Supporting research at every stage
Start or scale up your Deep Learning project with Lambda Cloud. Get started quickly, save on compute costs, and easily scale to hundreds of GPUs.
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Start training models right away
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Major frameworks preinstalled
Every VM comes preinstalled with the latest version of Lambda Stack — which includes major deep learning frameworks and CUDA® drivers.
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Jupyter notebooks
In seconds, access a dedicated Jupyter Notebook development environment for each machine directly from the cloud dashboard.
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Direct SSH access
For direct access, connect via the Web Terminal in the dashboard or use SSH directly with one of your provided SSH keys.
Spend less
Lower compute costs, without commitments
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Save up to 50% on compute costs
By building compute infrastructure at scale for the unique requirements of deep learning researchers, Lambda can pass on significant savings.
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Reduce cloud TCO
Benefit from the flexibility of using cloud computing without paying a fortune in on-demand pricing when workloads rapidly increase.
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No multi-year commitments
We provide on-demand pricing at or below typical one year commitment pricing — you benefit from lower costs without lock-in to a specific instance type.
Scale up
Seamlessly scale GPU compute infrastructure
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Multi-node distributed training
Instances support up to 10 Gbps of inter-node bandwidth to enable distributed training with Horovod or another framework.
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Hyper-parameter optimization
Reduce model optimization times by scaling across large numbers of GPUs on one or more instances.
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Growing research teams
Supplement oversubscribed or underpowered compute resources with dedicated instances for new team members.