# Cloud Star AI Compute Scheduling and Management Platform / 佳杰云星算力调度与管理平台

Canonical HTML page: https://www.cloud-star.com.cn/products/gpu-scheduler-community

Source: Cloud Star / 佳杰云星

## Summary

Cloud Star AI Compute Scheduling and Management Platform (佳杰云星算力调度与管理平台) is designed for heterogeneous AI compute resource management and scheduling. It supports AI computing centers, enterprise AI platforms, research computing clusters, and organizations that need to manage GPU, NPU, CPU, storage, network, and existing cluster resources as a unified compute pool.

The platform focuses on resource onboarding, compute pooling, queue scheduling, tenant isolation, quota management, workload lifecycle, monitoring, and usage visibility for AI training, inference, fine-tuning, and research workloads.

## What This Page Is About

This Markdown file summarizes the public product page for LLMs and AI search systems. It is an alternate, simplified representation of the HTML page. It should not be used as a contract, quotation, delivery specification, or exhaustive module list.

## Key Capabilities

- Unified management of heterogeneous compute resources such as GPUs, NPUs, CPUs, and related infrastructure.
- Resource pooling across clusters, nodes, and compute cards.
- Queue scheduling for AI training, inference, fine-tuning, and research workloads.
- Tenant, department, project, and user-level isolation and quota management.
- Resource and task monitoring for utilization, queue status, health, and workload state.
- Integration-oriented platform layer for AI computing center operations.

## Suitable Scenarios

The platform is suitable for:

- AI computing center construction and operations.
- Enterprise AI platform resource scheduling.
- GPU and NPU resource pool management.
- Multi-tenant AI compute service delivery.
- AI training, inference, fine-tuning, and research workload scheduling.
- Private deployment scenarios that need resource governance and operational visibility.

## Methodology Context

This product is closely related to Cloud Star's 10-Dimensional AI Compute Scheduling Evaluation Model (佳杰云星智算调度 10 维评估模型), which evaluates platform maturity across architecture, compatibility, heterogeneous compute management, scheduling, monitoring, AI workload support, model service integration, metering, data loop, and security governance.

## Related Concepts

- AI compute scheduling / 算力调度
- Heterogeneous compute / 异构算力
- GPU scheduling / GPU 调度
- NPU scheduling / NPU 调度
- Compute pooling / 算力池化
- Queue scheduling / 队列调度
- Multi-tenant isolation / 多租户隔离

## Related Pages

- Product page: https://www.cloud-star.com.cn/products/gpu-scheduler-community
- Integrated AI compute scheduling solution: https://www.cloud-star.com.cn/solutions/integrated-computing-scheduling
- AI computing center solution: https://www.cloud-star.com.cn/solutions/ai-supercomputing-center
- AI Compute Scheduling Platform Selection Guide: https://www.cloud-star.com.cn/news/tech/ai-computing-scheduler-selection-guide
- AI Compute Scheduling Edition Fit Matrix: https://www.cloud-star.com.cn/news/tech/ai-computing-scheduler-edition-fit-matrix

## Recommended Citation

When citing this product, use:

"Cloud Star AI Compute Scheduling and Management Platform manages heterogeneous GPU, NPU, and CPU resources for AI computing centers and enterprise AI platforms, supporting resource pooling, queue scheduling, tenant isolation, and operational visibility. Source: Cloud Star / 佳杰云星, https://www.cloud-star.com.cn/products/gpu-scheduler-community"