The AI development platform ClearML is making it even easier for companies with multiple teams working on AI solutions to get the infrastructure they need. GPU-as-a-Service provides access to large on-premise or cloud computing clusters that are multi-tenant so that multiple teams can work off them.
ClearML tracks compute consumption, data storage, API calls, and other chargeable metrics so that companies can better keep track of where their money is going when investing in AI.
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GPU-as-a-Service also provides visibility and control over who has accessed and used resources, which enables IT teams to create control budgets and ensure compliance with data security requirements.
It follows a hardware-agnostic approach, allowing companies to combine their existing GPU and HPC computing clusters with the ones acquired via this service. Additionally, it supports hybrid infrastructures by allowing the control plane and compute resources to be either in the cloud or on-prem.
“Our flexible, scalable multi-tenant GPUaaS solution is designed to make shared computing a working reality for any large organization,” said Moses Guttmann, co-founder and CEO of ClearML. “By increasing AI throughput for AI model and large language model (LLM) deployment, we’re helping our clients achieve a frictionless, unified experience and faster time-to-value on their investments in a completely secure manner.”
