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本地安装在宿主机/虚拟机安装TensorFusion架构

应用操作

创建AI应用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

对比

与NVIDIA vGPU比较与MIG/MPS对比与趋动科技对比与 Run.AI 对比与HAMi的对比

QoS级别与计价

配置QoS级别和多租户应用级内部计价

配置QoS级别的调度优先级

🚧 Under Construction

配置GPU租用单价信息

kubectl edit configmap tensor-fusion-sys-public-gpu-info -n tensor-fusion-sys
# Refer:
#  - https://www.techpowerup.com/gpu-specs
#  - https://getdeploying.com/reference/cloud-gpu

# Field Definition:
# - 'model' is `GPUModel_BoardSlotType` to identify the GPU
# - 'costPerHour' is the average cost referring a few Cloud/Serverless GPU vendors
# - 'fp16TFlops' is the max FP16 TFLOPs of the GPU. For NVIDIA, it means none-sparsity performance and using Tensor Cores

# note that this sheet only contains TFLOPs, no VRAM, since variant GPUs have the same TFLOPs but different VRAM, VRAM can be easily detected from NVML lib
# TODO: this should be dynamic after user inputs their cloud vendor and discounts info, for example Azure/AWS has much higher price than this sheet

# Turing Architecture Series
- model: T4
  fullModelName: "Tesla T4"
  vendor: NVIDIA
  costPerHour: 0.53
  fp16TFlops: 65

生产级部署指南

部署生产环境,具有高可用性、可观测性、可灰度、可回滚、高性能

云厂商集成(BYOC)

配置云厂商集成的GPU池,自动管理GPU节点

目录

配置QoS级别的调度优先级
配置GPU租用单价信息