NVIDIA DGX™ Systems
Guarantee ROI for your NVIDIA DGX™ deployment
with Lambda’s deep learning expertise
Accelerate development with purpose-built software for ML/AI
All DGX systems come with the DGX software stack, including AI frameworks, scripts, and pre-trained models. It also comes with cluster management, network/storage acceleration libraries, and an optimized OS.
Maximize uptime with first-party support by NVIDIA
Get your team up and running quickly with NVIDIA’s onboarding programs and comprehensive hardware, software, and ML support customized to your organization.
Scale efficiently by leveraging Lambda’s expertise in deep learning
Build tailored MLOps infrastructure for your company with consulting from Lambda engineers on machine learning frameworks, training platforms, as well as compute hardware, power, networking, and storage.
Bring infrastructure online faster with less expense
We will install and deploy your machines onsite, or you can use Lambda Colocation to also save on operating expenses.
NVIDIA DGX™ compute solutions
As your organization and compute workloads grow, Lambda’s deep learning engineers can provide guidance and support on choosing the right compute solutions tailored to your applications and requirements.
NVIDIA DGX Station™ A100
Server-class workstation ideal for experimentation and development by teams. No data center required.
NVIDIA DGX A100™
The third generation of the world’s most advanced AI system, unifying all AI workloads.
NVIDIA DGX POD™
Industry-standard infrastructure designs for the AI enterprise.
NVIDIA DGX SuperPOD™
Full-cycle, industry-leading infrastructure for the fastest path to AI innovation at scale.
Your servers. Our datacenter.
Lambda’s DGX-Ready Colocation makes it easy to deploy and scale your machine learning infrastructure in weeks, not months.
10,000+ research teams trust Lambda
NVIDIA DGX™ H100
Up to 9x training speed with next-gen NVIDIA H100 GPUs based on the Hopper architecture*
- 8U server with 8 x NVIDIA H100 Tensor Core GPUs
- 1.5x the inter-GPU bandwidth
- 2x the networking bandwidth
- Up to 30x higher inference performance**
*MoE Switch-XXL (395B Params), pending verification
**Inference on Megatron 530B parameter model chatbot for input sequence length=128, output sequence length =20 |32 A100 HDR IB network vs 16 H100 NDR IB network
More from the Deep Learning Experts
Multiple Pairwise Ranking Networks for Personalized Video Summarization
We propose a model for personalized video summaries by conditioning the summarization process with predefined categorical labels.
HoloGAN: Unsupervised Learning of 3D Reps. from Natural Images
We propose a novel generative adversarial network (GAN) for the task of unsupervised learning of 3D representations from natural images.
RenderNet: A Deep ConvNet for Differentiable Rendering from 3D Shapes
We present a differentiable rendering convolutional network with a novel projection unit that can render 2D images from 3D shapes.
Adversarial Monte Carlo Denoising with Conditioned Aux. Feature Modulation
We demonstrate that GANs can help denoiser networks produce more realistic high-frequency details and global illumination.