Google Cloud has announced the rebranding of its Cloud HPC Toolkit to Cluster Toolkit, expanding its scope to encompass AI/ML workloads. This toolkit aims to simplify the creation and management of high-performance computing environments on Google Cloud.
This change reflects the widespread adoption of Cluster Toolkit across various domains, from scientific and technical computing to AI/ML applications.
By streamlining cluster setup and deployment, Cluster Toolkit empowers users to focus on their workloads rather than infrastructure management. It also offers flexibility for diverse computing tasks by supporting multiple schedulers like Slurm, GKE, and Batch.
Key benefits of Cluster Toolkit include:
* Easy deployment and management of clusters
* Quickstart options for HPC and AI/ML workloads
* Integration of Google Cloud best practices
* Regular updates and new features
* Open-source accessibility
Some of the new features in Cluster Toolkit include:
* A3 Mega Blueprint: For deploying a cluster of A3 Mega VMs ready for training large language models (LLMs) and other AI/ML workloads.
* HPC VM Image: A VM image pre-installed with popular HPC tools and libraries.
* Slurm-gcp v6: The latest version of the Slurm-gcp solution, which provides a seamless experience for running Slurm workloads on Google Cloud.
It is highly recommended to update local clones and command names to avoid any confusion.
To get started with Cluster Toolkit, select one of their easy-to-use HPC and AI/ML blueprints, available through their GitHub repo, and use it to set up a cluster. They also offer a variety of resources to help you get started, including documentation, quickstarts, and videos.
