Audience
Organizations in need of a powerful GPU cloud platform
About JarvisLabs.ai
We have set up all the infrastructure, computing, and software (Cuda, Frameworks) required for you to train and deploy your favorite deep-learning models. You can spin up GPU/CPU-powered instances directly from your browser or automate it through our Python API.
Pricing
Starting Price:
$1,440 per month
Company Information
JarvisLabs.ai
Founded: 2021
India
jarvislabs.ai/
NVIDIA GPU-Optimized AMI
The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit.
This AMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions.
This GPU-optimized AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'
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Vultr
Easily deploy cloud servers, bare metal, and storage worldwide! Our high performance compute instances are perfect for your web application or development environment. As soon as you click deploy, the Vultr cloud orchestration takes over and spins up your instance in your desired data center. Spin up a new instance with your preferred operating system or pre-installed application in just seconds. Enhance the capabilities of your cloud servers on demand. Automatic backups are extremely important for mission critical systems. Enable scheduled backups with just a few clicks from the customer portal. Our easy-to-use control panel and API let you spend more time coding and less time managing your infrastructure.
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GPUonCLOUD
Traditionally, deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling take days or weeks time. However, with GPUonCLOUD’s dedicated GPU servers, it's a matter of hours. You may want to opt for pre-configured systems or pre-built instances with GPUs featuring deep learning frameworks like TensorFlow, PyTorch, MXNet, TensorRT, libraries e.g. real-time computer vision library OpenCV, thereby accelerating your AI/ML model-building experience. Among the wide variety of GPUs available to us, some of the GPU servers are best fit for graphics workstations and multi-player accelerated gaming. Instant jumpstart frameworks increase the speed and agility of the AI/ML environment with effective and efficient environment lifecycle management.
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Brev.dev
Find, provision, and configure AI-ready cloud instances for dev, training, and deployment. Automatically install CUDA and Python, load the model, and SSH in. Use Brev.dev to find a GPU and get it configured to fine-tune or train your model. A single interface between AWS, GCP, and Lambda GPU cloud. Use credits when you have them. Pick an instance based on costs & availability. A CLI to automatically update your SSH config ensuring it's done securely. Build faster with a better dev environment. Brev connects to cloud providers to find you a GPU at the best price, configures it, and wraps SSH to connect your code editor to the remote machine. Change your instance, add or remove a GPU, add GB to your hard drive, etc. Set up your environment to make sure your code always runs, and make it easy to share or clone. You can create your own instance from scratch or use a template. The console should give you a couple of template options.
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Product Details
Platforms Supported
SaaS
Training
Documentation
Videos
Support
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