使用Karpenter通过时间切片管理GPU节点

深度学习
Amazon EKS Anywhere
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0
{"value":"\n在机器学习领域,我们经常使用 GPU 来加速计算工作负载。但现在的企业和开发者都更热衷于“上云”。有了云计算,使用云服务,用多少付多少,也就能降低运营成本了。\n\n当你拥有数十个在不同时间段需要用到 GPU 的应用程序时,怎么以更低成本,怎么更灵活地在云服务器中调度资源,就会变成一件非常重要的事情。 \n\n==作者介绍==\n== [Jina AI](jina.ai) 云架构研发工程师陶然\n🔗 原文链接:[https://jina.ai/news/time-slicing-gpus-with-karpenter/](https://jina.ai/news/time-slicing-gpus-with-karpenter/)\n\n## 问题\n那么,如何优化云服务中 GPU 的使用成本呢?在使用虚拟机时,哪怕你不需要全天候的服务,你也必须持续为所有的设备付费。相比于虚拟机,容器拥有更高的资源使用效率,作为容器界的扛把子,kubernetes 提供了弹性的节点缩放方式。\n\n因为我使用的是 Amazon EKS,所以本文选择了 Karpenter 作为节点缩放器。Karpenter 是一个为 Kubernetes 构建的开源自动扩缩容项目,你可以通过 [此文档](https://karpenter.sh/) 了解更多关于 Karpenter 的信息。\n\n想要管理多个 GPU 节点,还需要用到 NVIDIA 的 [k8s 插件]( https://github.com/NVIDIA/k8s-device-plugin)。这是一个 Daemonset(守护进程),提供了以下自动化的功能:\n\n• 公开集群每个节点上的 GPU 数量\n\n• 实时追踪 GPU 的运行状况\n\n• 在 Kubernetes 集群中运行启用 GPU 的容器\n\n除此之外,它还支持 时间切片,使得用户可以在 Pod (Kubernetes 的最小调度对象)之间共享 GPU,从而节省成本。\n\nKarpenter 本身也为节点提供了自动缩放功能,也就是说,只有在需要算力时,才会创建 GPU 实例,并且可以根据实际需求修改应用实例的调度规则。除了降低成本之外,也能更灵活地把 GPU 资源调度到 kubernetes 集群中的应用程序。\n\n## 架构\n![640.jpeg](2)\n::: hljs-center\n\n基础架构图\n\n![640 1.png](1)\n\n这个架构非常简单易懂:应用程序选择了一个带有选择器(selector)的 karpenter 制备器(provisioner),接着,karpenter 制备器根据启动模板创建节点。\n::: hljs-left\n\n## 部署\n\n接下来最重要的问题是如何去部署它,仍有一些细节需要考虑清楚:\n\n• 如何将 NVIDIA k8s 插件部署到仅有 GPU 的节点\n\n• 如何配置共享的 GPU 节点以使用时间切片,而不影响其他节点\n\n• 如何在启动模板中自动更新节点 AMI,以便节点可以使用最新的镜像\n\n• 如何设置 karpenter 制备器\n\n\n下面我将逐一讲解。\n\n首先,我们安装 karpenter,并使用 terraform 设置制备器。也可以参考官方文档,在 Amazon EKS 中手动安装 karpenter。如果你已经有 EKS 以及karpenter,可以跳过这一步。\n\n不妨参考这个 GitHub repo。\n\n### 制备器\n```python\nresource \"kubectl_manifest\" \"karpenter_provisioner_gpu_shared\" {\n yaml_body = <<-YAML\n apiVersion: karpenter.sh/v1alpha5\n kind: Provisioner\n metadata:\n name: gpu-shared\n spec:\n ttlSecondsAfterEmpty: 300\n labels:\n jina.ai/node-type: gpu-shared\n jina.ai/gpu-type: nvidia\n nvidia.com/device-plugin.config: shared_gpu\n requirements:\n - key: node.kubernetes.io/instance-type\n operator: In\n values: [\"g4dn.xlarge\", \"g4dn.2xlarge\", \"g4dn.4xlarge\", \"g4dn.12xlarge\"]\n - key: karpenter.sh/capacity-type\n operator: In\n values: [\"spot\", \"on-demand\"]\n - key: kubernetes.io/arch\n operator: In\n values: [\"amd64\"]\n taints:\n - key: nvidia.com/gpu-shared\n effect: \"NoSchedule\"\n limits:\n resources:\n cpu: 1000\n provider:\n launchTemplate: \"karpenter-gpu-shared-${local.cluster_name}\"\n subnetSelector:\n karpenter.sh/discovery: ${local.cluster_name}\n tags:\n karpenter.sh/discovery: ${local.cluster_name}\n ttlSecondsAfterEmpty: 30\n YAML\n\n depends_on = [\n helm_release.karpenter\n ]\n}\n\nresource \"kubectl_manifest\" \"karpenter_provisioner_gpu\" {\n yaml_body = <<-YAML\n apiVersion: karpenter.sh/v1alpha5\n kind: Provisioner\n metadata:\n name: gpu\n spec:\n ttlSecondsAfterEmpty: 300\n labels:\n jina.ai/node-type: gpu\n jina.ai/gpu-type: nvidia\n requirements:\n - key: node.kubernetes.io/instance-type\n operator: In\n values: [\"g4dn.xlarge\", \"g4dn.2xlarge\", \"g4dn.4xlarge\", \"g4dn.12xlarge\"]\n - key: karpenter.sh/capacity-type\n operator: In\n values: [\"spot\", \"on-demand\"]\n - key: kubernetes.io/arch\n operator: In\n values: [\"amd64\"]\n taints:\n - key: nvidia.com/gpu\n effect: \"NoSchedule\"\n limits:\n resources:\n cpu: 1000\n provider:\n launchTemplate: \"karpenter-gpu-${local.cluster_name}\"\n subnetSelector:\n karpenter.sh/discovery: ${local.cluster_name}\n tags:\n karpenter.sh/discovery: ${local.cluster_name}\n ttlSecondsAfterEmpty: 30\n YAML\n\n depends_on = [\n helm_release.karpenter\n ]\n}\n```\n上述两份制备器(provisioner)配置使 Kapenter 通过启动模板(launch template)来初始化对应实例,并添加不同标签(labels)和污点(taints)。\n\n\n### 启动模板(仅有GPU)\n```python\nresource \"aws_launch_template\" \"gpu\" {\n name = \"karpenter-gpu-${local.cluster_name}\"\n\n block_device_mappings {\n device_name = \"/dev/xvda\"\n\n ebs {\n volume_size = 120\n }\n }\n\n iam_instance_profile {\n name = aws_iam_instance_profile.karpenter.name\n }\n\n tag_specifications {\n resource_type = \"instance\"\n\n tags = {\n \"karpenter.sh/discovery\" = local.cluster_name\n \"jina.ai/node-type\" = \"gpu\"\n }\n }\n\n image_id = data.aws_ami.eks_node_gpu.image_id\n\n instance_initiated_shutdown_behavior = \"terminate\"\n\n update_default_version = true\n\n # key_name = \"${local.cluster_name}-sshkey\"\n\n metadata_options {\n http_endpoint = \"enabled\"\n http_tokens = \"optional\"\n http_put_response_hop_limit = 2\n }\n\n vpc_security_group_ids = [module.eks.node_security_group_id]\n\n user_data = base64encode(templatefile(\"${path.module}/customized_bootstraps.sh\", { cluster_name = \"${local.cluster_name}\" }))\n\n tags = {\n \"karpenter.sh/discovery\" = local.cluster_name\n \"node-type\" = \"gpu\"\n }\n}\n```\n接下来,我们需要部署具有时间切片配置和默认配置的 NVIDIA k8s 插件,并设置节点选择器,以便 daemonset 仅在 GPU 实例上运行。\n### nvdp.yml\n```yaml\nconfig:\n # ConfigMap name if pulling from an external ConfigMap\n name: \"\"\n # Set of named configs to build an integrated ConfigMap from\n map: \n default: |-\n version: v1\n flags:\n migStrategy: \"none\"\n failOnInitError: true\n nvidiaDriverRoot: \"/\"\n plugin:\n passDeviceSpecs: false\n deviceListStrategy: envvar\n deviceIDStrategy: uuid\n shared_gpu: |-\n version: v1\n flags:\n migStrategy: \"none\"\n failOnInitError: true\n nvidiaDriverRoot: \"/\"\n plugin:\n passDeviceSpecs: false\n deviceListStrategy: envvar\n deviceIDStrategy: uuid\n sharing:\n timeSlicing:\n renameByDefault: false\n resources:\n - name: nvidia.com/gpu\n replicas: 10\nnodeSelector: \n jina.ai/gpu-type: nvidia\n\n```\n\n运行下述命令来安装 NVIDIA 的 k8s 插件:\n```\n$ helm repo add nvdp https://nvidia.github.io/k8s-device-plugin\n$ helm repo update\n$ helm upgrade -i nvdp nvdp/nvidia-device-plugin \\\n --namespace nvidia-device-plugin \\\n --create-namespace -f nvdp.yaml\n\n```\n\n再之后,使用 nodeSelector 和 toleration 部署应用程序。\n\n\n### gpu.yml\n```yaml\nkind: Deployment\napiVersion: apps/v1\nmetadata:\n name: test-gpu\n labels:\n app: gpu\nspec:\n replicas: 1\n selector:\n matchLabels:\n app: gpu\n template:\n metadata:\n labels:\n app: gpu\n spec:\n nodeSelector:\n jina.ai/node-type: gpu\n karpenter.sh/provisioner-name: gpu\n tolerations:\n - key: nvidia.com/gpu\n operator: Exists\n effect: NoSchedule\n containers:\n - name: gpu-container\n image: tensorflow/tensorflow:latest-gpu\n imagePullPolicy: Always\n command: [\"python\"]\n args: [\"-u\", \"-c\", \"import tensorflow\"]\n resources:\n limits:\n nvidia.com/gpu: 1\n```\n### gpu-shared.yml\n\n```yaml\nkind: Deployment\napiVersion: apps/v1\nmetadata:\n name: test-gpu-shared\n labels:\n app: gpu-shared\nspec:\n replicas: 1\n selector:\n matchLabels:\n app: gpu-shared\n template:\n metadata:\n labels:\n app: gpu-shared\n spec:\n nodeSelector:\n jina.ai/node-type: gpu-shared\n karpenter.sh/provisioner-name: gpu-shared\n tolerations:\n - key: nvidia.com/gpu-shared\n operator: Exists\n effect: NoSchedule\n containers:\n - name: gpu-container\n image: tensorflow/tensorflow:latest-gpu\n imagePullPolicy: Always\n command: [\"python\"]\n args: [\"-u\", \"-c\", \"import tensorflow\"]\n resources:\n limits:\n nvidia.com/gpu: 1\n```\n现在,如果部署两个 YAML 文件,你将在 AWS 控制台中看到制备的两个节点,或者通过 kubectl get nodes — show-labels命令查看。在每个节点上运行 nvidia-k8s-plugin 后,就可以在应用程序中进行测试。\n\n\n\n\n\n\n\n\n","render":"<p>在机器学习领域,我们经常使用 GPU 来加速计算工作负载。但现在的企业和开发者都更热衷于“上云”。有了云计算,使用云服务,用多少付多少,也就能降低运营成本了。</p>\n<p>当你拥有数十个在不同时间段需要用到 GPU 的应用程序时,怎么以更低成本,怎么更灵活地在云服务器中调度资源,就会变成一件非常重要的事情。</p>\n<p><mark>作者介绍</mark><br />\n== <a href=\"jina.ai\" target=\"_blank\">Jina AI</a> 云架构研发工程师陶然<br />\n🔗 原文链接:<a href=\"https://jina.ai/news/time-slicing-gpus-with-karpenter/\" target=\"_blank\">https://jina.ai/news/time-slicing-gpus-with-karpenter/</a></p>\n<h2><a id=\"_9\"></a>问题</h2>\n<p>那么,如何优化云服务中 GPU 的使用成本呢?在使用虚拟机时,哪怕你不需要全天候的服务,你也必须持续为所有的设备付费。相比于虚拟机,容器拥有更高的资源使用效率,作为容器界的扛把子,kubernetes 提供了弹性的节点缩放方式。</p>\n<p>因为我使用的是 Amazon EKS,所以本文选择了 Karpenter 作为节点缩放器。Karpenter 是一个为 Kubernetes 构建的开源自动扩缩容项目,你可以通过 <a href=\"https://karpenter.sh/\" target=\"_blank\">此文档</a> 了解更多关于 Karpenter 的信息。</p>\n<p>想要管理多个 GPU 节点,还需要用到 NVIDIA 的 <a href=\"https://github.com/NVIDIA/k8s-device-plugin\" target=\"_blank\">k8s 插件</a>。这是一个 Daemonset(守护进程),提供了以下自动化的功能:</p>\n<p>• 公开集群每个节点上的 GPU 数量</p>\n<p>• 实时追踪 GPU 的运行状况</p>\n<p>• 在 Kubernetes 集群中运行启用 GPU 的容器</p>\n<p>除此之外,它还支持 时间切片,使得用户可以在 Pod (Kubernetes 的最小调度对象)之间共享 GPU,从而节省成本。</p>\n<p>Karpenter 本身也为节点提供了自动缩放功能,也就是说,只有在需要算力时,才会创建 GPU 实例,并且可以根据实际需求修改应用实例的调度规则。除了降低成本之外,也能更灵活地把 GPU 资源调度到 kubernetes 集群中的应用程序。</p>\n<h2><a id=\"_26\"></a>架构</h2>\n<p><img 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alt=\"640.jpeg\" rel=\"2\" /></p>\n<div class=\"hljs-center\">\n<p>基础架构图</p>\n<p><img src=\"data:image/png;base64,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\" alt=\"640 1.png\" rel=\"1\" /></p>\n<p>这个架构非常简单易懂:应用程序选择了一个带有选择器(selector)的 karpenter 制备器(provisioner),接着,karpenter 制备器根据启动模板创建节点。</p>\n<div class=\"hljs-left\">\n<h2><a id=\"_37\"></a>部署</h2>\n<p>接下来最重要的问题是如何去部署它,仍有一些细节需要考虑清楚:</p>\n<p>• 如何将 NVIDIA k8s 插件部署到仅有 GPU 的节点</p>\n<p>• 如何配置共享的 GPU 节点以使用时间切片,而不影响其他节点</p>\n<p>• 如何在启动模板中自动更新节点 AMI,以便节点可以使用最新的镜像</p>\n<p>• 如何设置 karpenter 制备器</p>\n<p>下面我将逐一讲解。</p>\n<p>首先,我们安装 karpenter,并使用 terraform 设置制备器。也可以参考官方文档,在 Amazon EKS 中手动安装 karpenter。如果你已经有 EKS 以及karpenter,可以跳过这一步。</p>\n<p>不妨参考这个 GitHub repo。</p>\n<h3><a id=\"_56\"></a>制备器</h3>\n<pre><div class=\"hljs\"><code class=\"lang-python\">resource <span class=\"hljs-string\">&quot;kubectl_manifest&quot;</span> <span class=\"hljs-string\">&quot;karpenter_provisioner_gpu_shared&quot;</span> {\n yaml_body = &lt;&lt;-YAML\n apiVersion: karpenter.sh/v1alpha5\n kind: Provisioner\n metadata:\n name: gpu-shared\n spec:\n ttlSecondsAfterEmpty: <span class=\"hljs-number\">300</span>\n labels:\n jina.ai/node-<span class=\"hljs-built_in\">type</span>: gpu-shared\n jina.ai/gpu-<span class=\"hljs-built_in\">type</span>: nvidia\n nvidia.com/device-plugin.config: shared_gpu\n requirements:\n - key: node.kubernetes.io/instance-<span class=\"hljs-built_in\">type</span>\n operator: In\n values: [<span class=\"hljs-string\">&quot;g4dn.xlarge&quot;</span>, <span class=\"hljs-string\">&quot;g4dn.2xlarge&quot;</span>, <span class=\"hljs-string\">&quot;g4dn.4xlarge&quot;</span>, <span class=\"hljs-string\">&quot;g4dn.12xlarge&quot;</span>]\n - key: karpenter.sh/capacity-<span class=\"hljs-built_in\">type</span>\n operator: In\n values: [<span class=\"hljs-string\">&quot;spot&quot;</span>, <span class=\"hljs-string\">&quot;on-demand&quot;</span>]\n - key: kubernetes.io/arch\n operator: In\n values: [<span class=\"hljs-string\">&quot;amd64&quot;</span>]\n taints:\n - key: nvidia.com/gpu-shared\n effect: <span class=\"hljs-string\">&quot;NoSchedule&quot;</span>\n limits:\n resources:\n cpu: <span class=\"hljs-number\">1000</span>\n provider:\n launchTemplate: <span class=\"hljs-string\">&quot;karpenter-gpu-shared-${local.cluster_name}&quot;</span>\n subnetSelector:\n karpenter.sh/discovery: ${local.cluster_name}\n tags:\n karpenter.sh/discovery: ${local.cluster_name}\n ttlSecondsAfterEmpty: <span class=\"hljs-number\">30</span>\n YAML\n\n depends_on = [\n helm_release.karpenter\n ]\n}\n\nresource <span class=\"hljs-string\">&quot;kubectl_manifest&quot;</span> <span class=\"hljs-string\">&quot;karpenter_provisioner_gpu&quot;</span> {\n yaml_body = &lt;&lt;-YAML\n apiVersion: karpenter.sh/v1alpha5\n kind: Provisioner\n metadata:\n name: gpu\n spec:\n ttlSecondsAfterEmpty: <span class=\"hljs-number\">300</span>\n labels:\n jina.ai/node-<span class=\"hljs-built_in\">type</span>: gpu\n jina.ai/gpu-<span class=\"hljs-built_in\">type</span>: nvidia\n requirements:\n - key: node.kubernetes.io/instance-<span class=\"hljs-built_in\">type</span>\n operator: In\n values: [<span class=\"hljs-string\">&quot;g4dn.xlarge&quot;</span>, <span class=\"hljs-string\">&quot;g4dn.2xlarge&quot;</span>, <span class=\"hljs-string\">&quot;g4dn.4xlarge&quot;</span>, <span class=\"hljs-string\">&quot;g4dn.12xlarge&quot;</span>]\n - key: karpenter.sh/capacity-<span class=\"hljs-built_in\">type</span>\n operator: In\n values: [<span class=\"hljs-string\">&quot;spot&quot;</span>, <span class=\"hljs-string\">&quot;on-demand&quot;</span>]\n - key: kubernetes.io/arch\n operator: In\n values: [<span class=\"hljs-string\">&quot;amd64&quot;</span>]\n taints:\n - key: nvidia.com/gpu\n effect: <span class=\"hljs-string\">&quot;NoSchedule&quot;</span>\n limits:\n resources:\n cpu: <span class=\"hljs-number\">1000</span>\n provider:\n launchTemplate: <span class=\"hljs-string\">&quot;karpenter-gpu-${local.cluster_name}&quot;</span>\n subnetSelector:\n karpenter.sh/discovery: ${local.cluster_name}\n tags:\n karpenter.sh/discovery: ${local.cluster_name}\n ttlSecondsAfterEmpty: <span class=\"hljs-number\">30</span>\n YAML\n\n depends_on = [\n helm_release.karpenter\n ]\n}\n</code></div></pre>\n<p>上述两份制备器(provisioner)配置使 Kapenter 通过启动模板(launch template)来初始化对应实例,并添加不同标签(labels)和污点(taints)。</p>\n<h3><a id=\"GPU_144\"></a>启动模板(仅有GPU)</h3>\n<pre><div class=\"hljs\"><code class=\"lang-python\">resource <span class=\"hljs-string\">&quot;aws_launch_template&quot;</span> <span class=\"hljs-string\">&quot;gpu&quot;</span> {\n name = <span class=\"hljs-string\">&quot;karpenter-gpu-${local.cluster_name}&quot;</span>\n\n block_device_mappings {\n device_name = <span class=\"hljs-string\">&quot;/dev/xvda&quot;</span>\n\n ebs {\n volume_size = <span class=\"hljs-number\">120</span>\n }\n }\n\n iam_instance_profile {\n name = aws_iam_instance_profile.karpenter.name\n }\n\n tag_specifications {\n resource_type = <span class=\"hljs-string\">&quot;instance&quot;</span>\n\n tags = {\n <span class=\"hljs-string\">&quot;karpenter.sh/discovery&quot;</span> = local.cluster_name\n <span class=\"hljs-string\">&quot;jina.ai/node-type&quot;</span> = <span class=\"hljs-string\">&quot;gpu&quot;</span>\n }\n }\n\n image_id = data.aws_ami.eks_node_gpu.image_id\n\n instance_initiated_shutdown_behavior = <span class=\"hljs-string\">&quot;terminate&quot;</span>\n\n update_default_version = true\n\n <span class=\"hljs-comment\"># key_name = &quot;${local.cluster_name}-sshkey&quot;</span>\n\n metadata_options {\n http_endpoint = <span class=\"hljs-string\">&quot;enabled&quot;</span>\n http_tokens = <span class=\"hljs-string\">&quot;optional&quot;</span>\n http_put_response_hop_limit = <span class=\"hljs-number\">2</span>\n }\n\n vpc_security_group_ids = [module.eks.node_security_group_id]\n\n user_data = base64encode(templatefile(<span class=\"hljs-string\">&quot;${path.module}/customized_bootstraps.sh&quot;</span>, { cluster_name = <span class=\"hljs-string\">&quot;${local.cluster_name}&quot;</span> }))\n\n tags = {\n <span class=\"hljs-string\">&quot;karpenter.sh/discovery&quot;</span> = local.cluster_name\n <span class=\"hljs-string\">&quot;node-type&quot;</span> = <span class=\"hljs-string\">&quot;gpu&quot;</span>\n }\n}\n</code></div></pre>\n<p>接下来,我们需要部署具有时间切片配置和默认配置的 NVIDIA k8s 插件,并设置节点选择器,以便 daemonset 仅在 GPU 实例上运行。</p>\n<h3><a id=\"nvdpyml_195\"></a>nvdp.yml</h3>\n<pre><div class=\"hljs\"><code class=\"lang-yaml\"><span class=\"hljs-attr\">config:</span>\n <span class=\"hljs-comment\"># ConfigMap name if pulling from an external ConfigMap</span>\n <span class=\"hljs-attr\">name:</span> <span class=\"hljs-string\">&quot;&quot;</span>\n <span class=\"hljs-comment\"># Set of named configs to build an integrated ConfigMap from</span>\n <span class=\"hljs-attr\">map:</span> \n <span class=\"hljs-attr\">default:</span> <span class=\"hljs-string\">|-\n version: v1\n flags:\n migStrategy: &quot;none&quot;\n failOnInitError: true\n nvidiaDriverRoot: &quot;/&quot;\n plugin:\n passDeviceSpecs: false\n deviceListStrategy: envvar\n deviceIDStrategy: uuid\n</span> <span class=\"hljs-attr\">shared_gpu:</span> <span class=\"hljs-string\">|-\n version: v1\n flags:\n migStrategy: &quot;none&quot;\n failOnInitError: true\n nvidiaDriverRoot: &quot;/&quot;\n plugin:\n passDeviceSpecs: false\n deviceListStrategy: envvar\n deviceIDStrategy: uuid\n sharing:\n timeSlicing:\n renameByDefault: false\n resources:\n - name: nvidia.com/gpu\n replicas: 10\n</span><span class=\"hljs-attr\">nodeSelector:</span> \n <span class=\"hljs-attr\">jina.ai/gpu-type:</span> <span class=\"hljs-string\">nvidia</span>\n\n</code></div></pre>\n<p>运行下述命令来安装 NVIDIA 的 k8s 插件:</p>\n<pre><code class=\"lang-\">$ helm repo add nvdp https://nvidia.github.io/k8s-device-plugin\n$ helm repo update\n$ helm upgrade -i nvdp nvdp/nvidia-device-plugin \\\n --namespace nvidia-device-plugin \\\n --create-namespace -f nvdp.yaml\n\n</code></pre>\n<p>再之后,使用 nodeSelector 和 toleration 部署应用程序。</p>\n<h3><a id=\"gpuyml_246\"></a>gpu.yml</h3>\n<pre><div class=\"hljs\"><code class=\"lang-yaml\"><span class=\"hljs-attr\">kind:</span> <span class=\"hljs-string\">Deployment</span>\n<span class=\"hljs-attr\">apiVersion:</span> <span class=\"hljs-string\">apps/v1</span>\n<span class=\"hljs-attr\">metadata:</span>\n <span class=\"hljs-attr\">name:</span> <span class=\"hljs-string\">test-gpu</span>\n <span class=\"hljs-attr\">labels:</span>\n <span class=\"hljs-attr\">app:</span> <span class=\"hljs-string\">gpu</span>\n<span class=\"hljs-attr\">spec:</span>\n <span class=\"hljs-attr\">replicas:</span> <span class=\"hljs-number\">1</span>\n <span class=\"hljs-attr\">selector:</span>\n <span class=\"hljs-attr\">matchLabels:</span>\n <span class=\"hljs-attr\">app:</span> <span class=\"hljs-string\">gpu</span>\n <span class=\"hljs-attr\">template:</span>\n <span class=\"hljs-attr\">metadata:</span>\n <span class=\"hljs-attr\">labels:</span>\n <span class=\"hljs-attr\">app:</span> <span class=\"hljs-string\">gpu</span>\n <span class=\"hljs-attr\">spec:</span>\n <span class=\"hljs-attr\">nodeSelector:</span>\n <span class=\"hljs-attr\">jina.ai/node-type:</span> <span class=\"hljs-string\">gpu</span>\n <span class=\"hljs-attr\">karpenter.sh/provisioner-name:</span> <span class=\"hljs-string\">gpu</span>\n <span class=\"hljs-attr\">tolerations:</span>\n <span class=\"hljs-bullet\">-</span> <span class=\"hljs-attr\">key:</span> <span class=\"hljs-string\">nvidia.com/gpu</span>\n <span class=\"hljs-attr\">operator:</span> <span class=\"hljs-string\">Exists</span>\n <span class=\"hljs-attr\">effect:</span> <span class=\"hljs-string\">NoSchedule</span>\n <span class=\"hljs-attr\">containers:</span>\n <span class=\"hljs-bullet\">-</span> <span class=\"hljs-attr\">name:</span> <span class=\"hljs-string\">gpu-container</span>\n <span class=\"hljs-attr\">image:</span> <span class=\"hljs-string\">tensorflow/tensorflow:latest-gpu</span>\n <span class=\"hljs-attr\">imagePullPolicy:</span> <span class=\"hljs-string\">Always</span>\n <span class=\"hljs-attr\">command:</span> [<span class=\"hljs-string\">&quot;python&quot;</span>]\n <span class=\"hljs-attr\">args:</span> [<span class=\"hljs-string\">&quot;-u&quot;</span>, <span class=\"hljs-string\">&quot;-c&quot;</span>, <span class=\"hljs-string\">&quot;import tensorflow&quot;</span>]\n <span class=\"hljs-attr\">resources:</span>\n <span class=\"hljs-attr\">limits:</span>\n <span class=\"hljs-attr\">nvidia.com/gpu:</span> <span class=\"hljs-number\">1</span>\n</code></div></pre>\n<h3><a id=\"gpusharedyml_281\"></a>gpu-shared.yml</h3>\n<pre><div class=\"hljs\"><code class=\"lang-yaml\"><span class=\"hljs-attr\">kind:</span> <span class=\"hljs-string\">Deployment</span>\n<span class=\"hljs-attr\">apiVersion:</span> <span class=\"hljs-string\">apps/v1</span>\n<span class=\"hljs-attr\">metadata:</span>\n <span class=\"hljs-attr\">name:</span> <span class=\"hljs-string\">test-gpu-shared</span>\n <span class=\"hljs-attr\">labels:</span>\n <span class=\"hljs-attr\">app:</span> <span class=\"hljs-string\">gpu-shared</span>\n<span class=\"hljs-attr\">spec:</span>\n <span class=\"hljs-attr\">replicas:</span> <span class=\"hljs-number\">1</span>\n <span class=\"hljs-attr\">selector:</span>\n <span class=\"hljs-attr\">matchLabels:</span>\n <span class=\"hljs-attr\">app:</span> <span class=\"hljs-string\">gpu-shared</span>\n <span class=\"hljs-attr\">template:</span>\n <span class=\"hljs-attr\">metadata:</span>\n <span class=\"hljs-attr\">labels:</span>\n <span class=\"hljs-attr\">app:</span> <span class=\"hljs-string\">gpu-shared</span>\n <span class=\"hljs-attr\">spec:</span>\n <span class=\"hljs-attr\">nodeSelector:</span>\n <span class=\"hljs-attr\">jina.ai/node-type:</span> <span class=\"hljs-string\">gpu-shared</span>\n <span class=\"hljs-attr\">karpenter.sh/provisioner-name:</span> <span class=\"hljs-string\">gpu-shared</span>\n <span class=\"hljs-attr\">tolerations:</span>\n <span class=\"hljs-bullet\">-</span> <span class=\"hljs-attr\">key:</span> <span class=\"hljs-string\">nvidia.com/gpu-shared</span>\n <span class=\"hljs-attr\">operator:</span> <span class=\"hljs-string\">Exists</span>\n <span class=\"hljs-attr\">effect:</span> <span class=\"hljs-string\">NoSchedule</span>\n <span class=\"hljs-attr\">containers:</span>\n <span class=\"hljs-bullet\">-</span> <span class=\"hljs-attr\">name:</span> <span class=\"hljs-string\">gpu-container</span>\n <span class=\"hljs-attr\">image:</span> <span class=\"hljs-string\">tensorflow/tensorflow:latest-gpu</span>\n <span class=\"hljs-attr\">imagePullPolicy:</span> <span class=\"hljs-string\">Always</span>\n <span class=\"hljs-attr\">command:</span> [<span class=\"hljs-string\">&quot;python&quot;</span>]\n <span class=\"hljs-attr\">args:</span> [<span class=\"hljs-string\">&quot;-u&quot;</span>, <span class=\"hljs-string\">&quot;-c&quot;</span>, <span class=\"hljs-string\">&quot;import tensorflow&quot;</span>]\n <span class=\"hljs-attr\">resources:</span>\n <span class=\"hljs-attr\">limits:</span>\n <span class=\"hljs-attr\">nvidia.com/gpu:</span> <span class=\"hljs-number\">1</span>\n</code></div></pre>\n<p>现在,如果部署两个 YAML 文件,你将在 AWS 控制台中看到制备的两个节点,或者通过 kubectl get nodes — show-labels命令查看。在每个节点上运行 nvidia-k8s-plugin 后,就可以在应用程序中进行测试。</p>\n</div>\n</div>\n"}
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