app configuration, metrics, inbound ports, GPU access, samples

Author: mwunderl

Diff for: docs-source/applications-gpuaccess.md

@@ -0,0 +1,66 @@
+# Using the GPU<a name="applications-gpuaccess"></a>
+
+You can access the graphics processor \(GPU\) on the AWS Panorama Appliance to use GPU\-accelerated libraries, or run machine learning models in your application code\. To turn on GPU access, you add GPU access as a requirement to the package configuration after building your application code container\.
+
+**Important**  
+If you enable GPU access, you can't run model nodes in any application on the appliance\. For security purposes, GPU access is restricted when the appliance runs a model compiled with SageMaker Neo\. With GPU access, you must run your models in application code nodes, and all applications on the device share access to the GPU\.
+
+To turn on GPU access for your application, update the [package manifest](applications-packages.md) after you build the package with the AWS Panorama Application CLI\. The following example shows the `requirements` block that adds GPU access to the application code node\.
+
+**Example package\.json with requirements block**  
+
+```
+{
+    "nodePackage": {
+        "envelopeVersion": "2021-01-01",
+        "name": "SAMPLE_CODE",
+        "version": "1.0",
+        "description": "Computer vision application code.",
+        "assets": [
+            {
+                "name": "code_asset",
+                "implementations": [
+                    {
+                        "type": "container",
+                        "assetUri": "eba3xmpl71aa387e8f89be9a8c396416cdb80a717bb32103c957a8bf41440b12.tar.gz",
+                        "descriptorUri": "4abdxmpl5a6f047d2b3047adde44704759d13f0126c00ed9b4309726f6bb43400ba9.json",
+                        "requirements": [
+                            {
+                                "type": "hardware_access",
+                                "inferenceAccelerators": [
+                                    {
+                                        "deviceType": "nvhost_gpu",
+                                        "accessType": "open"
+                                    }
+                                ]
+                            }
+                        ]
+                    }
+                ]
+            }
+        ],
+        "interfaces": [
+        ...
+```
+
+Update the package manifest between the build and packaging steps in your development workflow\.
+
+**To deploy an application with GPU access**
+
+1. To build the application container, use the `build-container` command\.
+
+   ```
+   $ panorama-cli build-container --container-asset-name code_asset --package-path packages/123456789012-SAMPLE_CODE-1.0
+   ```
+
+1. Add the `requirements` block to the package manifest\.
+
+1. To upload the container asset and package manifest, use the `package-application` command\.
+
+   ```
+   $ panorama-cli package-application
+   ```
+
+1. Deploy the application\.
+
+For sample applications that use GPU access, visit the [aws\-panorama\-samples](https://github.com/aws-samples/aws-panorama-samples) GitHub repository\.

Diff for: docs-source/applications-manifest-parameters.md

@@ -0,0 +1,53 @@
+# Application parameters<a name="applications-manifest-parameters"></a>
+
+Parameters are nodes that have a basic type and can be overridden during deployment\. A parameter can have a default value and a *decorator*, which instructs the application's user how to configure it\.
+
+**Parameter types**
++ `string` – A string\. For example, `DEBUG`\.
++ `int32` – An integer\. For example, `20`
++ `float32` – A floating point number\. For example, `47.5`
++ `boolean` – `true` or `false`\.
+
+The following example shows two parameters, a string and a number, which are sent to a code node as inputs\.
+
+**Example graph\.json – Parameters**  
+
+```
+        "nodes": [
+            {
+                "name": "detection_threshold",
+                "interface": "float32",
+                "value": 20.0,
+                "overridable": true,
+                "decorator": {
+                    "title": "Threshold",
+                    "description": "The minimum confidence percentage for a positive classification."
+                }
+            },
+            {
+                "name": "log_level",
+                "interface": "string",
+                "value": "INFO",
+                "overridable": true,
+                "decorator": {
+                    "title": "Logging level",
+                    "description": "DEBUG, INFO, WARNING, ERROR, or CRITICAL."
+                }
+            }
+            ...
+        ],
+        "edges": [
+            {
+                "producer": "detection_threshold",
+                "consumer": "code_node.threshold"
+            },
+            {
+                "producer": "log_level",
+                "consumer": "code_node.log_level"
+            }
+            ...
+        ]
+    }
+```
+
+You can modify parameters directly in the application manifest, or provide new values at deploy\-time with overrides\. For more information, see [Deploy\-time configuration with overrides](applications-overrides.md)\.