Overview
CCE supports different types of resource scheduling and task scheduling, improving application performance and overall cluster resource utilization. This section describes the main functions of CPU resource scheduling, GPU/NPU heterogeneous resource scheduling, and Volcano scheduling.
CPU Scheduling
CCE provides CPU policies to allocate complete physical CPU cores to applications, improving application performance and reducing application scheduling latency.
Function |
Description |
Reference |
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CPU policy |
When many CPU-intensive pods are running on a node, workloads may be migrated to different CPU cores. Many workloads are not sensitive to this migration and thus work fine without any intervention. For CPU-sensitive applications, you can use the CPU policy provided by Kubernetes to allocate dedicated cores to applications, improving application performance and reducing application scheduling latency. |
GPU Scheduling
CCE schedules heterogeneous GPU resources in clusters and allows GPUs to be used in containers.
Function |
Description |
Reference |
---|---|---|
Default GPU scheduling in Kubernetes |
This function allows you to specify the number of GPUs that a pod requests. The value can be less than 1 so that multiple pods can share a GPU. |
NPU Scheduling
CCE schedules heterogeneous NPU resources in a cluster to quickly and efficiently perform inference and image recognition.
Function |
Description |
Reference |
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NPU scheduling |
NPU scheduling allows you to specify the number of NPUs that a pod requests to provide NPU resources for workloads. |
Volcano Scheduling
Volcano is a Kubernetes-based batch processing platform that supports machine learning, deep learning, bioinformatics, genomics, and other big data applications. It provides general-purpose, high-performance computing capabilities, such as job scheduling, heterogeneous chip management, and job running management.
Function |
Description |
Reference |
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NUMA affinity scheduling |
Volcano targets to lift the limitation to make scheduler NUMA topology aware so that:
|
Cloud Native Hybrid Deployment
The cloud native hybrid deployment solution focuses on the Volcano and Kubernetes ecosystems to help users improve resource utilization and efficiency and reduce costs.
Function |
Description |
Reference |
---|---|---|
Dynamic resource oversubscription |
Based on the types of online and offline jobs, Volcano scheduling is used to utilize the resources that are requested but not used in the cluster (that is, the difference between the number of requested resources and the number of used resources), implementing resource oversubscription and hybrid deployment and improving cluster resource utilization. |
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