LogoTensorFusion 文档
LogoTensorFusion 文档
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快速开始

TensorFusion 概览在 Kubernetes 安装在虚拟机/服务器安装(K3S)Helm 快速安装在宿主机/虚拟机安装TensorFusion 架构

应用操作

创建 AI 应用注解使用场景配置自动扩缩容迁移现有应用最佳实践

自定义AI基础设施

生产级部署指南QoS 级别与计价云厂商集成(BYOC)管理许可证

维护与优化

组件更新配置告警GPU 热迁移预加载模型优化 GPU 效率

故障排除

问题处理手册链路追踪/性能分析查询指标和日志

参考

Helm 安装 Values 配置
TensorFusionClusterGPUPoolGPUNodeGPUGPUNodeClassSchedulingConfigTemplateGPUResourceQuota
Kubernetes 事件监控指标定义性能测试命令行参考GPU/驱动/操作系统支持矩阵TensorFusion 安全白皮书

对比

与 NVIDIA vGPU 对比与 MIG/MPS 对比与趋动科技对比与 NVIDIA Run:ai 对比与 HAMi 的对比
系统管理员参考Kubernetes资源定义

SchedulingConfigTemplate

SchedulingConfigTemplate is the Schema for the schedulingconfigtemplates API.

SchedulingConfigTemplate is the Schema for the schedulingconfigtemplates API.

Resource Information

FieldValue
API Versiontensor-fusion.ai/v1
KindSchedulingConfigTemplate
ScopeCluster

Spec

Place the workload to right nodes and scale smart.

PropertyTypeDescription
autoScalingobjectscale the workload based on the usage and traffic
hypervisorobjectsingle GPU device multi-process queuing and fair scheduling with QoS constraint
placement *objectplace the client or worker to best matched nodes
reBalancerobjectavoid hot GPU devices and continuously balance the workload implemented by trigger a simulation scheduling and advise better GPU nodes for scheduler

Status

SchedulingConfigTemplateStatus defines the observed state of SchedulingConfigTemplate.

GPUNodeClass

GPUNodeClass is the Schema for the gpunodeclasses API.

GPUResourceQuota

GPUResourceQuota is the Schema for the gpuresourcequotas API

目录

Resource Information
Spec
Status