Getting started with GPUs
Tutorials
Learn how you can use popular GPU-based applications on Cudo Compute.
TensorFlow
TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.
Learn how you can deploy your TensorFlow projects to the latest Nvidia Ampere architecture GPUs on Cudo Compute.
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PyTorch
PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab (FAIR).
Learn how you can deploy your PyTorch projects to the latest Nvidia Ampere architecture GPUs on Cudo Compute.
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Parabricks
NVIDIA Clara™ Parabricks® is a GPU-accelerated computational genomics toolkit that delivers fast and accurate analysis for sequencing centers, clinical teams, genomics researchers, and next-generation sequencing instrument developers.
Learn how you can get started with Parabricks on Cudo Compute.
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GROMACS
GROMACS is a molecular dynamics package mainly designed for simulations of proteins, lipids, and nucleic acids. It wasoriginally developed in the Biophysical Chemistry department of University of Groningen, and is now maintained by contributors in universities and research centers worldwide.
Learn how you can get started with GROMACS on Cudo Compute.
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Blender
Blender is the free and open source 3D creation suite. It supports the entirety of the 3D pipeline—modeling, rigging, animation, simulation, rendering, compositing and motion tracking, even video editing and game creation.
Learn how to deploy your Blender projects on Cudo Compute.
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GPU cloud
Cudo Compute gives you access to on-demand GPU instances with per-second billing. Cudo is dedicated to providing the best user experience, whether it is via the web console, our command line tool or our terraform provider. All this with servers hosted in data centers with ISO 27001 security and ISO 9001 quality certifications.
When you launch an instance, the GPUs are connected directly via PCI passthrough so you can get the full performance. Cudo offers NVIDIA A6000 (48GB), A5000 (24GB), and A4000 (16GB) GPUs providing a range of options to cover your workload at the lowest possible cost to you. Additionally, the NVIDIA GPUs are paired with AMD EPYC CPUs for blazing performance.
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Why Cudo Compute for GPUs?
Whether your field is data science, deep learning, rendering or high-performance computing on GPU, getting started is simple. Launch your instance and pull a docker container with an NVIDIA optimised distribution of your application. See our tutorials for more information.
Instances are powered by KVM virtualization and offer NVIDIA’s latest generation Ampere architecture with up to 48 GB of VRAM and tensor cores for up to an order of magnitude improvement in performance with machine learning workloads. Visit our marketplace to see prices and deploy an instance.
Learn more about GPU cloud