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Volcano v1.12.0 Available Now

· 19 min read

Volcano v1.12 released: Advancing Cloud-Native AI and Batch Computing

As AI large model technology rapidly evolves, enterprises are placing higher demands on computing resource efficiency and application performance. For complex application scenarios such as AI, big data, and high-performance computing (HPC), efficiently utilizing accelerators like GPUs, ensuring high system availability, and managing resources with fine granularity are the core areas of focus for the Volcano community's continuous innovation.

Volcano v1.11.0 Available Now

· 19 min read

As the de facto standard in cloud-native batch computing, Volcano has been widely adopted across various scenarios, including AI, Big Data, and High-Performance Computing (HPC). With over 800 contributors from more than 30 countries and tens of thousands of code commits, Volcano has been deployed in production environments by over 60 enterprises worldwide. It provides the industry with excellent practical standards and solutions for cloud native batch computing.

Volcano 1.7.0 Available Now

· 6 min read

Volcano 1.7.0 is now available with the following new features:

  • enhanced plugin for PyTorch Jobs
  • Ray on Volcano
  • enhanced scheduling for general Kubernetes services
  • multi-architecture images of Volcano
  • optimized queue status info

volcano_logo.png

Volcano is the industry-first cloud native batch computing project. Open-sourced at KubeCon Shanghai in June 2019, it became an official CNCF project in April 2020. In April 2022, Volcano was promoted to a CNCF incubating project. By now, more than 490 global developers have committed code to the project. The community is seeing growing popularity among developers, partners, and users.

Volcano v1.4 (Beta) Release Note

· 3 min read

This article was firstly released at Container Cube on September 6th, 2021, refer to Volcano v1.4.0-Beta发布,支持NUMA-Aware等多个重要特性

Volcano, CNCF's first batch computing project, is now available with a new version, v1.4 (Beta). This version includes multiple important features, such as resource ratio-based partitions on GPU nodes, NUMA-aware, mixed deployment of multiple schedulers, and greatly improved stability.