加载中
正在获取最新内容,请稍候...
正在获取最新内容,请稍候...
Volcano is a Cloud Native Batch System built on Kubernetes, providing a powerful and flexible platform for running high-performance workloads like AI/ML, HPC, and genomics. It extends Kubernetes to support job-centric features such as gang scheduling, fair-share scheduling, and resource management.
Volcano is the first cloud-native batch system building upon Kubernetes. It aims to provide a unified platform for managing all types of compute-intensive workloads, including High-Performance Computing (HPC), Artificial Intelligence (AI), Machine Learning (ML), and data processing.
Standard Kubernetes is primarily designed for long-running services. Running batch jobs, HPC tasks, and AI/ML training that require specific scheduling semantics (like gang scheduling) and efficient resource sharing can be challenging. Volcano addresses these gaps by providing a specialized scheduler and controllers optimized for these types of workloads.
Ensures all tasks within a job start or terminate together, preventing deadlocks and improving resource utilization for tightly coupled workloads.
Provides advanced job queuing, prioritization, and resource fairness policies across different tenants and applications.
Manages heterogeneous resources like GPUs and FPGAs effectively for compute-intensive tasks.
Volcano is designed to efficiently handle a wide range of batch and high-performance workloads, including but not limited to:
Running distributed training jobs for deep learning models across multiple GPUs, ensuring efficient resource allocation and gang scheduling.
Accelerate AI/ML development cycles by efficiently utilizing shared GPU clusters.
Managing and scheduling complex pipelines for genomic data processing, simulations, and other scientific computing tasks.
Enable researchers to run demanding computational tasks on scalable Kubernetes infrastructure.
Handling large volumes of data processing tasks (like Spark, Flink) or CI/CD pipelines that require batch execution and specific resource guarantees.
Improve efficiency and resource utilization for data processing and automated build/test jobs.
You might be interested in these projects
tinygrad is a revolutionary neural network library designed for simplicity and minimalism. Inspired by PyTorch and Micrograd, it aims to provide a clear, concise framework for deep learning research and development, making complex concepts accessible.
Bruno is a Fast and Open Source API client, designed as a lightweight alternative to tools like Postman and Insomnia. It helps developers explore, test, and document APIs efficiently with a unique text-based collection format.
Pluvia is a lightweight unofficial Steam client for Android, offering essential features like chat, library browsing, and store access with optimized performance for mobile devices.