Highlights:
  • Rack Height: 4U
  • Processor: 2x AMD EPYC 7002-Series
  • Drive Bays: 8x 2.5" Hot-Swap
  • 8x NVIDIA A100 SXM4 GPUs
Contact sales for pricing

The TensorEX TS4-130921967-DPN is a 4U rack mountable Deep Learning & AI server supporting 2x AMD EPYC 7002-Series processors, a maximum of 4 TB DDR4 memory, and 8x NVIDIA A100 Ampere GPUs (SXM4), with up to 600 GB/s NVLINK interconnect.

GPUs have provided groundbreaking performance to accelerate deep learning research with thousands of computational cores and up to 100x application throughput when compared to CPUs alone. Exxact has developed the TensorEX TS4-168747704-DPN, featuring NVIDIA GPU technology coupled with state-of-the-art NVLINK interconnect technology, and a full pre-installed suite of the leading deep learning software, for developers to get a jump-start on deep learning research with the best tools that money can buy.

Features:

  • Supports 2x AMD EPYC 7002-Series processors
  • 8x A100 40 GB SXM4 GPUs (19.5 TFlops of single precision, 1555 GB/s of memory bandwidth, and 40 GB of memory per board)
  • NVIDIA DIGITS software providing powerful design, training, and visualization of deep neural networks for image classification
  • Pre-installed standard Ubuntu 18.04 w/ Deep Learning software stack
  • Google TensorFlow software library
  • Automatic software update tool included
  • A turn-key server with up to 600GB/s NVLINK interconnect

NVIDIA SXM4 GPU Options

ModelStandard MemoryMemory Bandwidth (GB/s)CUDA CoresTensor CoresSingle Precision (TFLOPS)Double Precision (TFLOPS)Power (W)Explore
A100 40 GB SXM440 GB HBM2e1555691243219.59.7400--

EMLI (Exxact Machine Learning Images)


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

Conda EMLI

Separated Frameworks

Container EMLI

Flexible. Reconfigurable.

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 NVIDIA GPU Solutions

Processor & Chipset
Number of Processors Supported
2
Processor Socket
Socket SP3
Processor Type
EPYC
Processor Supported
  • 7002-Series
Thermal Design Power (TDP)
240 W
GPU
8x NVIDIA A100 Ampere SXM4
Chipset Manufacturer
N/A
Chipset Model
SoC
Memory
Maximum Memory
4 TB
Memory Technology
  • DDR4 SDRAM
Memory Standard
DDR4-3200/PC4-25600
Number of Total Memory Slots
32
Controllers
SATA3
  • Via SoC
Display & Graphics
Graphics Controller Manufacturer
ASPEED
Graphics Controller Model
AST2500
Network & Communication
Ethernet Technology
  • 1000BASE-T
I/O Expansions
PCI Express
  • 8x PCI-E 4.0 x16 slots (Low-Profile)
Drive Bays
Hot-swap
  • 8x 2.5 hot-swap drive bays
  • Supports 4x NVMe drives
Interfaces/Ports
Total Number of USB 3.0 Ports
2
Number of SATA Interfaces
8
Number of NVMe Interfaces
4
LAN
  • 2x RJ45 1000BASE-T Ports
  • 1x RJ45 Dedicated IPMI Port
Onboard Video
1x VGA Connector
Serial Port / Header
1x COM Header
TPM
1x TPM Header
Power Description
Number of Power Supplies
4
Redundant Power Supplies
Yes
Maximum Power Supply Wattage
3000 W
Certification
80 Plus Platinum
Physical Characteristics
Color
Black
Form Factor
Rack-mountable
Rack Height
4U
Height
10.32"
Width
17.6"
Depth
35.43"