- Rack Height: 2U
- Processor Supported: 2x IBM POWER8 with NVLINK
- Drive Bays: 2x 2.5" Hot-Swap
- Supports up to 4x NVIDIA Tesla P100 SXM2 GPUs
The TensorEX TS2-306052-DPN is a 2U rack mountable Deep Learning & AI Server supporting 2x IBM POWER8 with NVLINK processors, a maximum of 1 TB DDR4 memory, and four Tesla P100 Pascal GPUs (SXM2), with up to 80GB/s NVLINK GPU-GPU 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 Deep Learning DevBox, featuring NVIDIA GPU technology coupled with state-of-the-art NVLINK GPU-GPU 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.
- Supports 2x IBM POWER8 with NVLINK processors
- 4x Tesla P100 SXM2 (10.6 TFlops of single precision, 732 GB/s of memory bandwidth, and 16 GB of memory per board) GPUs
- 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 80GB/s NVLINK GPU-GPU interconnect
EMLI (Exxact Machine Learning Images)
*Additional NGC (NVIDIA GPU Cloud) containers can be added upon request.
Conda EMLISeparated Frameworks
Container EMLIFlexible. Reconfigurable.
DIY EMLISimple. 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.
|Microsoft Cognitive Toolkit||—||—|
|NVIDIA CUDA Toolkit|
|NVIDIA CUDA Dev Toolkit||—|
|Micro-K8s||Free upgrade available||Free upgrade available||Free upgrade available|
- Integrated onboard
- 2x PCI-E 3.0 x16 slots
- 3x PCI-E 3.0 x8 slots
- 4x RJ45 10GBASE-T Ethernet LAN Ports
- 1x RJ45 IPMI LAN Port