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 |
Documentation |
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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 |
Documentation |
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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 |
Documentation |
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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 |
Documentation |
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Scheduling workloads |
Kubernetes typically uses its default scheduler to schedule workloads. To use Volcano, specify Volcano for your workloads. |
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Resource utilization-based scheduling |
Scheduling policies are optimized for computing resources to effectively reduce resource fragments on each node and maximize computing resource utilization. |
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Priority-based scheduling |
Scheduling policies are customized based on service importance and priorities to guarantee the resources of key services. |
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AI performance-based scheduling |
Scheduling policies are configured based on the nature and resource usage of AI tasks to increase the throughput of cluster services and improve service performance. |
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NUMA affinity scheduling |
Volcano targets to lift the limitation to make scheduler NUMA topology aware so that:
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