Convert domain specific jobs to k8s workloads and Schedules the jobs in batches for optimal performance.
Co-scheduling, Fair-Share, Gang scheduling, Topologies, Reserve/BackFill, Data ware Scheduling
Manages jobs with multiple template……
Singularity and GPU Accelerators
Logging, Metric & Dashboard
Volcano is system for runnning high performance workloads on Kubernetes. It provides a suite of mechanisms currently missing from Kubernetes that are commonly required by many classes of high performance workload including:
These types of applications typically run on generalized domain frameworks like Tensorflow, Spark, PyTorch, MPI, etc, which Volcano integrates with.
Volcano builds upon a decade and a half of experience running a wide variety of high performance workloads at scale using several systems and platforms, combined with best-of-breed ideas and practices from the open source community.
Are you planning to Deploy any of the below workloads on Kubernetes? If Yes then Volcano is the right choice for your Deployment framework.
The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures.
Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis.It also supports a rich set of higher-level tools including Spark SQL, MLlib, GraphX and Spark Streaming.
KubeGene is dedicated to making genome sequencing process simple, portable and scalable. It provides a complete solution for genome sequencing on the kubernetes and supports mainstream biological genome sequencing scenarios such as DNA, RNA, and liquid biopsy.