# Certified MLOps Software for NVIDIA DGX Systems Explore enterprise-grade solutions for workflow, cluster management, and scheduling and orchestration. ## Streamline AI Deployment and Workflows The NVIDIA DGX™-Ready Software program features enterprise-grade [MLOps](https://blogs.nvidia.com/blog/2020/09/03/what-is-mlops/) solutions that accelerate AI workflows and improve deployment, accessibility, and utilization of AI infrastructure. DGX-Ready Software is tested and certified for use on DGX systems, helping you get the most out of your AI platform investment. ## AI Infrastructure With MLOps MLOps solutions span AI workflow management applications, cluster management, pipeline orchestration, and resource scheduling to maximize efficiency and utilization of AI infrastructure. ## DGX-Ready Software Solutions Learn about our partners’ certified software solutions. * All * MLOps * Cluster Management and Orchestration * Scheduling ## **Get more out of your DGX Systems with MLOps** [Watch on Demand](https://www.nvidia.com/en-us/on-demand/playlist/playList-97299db0-3edc-456e-9abd-b8ddb4154fbd/) ### Weights & Biases Weights & Biases (W&B) is the developer stack for machine learning practitioners. Use their lightweight, interoperable tools for debugging and reproducing the entire lifecycle of your machine learning projects. W&B is trusted by over 150,000 machine learning practitioners developing better medicine, safer self-driving cars, more sustainable farming, and state-of-the-art research. Weight & Biases MLOps software is certified for use with NVIDIA DGX systems and is also available with [NVIDIA Base Command](https://www.nvidia.com/en-us/data-center/base-command.md). ### Contact [www.wandb.ai](http://wandb.ai/) ### Backend.AI Experience convenient and powerful AI development through Lablup Backend.AI and NVIDIA DGX systems. Backend.AI makes it hassle-free to take full advantage of the enormous computing power of NVIDIA accelerated computing, including DGX systems. ### Contact [www.backend.ai](https://www.backend.ai) ### Bright Computing Bright Computing software makes different possible. Quickly build and manage heterogeneous high-performance clusters that host HPC, machine learning, and analytics applications that span from core to edge to cloud. ### Contact [www.brightcomputing.com](https://www.brightcomputing.com/) ### ClearML ClearML provides a management and orchestration stack on top of DGX systems. With ClearML, teams can more easily manage their workloads, gain better visibility and control over their data and models, and collaborate effectively. Using ClearML Orchestrate, teams can leverage one or more NVIDIA DGX A100 system to create virtual clusters for both remote virtual development environments, as well as support scalable training workloads. ### Resources [Streamline Medical Imaging Workflows With NVIDIA DGX Station™ A100, NVIDIA Clara™ Imaging, and ClearML (Solution Brief)](https://images.nvidia.com/aem-dam/Solutions/Data-Center/nvidia-dgx-station-a100-clara-solution-brief.pdf) ### Contact [www.clear.ml (Allegro AI)](https://www.allegro.ai/lp/dgx-ready-dl-ml-platform/) ### Shakudo Shakudo's Hyperplane platform is an end-to-end environment for machine learning teams. Hyperplane combines the best open-source tools and frameworks into a single preconfigured and tuned platform that’s designed for the best developer experience. Shakudo’s approach is to provide a single UI and a continuously evolving multi-framework, multi-infrastructure backend that aligns to the prevailing machine learning stacks in the industry. It’s straightforward to get up and running with Hyperplane on NVIDIA DGX systems with full support for RAPIDS™, NVIDIA Triton™ Inference Server, NVIDIA Multi-Instance GPU (MIG), and other powerful NVIDIA technologies. Hyperplane covers the entire machine learning life cycle, from development and experimentations, through scaling and deployment of models and extract, transform, and load (ETL) jobs, to experiment tracking, monitoring, and real-time troubleshooting of production workloads. ### Contact ### Domino Data Lab The Domino Data Science Platform centralizes data science work and infrastructure across the enterprise for collaboratively building, training, deploying, and managing models—faster and more efficiently. With Domino, data scientists can innovate faster, teams can reuse work and collaborate more, and IT teams can manage and govern infrastructure. ### Resources [How Lockheed Martin Is Pushing the Boundaries of Rocket Science with Data Science (on-demand webinar)](https://go.dominodatalab.com/how-lockheed-martin-is-pushing-the-boundaries-of-rocket-science-with-data-science-video) ### Contact [www.dominodatalab.com](https://www.dominodatalab.com/partners/nvidia/) ### Determined AI Determined is an open-source deep learning training platform that makes building models fast and easy. Determined enables you to: * Train models faster using state-of-the-art distributed training, without changing your model code * Automatically find high-quality models with advanced hyperparameter tuning from the creators of Hyperband * Get more from your GPUs with smart scheduling, and cut cloud GPU costs by seamlessly using preemptible instances * Track and reproduce your work with experiment tracking that works out of the box, covering code versions, metrics, checkpoints, and hyperparameters ### Contact [www.determined.ai](https://www.determined.ai/nvidia-dgx-ready-partner) ### Iguazio The Iguazio Data Science Platform transforms AI projects into real-world business outcomes. Accelerate and scale development, deployment, and management of your AI applications with MLOps and end-to-end automation of machine learning pipelines. ### Contact [www.iguazio.com/](https://www.iguazio.com/) ### Paperspace Paperspace Gradient accelerates and scales the development and deployment of production-ready machine learning and deep learning models. The platform runs on the industry's first comprehensive continuous integration and continuous deployment (CI/CD) engine for building, training, and deploying deep learning models. Paperspace's best-in-class machine learning tooling and methodology supports multi-cloud, on-premises, and hybrid environments for today's modern enterprises. It also works with NVIDIA NGC and is optimized for NVIDIA DGX systems. ### Contact [www.paperspace.com](https://www.paperspace.com/) ### Red Hat OpenShift Red Hat OpenShift is the hybrid cloud platform of open possibility: powerful, so you can build anything, and flexible, so it works anywhere. With OpenShift as part of the DGX-Ready Software program, customers have access to proven, tested, enterprise-grade software solutions certified with OpenShift on clusters of NVIDIA DGX systems. This can help simplify the deployment, management, and scaling of AI infrastructure, while ecosystem partners can tap OpenShift to develop and deliver solutions to customers in a more scalable and repeatable way. ### Contact [www.openshift.com](https://www.openshift.com/learn/partners/nvidia) ### Pachyderm Pachyderm provides the data layer that allows machine learning (ML) teams to productionize and scale their machine learning lifecycle. Certified for use with NVIDIA DGX™ systems, Pachyderm’s industry-leading data versioning gives pipelines and lineage teams data-driven automation, petabyte scalability, and end-to-end reproducibility. Teams using Pachyderm get their ML projects to market faster, lower data processing and storage costs, and can more easily meet regulatory compliance requirements. ### Contact ### D2iQ D2iQ Kaptain is an enterprise-ready, end-to-end machine learning (ML) platform, powered by Kubeflow, that accelerates time-to-market and positive ROI by breaking down the barriers between ML prototypes and production. D2iQ Kaptain enables organizations to develop and deploy ML workloads, at scale, in hybrid and cloud environments. D2iQ Konvoy is a comprehensive Kubernetes distribution that enables companies to leverage Kubernetes with an easy, out-of-the-box, enterprise-grade experience. Konvoy is built on pure upstream open source software with the add-ons needed for Day 2 production selected, integrated, and tested at scale, for hybrid and cloud environments. ### Resources [D2iQ Kubernetes Platform and NVIDIA DGX systems (Solution Brief)](https://images.nvidia.com/aem-dam/Solutions/Data-Center/d2iq-nvidia-solution-brief.pdf) ### Contact ### Run:AI Run:AI has built the world’s first compute-management platform for orchestrating and accelerating AI. By centralizing and virtualizing GPU compute resources, Run:AI provides visibility and control over resource prioritization and allocation while simplifying workflows and removing infrastructure hassles for data scientists. This ensures AI projects are mapped to business goals and yields significant improvement in the productivity of data science teams, allowing them to build and train concurrent models without resource limitations. ### Resources [Building the Best AI Infrastructure Stack to Accelerate Your Data Science (on-demand webinar)](https://www.youtube.com/watch?v=I3TNGcSSgLY) ### Contact [www.run.ai](https://www.run.ai/platform/run-ai-accelerate-nvidia-dgx-systems/) ### Shakudo Shakudo's Hyperplane platform is an end-to-end environment for machine learning teams. Hyperplane combines the best open-source tools and frameworks into a single preconfigured and tuned platform that’s designed for the best developer experience. Shakudo’s approach is to provide a single UI and a continuously evolving multi-framework, multi-infrastructure backend that aligns to the prevailing machine learning stacks in the industry. It’s straightforward to get up and running with Hyperplane on NVIDIA DGX systems with full support for RAPIDS™, NVIDIA Triton™ Inference Server, NVIDIA Multi-Instance GPU (MIG), and other powerful NVIDIA technologies. Hyperplane covers the entire machine learning life cycle, from development and experimentations, through scaling and deployment of models and extract, transform, and load (ETL) jobs, to experiment tracking, monitoring, and real-time troubleshooting of production workloads. ### Contact [https://shakudo.io](https://shakudo.io/dgx) ### Canonical Ubuntu Canonical’s Ubuntu is an optimized platform for NVIDIA DGX, NVIDIA NGC™ containers, and more that enables data scientists and engineers to innovate more productively. Canonical Kubernetes builds on optimized Ubuntu images and provides unparalleled integrations and operations for any compute environment. Additionally, for crafting their AI solutions and scaling their projects, Canonical Kubeflow, an end-to-end MLOps platform, can be added to the stack and run on NVIDIA DGX systems. ### Resources [Solution Brief: Charmed Kubernetes Delivered on NVIDIA DGX Systems Solution Brief](https://ubuntu.com/engage/kubernetes-by-canonical-delivered-on-nvidia-dgx-systems) [Solution Brief: Charmed Kubeflow Delivered on NVIDIA DGX Systems](https://pages.ubuntu.com/rs/066-EOV-335/images/NVIDIA_DGX_Kubeflow_solution_06_03_23.pdf) [Whitepaper: Build Your Performant ML Stack with NVIDIA DGX and Kubeflow](https://ubuntu.com/engage/run-ai-at-scale) ### Contact ### IBM Spectrum LSF The IBM Spectrum® LSF® Suites portfolio, a complete workload management solution for demanding distributed computing environments, helps increase user productivity and hardware utilization, while decreasing management costs. LSF Suites provide support for classical high performance computing (HPC), big data, GPUs, machine learning (ML) and AI, and containerized workloads on-premises and in the cloud. Dynamic hybrid cloud bursting and intelligent data staging help organizations control costs by enabling them to pay for only what they use. ### Resources [Using IBM Spectrum with NVIDIA DGX Systems](https://community.ibm.com/community/user/businessanalytics/viewdocument/ibm-spectrum-lsf-with-nvidia-dgx-sy-1?CommunityKey=74d589b7-7276-4d70-acf5-0fc26430c6c0&tab=librarydocuments) ### Contact ### SchedMD SchedMD is the core developer and services provider for Slurm, providing support, consulting, configuration, development, and training services to cloud and on-premises clusters. Slurm is the market-leading open source workload manager designed for the most complex and demanding HPC, high throughput computing (HTC), and AI systems. Slurm maximizes workload throughput and reliability, while optimizing consumption and managing workloads across cloud and on-premises clusters. Slurm provides key scheduling to NVIDIA GPUs: * Manages GPUs similar to CPUs with flexible control for requesting GPUs and binding tasks to the GPU (GPU=first-class resource) * Supports NVIDIA Multi-Instance GPU (MIG) * Auto detect GPU resources * Constrain workloads to only the specific allocated GPUs disallowing processes from using more than requested * Sets CUDA\_VISIBLE\_DEVICES environment variable allowing the job to know the allocated GPU ### Resources [Accelerating High Performance and AI Workloads with Slurm and NVIDIA DGX Systems](https://schedmd.com/downloads/extras/NVIDIA%20DGX%20with%20Slurm%20+%20SchedMD_HPC%20AI%20Solution.pdf) ### Contact [www.schedmd.com/](https://www.schedmd.com/) ### Altair Altair’s flagship workload management and job scheduling solution, [Altair® PBS Professional®,](https://www.altair.com/pbs-professional/) is optimized for performance in GPU environments, including NVIDIA DGX systems. PBS Professional includes support for scheduling large AI and high performance computing (HPC) workloads on multi-node DGX clusters, as well as individual GPU workloads utilizing Multi-Instance GPU (MIG). ### Resources [Altair PBS Professional Support for NVIDIA DGX Systems](https://www.altair.com/resource/altair-pbs-professional-support-for-nvidia-dgx-systems) ### Contact [www.altair.com/pbs-professional/](https://www.altair.com/pbs-professional/) ### SUSE From the data center to cloud to edge, SUSE’s Rancher Kubernetes Management solution provides a complete stack that eases the operational and security challenges of managing multiple container clusters. With Rancher, developers can quickly integrate and leverage the best of NVIDIA software and infrastructure in their Kubernetes environments, so they can focus on AI tasks. ### Resources [NVIDIA DGX Testing and Deployment Guide](https://links.imagerelay.com/cdn/3404/ql/174982dae37a4c42adaa4047445fc392/NVIDIA-DGX-Testing-and-Deployment-Guide.pdf) [Rancher Kubernetes Management Solution](https://ranchermanager.docs.rancher.com/) [Foundational Kubernetes and Rancher Training](https://www.rancher.academy/) ### Contact [Contact SUSE](https://www.suse.com/solutions/enterprise-container-management/) ### Dataiku Dataiku is the platform for everyday AI, helping data experts and domain experts work together to build AI into their daily operations. Together, they design, develop, and deploy new AI capabilities at all scales and in all industries. Organizations that use Dataiku enable their people to be extraordinary, creating the AI that will power their company into the future. More than 500 companies worldwide use Dataiku, driving diverse use cases, from predictive maintenance and supply chain optimization, to quality control in precision engineering, to marketing optimization, and everything in between. ### Contact [www.dataiku.com](https://www.dataiku.com) ## Contact Us To Learn More About DGX Welcome back. Not you? Log Out Welcome back. Not you? Clear form