Dataoorts GPU Cloud Integrations

Better security. More packages. Newer tools. All your open source, from cloud to edge. Secure your open source apps. Patch the full stack, from kernel to library and applications, for CVE compliance. Governments and auditors certify Ubuntu for FedRAMP, FISMA and HITECH. Rethink what’s possible with Linux and open source. Companies engage Canonical to drive down open source operating costs. Automate everything: multi-cloud operations, bare metal provisioning, edge clusters and IoT. Whether you’re a mobile app developer, an engineering manager, a music or video editor or a financial analyst with large-scale models to run — in fact, anyone in need of a powerful machine for your work — Ubuntu is the ideal platform. Ubuntu is used by thousands of development teams around the world because of its versatility, reliability, constantly updated features, and extensive developer libraries.

Docker takes away repetitive, mundane configuration tasks and is used throughout the development lifecycle for fast, easy and portable application development, desktop and cloud. Docker’s comprehensive end-to-end platform includes UIs, CLIs, APIs and security that are engineered to work together across the entire application delivery lifecycle. Get a head start on your coding by leveraging Docker images to efficiently develop your own unique applications on Windows and Mac. Create your multi-container application using Docker Compose. Integrate with your favorite tools throughout your development pipeline, Docker works with all development tools you use including VS Code, CircleCI and GitHub. Package applications as portable container images to run in any environment consistently from on-premises Kubernetes to AWS ECS, Azure ACI, Google GKE and more. Leverage Docker Trusted Content, including Docker Official Images and images from Docker Verified Publishers.

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.

AI/ML API is a game-changing platform for developers and SaaS entrepreneurs looking to integrate cutting-edge AI capabilities into their products. It offers a single point of access to over 200 state-of-the-art AI models, covering everything from NLP to computer vision. Key Features for Developers: Extensive Model Library: 200+ pre-trained models for rapid prototyping and deployment Developer-Friendly Integration: RESTful APIs and SDKs for seamless incorporation into your stack Serverless Architecture: Focus on coding, not infrastructure management Advantages for SaaS Entrepreneurs: Rapid Time-to-Market: Leverage advanced AI without building from scratch Scalability: From MVP to enterprise-grade solutions, AI/ML API grows with your business Cost-Efficiency: Pay-as-you-go pricing model reduces upfront investment Competitive Edge: Stay ahead with continuously updated AI models

Declare AWS Lambda functions and their triggers through simple abstract syntax in YAML. AWS Lambda functions, triggers & code will be deployed and wired together in the cloud, automatically. Install thousands of Serverless Framework Plugins to build new serverless use-cases on AWS and integrate with other tools. Track usage, performance, errors on your serverless apps with instant, powerful metrics. See all of your serverless applications and their resources in one place, regardless of AWS account or region. Easily share secrets, outputs from your serverless applications and delegate AWS account access. You can deploy many familiar use-cases instantly with the Serverless Framework. From REST APIs on Node.js, Python, Go, Java, to GraphQL APIs, scheduled tasks, Express.js applications, and front-end applications.

TensorBoard is TensorFlow's comprehensive visualization toolkit designed to facilitate machine learning experimentation. It enables users to track and visualize metrics such as loss and accuracy, visualize the model graph (operations and layers), view histograms of weights, biases, or other tensors as they change over time, project embeddings to a lower-dimensional space, and display images, text, and audio data. Additionally, TensorBoard offers profiling capabilities to optimize TensorFlow programs. These features collectively provide a suite of tools to understand, debug, and optimize TensorFlow programs, enhancing the machine learning workflow. In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics, visualizing the model graph, and projecting embeddings to a lower dimensional space.

NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.

CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

Moody's Intelligent Risk Platform™ (IRP) is a cloud-native solution designed to enhance risk assessment and decision-making for insurers, reinsurers, and brokers. Leveraging over 30 years of risk analytics expertise, the platform integrates industry-leading Moody's RMS™ models to provide deep insights into various perils, including natural and man-made catastrophes. Its modular architecture offers a suite of applications—such as Risk Modeler™, UnderwriteIQ™, TreatyIQ™, and ExposureIQ™—that streamline workflows across the insurance value chain, from underwriting to portfolio management. Built on Amazon Web Services (AWS), the IRP ensures scalability, flexibility, and continuous innovation, with new features released every six weeks. Additionally, the platform supports over 700 third-party and in-house models through its Open Modeling Engine, facilitating unified multi-vendor risk modeling.

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Tensor's mission is to become the trading venue for the pro-NFT trader. We started Tensor become we ourselves were flipping NFTs daily and weren't satisfied with existing tooling. We wanted something faster, with better coverage, more data, and advanced order types, and so Tensor was born. When you go to Tensor you'll find a single coherent dApp, but under the hood, we actually have a few moving parts. Bonding-curve-based orders: linear & exponential, lets you DCA into/out of NFTs! Instant new collection listings (we appreciate traders want to always trade the latest stuff). Earn trading fees & LP rewards by providing liquidity and creating markets for your favorite NFT collections on TensorSwap. Market-makers are important because they make markets more liquid, meaning they let other traders enter/exit the market at a more favorable price.

The software layer of the NVIDIA AI platform, NVIDIA AI Enterprise accelerates the data science pipeline and streamlines development and deployment of production AI including generative AI, computer vision, speech AI and more. With over 50 frameworks, pretrained models and development tools, NVIDIA AI Enterprise is designed to accelerate enterprises to the leading edge of AI, while also simplifying AI to make it accessible to every enterprise. The adoption of artificial intelligence and machine learning has gone mainstream, and is core to nearly every company’s competitive strategy. One of the toughest challenges for enterprises is the struggle with siloed infrastructure across the cloud and on-premises data centers. AI requires their environments to be managed as a common platform, instead of islands of compute.

Impacting virtually every industry, generative AI unlocks a new frontier of opportunities, for knowledge and creative workers, to solve today’s most important challenges. NVIDIA is powering generative AI through an impressive suite of cloud services, pre-trained foundation models, as well as cutting-edge frameworks, optimized inference engines, and APIs to bring intelligence to your enterprise applications. NVIDIA AI Foundations is a set of cloud services that advance enterprise-level generative AI and enable customization across use cases in areas such as text (NVIDIA NeMo™), visual content (NVIDIA Picasso), and biology (NVIDIA BioNeMo™). Unleash the full potential with NeMo, Picasso, and BioNeMo cloud services, powered by NVIDIA DGX™ Cloud, the AI supercomputer. Marketing copy, storyline creation, and global translation in many languages. For news, email, meeting minutes, and information synthesis.