Hardware Optimized for Maximum Performance
A Purpose-Built AI Appliance, Instead of a Re-purposed Commodity Server
- More cores per server; 112 cores keep the GPUs fed vs core-constrained designs
- Fastest Architecture for your AI projects; Up to 2TB system memory for processing large amounts of data, NVMe drives speed data access
- Superiour Parallelism using NVLink; NVLink and NVSwitch shrinks training time on complex models, SMX architecture outperforms PCIe by 1.5x or more
- Purely designed for Speed and Scale; Infiniband network I/O for each DGX ensures maximum performance and multi-system scale
- Benchmarked for success, your success; Consistently delivering record-setting performance in leading industry benchmarks like MLPerf.
We know that when evaluating AI infrastructure, there are a lot of options out there, and you could be faced with a whole lot of permutations in terms of CPU and RAM and IO and more. Unlike a general-purpose server re-purposed for AI, NVIDIA DGX systems come in only one configuration, and are purpose built with only one application in mind, and that is to run AI workloads.
QA Hardened Software that Just Works
Don’t be Someone Else’s QA Tester - Avoid Downtime and Lost Cycles
- Software Built for DGX; OS image and NGC software tuned for DGX-specific config vs generic images loaded on generic hardware
- Better over Time; On-going improvements and enhancements from NVIDIA’s engineering team – continuously delivered to DGX customers
- Peace of Mind; With DIY servers, one small change in the stack – be it updates in OS, device drivers, libraries, etc. – can drastically impact performance, and thus productivity
Lost data science cycles due to downtime = lost revenue for an AI enterprise. Our decade plus AI leadership ensures your AI projects stay up and running and your data scientists remain productive
DIY and non-DGX solutions result in AI deployments that are complex and time consuming to build, test and maintain. The software engineering work requires a high level of expertise to manage driver, library, framework dependencies, it also requires you to be constantly up to date as the development of software frameworks by the community is moving very fast. This results in lost productivity of your data science team.
Reference Architecture Speed Deployment
Not Just Whitepapers: Field Proven Performance Built Using Names You Trust
- Expertise Building AI Infrastructure; We’ve been building scaled AI infrastructure since 2016 – DGX POD puts our experience into action
- Thoroughly Tested; Not just paperwork, not a snowflake design: every DGX RA tested at full-scale, in our proving ground
- Turnkey Scalable AI Infrastructure; DGX SuperPOD Solution delivers our best scaled infrastructure in a turnkey solution with life-cycle services
Operations; Enterprise support for the entire stack vs. chasing 5 vendors + open source forums for answers
Every DGX POD reference architecture has been tested in our NVIDIA RAPLab, to ensure consistent results that customers can trust. Any vendor can write a whitepaper on how to scale, no one proves it in practice like NVIDIA DGX does, before the paper is even written.
This is a valuable suite of expertise and insight that all of our customers benefit from. For enterprises that need the fastest path to AI-innovation at scale, we’ve taken our industry-leading reference architecture, and wrapped it in a full-circle solution and services offering with our NVIDIA DGX SuperPOD Solution for Enterprise, so everyone can have the “SuperPOD” experience.
More than a box: AI platform that’s ready-to-go
From NGC to DGX-Ready Software Ecosystem – Everything You Need to Build AI Now
- Infrastructure solutions that fit you; Broad range of options, from -aaS to leasing to colocation, that makes it easier to deploy AI
- More than a Point Product; Whole solutions that are interoperable, for every stage of the AI workflow
- Industrialized AI Workflow; MLOps software from leading names, certified on DGX systems
3rd party software and open source on a commodity server ≠ enterprise AI platform. Instead of worrying about configuring and tooling, ensure your data scientists can focus on data analysis.
- Runs Best on DGX; NGC containers already tested on DGX, optimized to run best on DGX. Unlike others, NGC support comes with every DGX
- Get Results Sooner; Pre-trained models, scripts and more = better results, sooner vs chasing forums
- Always the Best Performance; Monthly deep learning framework updates and stack optimizations deliver better performance on the same hardware
Instead of using 3rd party software and open source on a commodity server, run your AI projects on the exact same platform NVIDIA engineers use to develop and test optimized AI software, one that is always optimized for the best performance. This way, your data scientists can focus on data analysis instead of configuring and tooling.
Full-stack AI expertise – in one place
NVIDIA Professional Services = Up and Running vs. Vendor Run-Around and Open-Source Forums
- NVIDIA Backed; Even ”supported systems” might not be backed by people who know AI intimately – ours do
- Single Point of Contact; From framework to libraries to drivers to network, storage and compute – we’re one stop for answers and uptime
- Fastest Path to Resolution; Commodity server = commodity support: AI problems take the longer path to an NVIDIA expert
- Insider Access; Get DGX customer exclusive sessions taught by experts in the field
- Direct Relationship with DGXperts; NVIDIA Enterprise Support gets you a DGXpert who can offer valuable advice now, not later.
With NVIDIA DGX systems, you get direct access to NVIDIA’s own AI practitioners who have extensive experience gained from customer deployments around the globe. These are people who understand AI as part of their DNA. Our DGXperts have access to tools and infrastructure, hat is impossible for others to replicate .