H100 80GB SXM5
GPU cores
GPU memory
8x NVIDIA H100 80 GB
Dual 56-core 4th Gen Intel Xeon CPU
32x 64 GB DDR5
8x single-port ConnectX-7 VPI 400 Gb/s InfiniBand / 200Gb/s Ethernet
2x dual-port ConnectX-7 VPI 400 Gb/s InfiniBand / 200Gb/s Ethernet
2x 1,92 TB NVMe M.2
8x 3,84 TB NVMe U.2
10 Gb/s onboard NIC (RJ45)
50 GbE optional NIC
RAM
NVMe for OS
NVMe for data
Hardware
Parametr | NVIDIA DGX H100 640 GB |
---|---|
GPUs | 8× NVIDIA H100 SXM5 80 GB |
GPU memory | 640 GB |
CPU | Dual Intel Xeon Platinum 8480C CPU, (112 jader) 2.00 GHz (Base), 3.80 GHz (Max Boost) |
Výkon (FP8 tensor operace) | 32 PetaFLOPS (FP8) |
# CUDA jader | 135 168 |
# Tensor jader | 4 224 |
Multi-instantce GPU | 56 instancí |
RAM | 2 TB |
HDD | OS: 2× 1.92 TB NVMe data: 30 TB (8× 3.84 TB) NVMe |
Network | 8x single-port ConnectX-7 VPI 400 Gb/s InfiniBand/ 200Gb/s Ethernet 2x dual-port ConnectX-7 VPI 400 Gb/s InfiniBand/ 200Gb/s Ethernet |
Max. spotřeba | ~10,2 kW max |
Provedení | rack, 8U |
Technická specifikace | Datasheet |
Software
But what is much more interesting is the aforementioned software features of the offered NVIDIA machines. They all offer pre-installed and especially performance-tuned machine learning environments (e.g. Caffe, or Cafe 2, Theano, TensorFlow, Torch, or MXNet) or intuitive data analytics environments (NVIDIA Digits). All neatly packaged in Docker containers, freely downloadable on the NVIDIA GPU Cloud (NGC). Such a tuned environment provides 30% more power for machine learning applications against applications deployed purely on NVIDIA hardware. The main advantage of the pre-installed environment is the deployment speed, which is in units of hours.
NVIDIA GPU Cloud (NGC)
NVIDIA GPU Cloud (NGC) represents the repository of the most used frameworks for machine learning and deep learning applications, HPC applications, or NVIDIA GPU cards accelerated visualization. Deploying these applications is a question minutes — copying a link of the appropriate Docker image from the NGC repository, moving it on the DGX system, and downloading and running the Docker container. The individual development environments – versions of all included libraries and frameworks, settings of environment parameters – are updated and optimized by NVIDIA for deployment on DGX systems. https://ngc.nvidia.com/
Support
The strength of the NVIDIA solution is to support the entire system. Hardware support (in case of failure of any of the components) is a matter of course. Software support for the entire environment is critical if something does not work as intended. The customer has hundreds of developers ready to help. Support is part of NVIDIA DGX purchase. It is available for 3-5 years and can be extended beyond this period.
NVIDIA support covers:
- Dispatch a customer engineer onsite for field replacement unit (FRU) replacement
- Run onboard diagnostic tools (from remote) to troubleshoot system issues
- Remote software support
- Access to the latest software updates and upgrades
- Direct communication with NVIDIA support experts
- A private NGC container repository for accessing NVIDIA-optimized AI software with powerful sharing and collaboration features for your organization
- A searchable knowledge base with how-to articles, application notes, and product documentation
- Rapid response and timely issue resolution through a support portal and 24×7 phone access
- Lifecycle support for NVIDIA DGX systems’ AI software
- Replacement of defective HW components by the next working day
- DGX Systems Appliance Support Services Terms and Conditions
- End-user license agreement (EULA)
Through a combination of tuned hardware, software and NVIDIA support, NVIDIA DGX delivers significantly higher performance and acceleration in the learning phase of machine learning applications:
NVIDIA offers special programs for DGX systems and Tesla accelerators for EDU organizations or start-up companies. Thanks to the international collaboration between NVIDIA and IBM Global Financing, preferential financing in the form of operating leases is available for DGX models.
The NVIDIA Deep Learning Institute (DLI) offers both online and hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing.
M Computers represents NVIDIA on the Czech market in the Enterprise area of computing accelerators and AI systems.
Last year, it was the first company in Central and Eastern Europe to receive the highest ELITE PARTNER status, as well as two NVIDIA AI Innovator and NVIDIA AI Champion awards.
Testing
To test the performance and, above all, the speed of deployment of ML and AI applications, we have the NVIDIA DGX Station system for testing, as well as the NVIDIA A100 and other latest NVIDIA card models as part of the NVIDIA Tesla Test Drive program. If you are interested in our testing offer, please fill out this form.