deep Learning Servers with Intel Xeon CPUs

Solution image
Base Specs
CPU2x Intel Xeon Scalable CPUs
GPUUp to 4x NVIDIA A100, A40, A30, RTX A6000, or RTX A5000 GPUs
MEMUp to 2TB DDR4 Memory
STOUp to 60TB NVMe Storage
NETGigabit Ethernet
Solution image
Base Specs
CPU2x Intel Xeon Scalable CPUs
GPUUp to 10x NVIDIA A100, A40, A30, RTX A6000, or RTX A5000 GPUs
MEMUp to 1.5TB DDR4 Memory
STOUp to 96TB NVMe Storage
NET10G Ethernet
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Base Specs
CPU2x Intel Xeon Scalable CPUs
GPU8x NVIDIA Tesla A100 SXM4-40GB or 80GB + NVSwitch
MEMUp to 8TB DDR4 Memory
STOUp to 96TB NVMe Storage
NETPCI-E 4.0 Compatible
nv tesla sol hero 2
Accelerate Deep Learning Initiatives

NVIDIA DGX™ A100

The universal system for all AI workloads, offering unprecedented compute density, performance and flexibility in the world’s first 5 petaFLOPS AI system. Order yours today.

a100 graph bert large
BERT pre-training throughput using Pytorch, including (2/3) Phase 1 and (1/3) Phase 2 | Phase 1 Seq Len = 128, Phase 2 Seq Len = 512; V100: NVIDIA DGX-1™ server with 8x V100 using FP32 precision; A100: DGX A100 Server with 8x A100 using TF32 precision.
a100 graph bert large inference
BERT Large Inference | NVIDIA T4 Tensor Core GPU: NVIDIA TensorRT (TRT) 7.1, precision = INT8, batch size = 256 | V100: TRT 7.1, precision = FP16, batch size = 256 | A100 with 7 MIG instances of 1g.5gb: pre-production TRT, batch size = 94, precision = INT8 with sparsity.
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.

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Find Your Perfect Deep Learning Environment with EMLI

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*Additional NGC (NVIDIA GPU Cloud) containers can be added upon request.

Conda EMLI

Conda EMLI

Separated Frameworks
Container EMLI

Container EMLI

Flexible. Reconfigurable.
DIY EMLI

DIY EMLI

Simple. Clean. Custom.

Who is it for?

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

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.

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

Frameworks*

TensorFlow V1
TensorFlow V2
PyTorch
MXnet
Caffe
Caffe2
Chainer
Microsoft Cognitive Toolkit

Libraries*

NVIDIA cuDNN
NVIDIA Rapids
Keras
Theano
OpenCV

Software Environments

NVIDIA CUDA Toolkit
NVIDIA CUDA Dev Toolkit
NVIDIA Digits
Anaconda

Container Management

Docker

Drivers

NVIDIA-qualified Driver

Orchestration

Micro-K8s

Free upgrade availableFree upgrade availableFree upgrade available
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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ai inference cycle
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Partnerships

nvidia
pny
panasas
ansys
Bright Computing
BeeGFS