Merge branch 'ArmDeveloperEcosystem:main' into main

Author: odincodeshen

content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/1-prerequisites.md

@@ -13,7 +13,7 @@ This Learning Path demonstrates how to improve the performance of camera pipelin
 ## Install required software
 
 Make sure the following tools are installed:
-- `git` - a version control system, for cloning the Voice Assistant codebase.
+- `git` - a version control system, for cloning the AI camera pipelines codebase.
 - `git lfs` - an extension to `git` for managing large files by storing lightweight references instead of the files themselves.
 - `docker` - an open-source containerization platform for running applications in isolated environments.
 - `libomp` - LLVM's OpenMP runtime library, required for enabling parallel execution during application performance optimization.
@@ -52,7 +52,7 @@ Once you have confirmed that Docker is installed on your machine, you can check
 docker run hello-world
 Unable to find image 'hello-world:latest' locally
 latest: Pulling from library/hello-world
-c9c5fd25a1bd: Pull complete 
+c9c5fd25a1bd: Pull complete
 Digest: sha256:c41088499908a59aae84b0a49c70e86f4731e588a737f1637e73c8c09d995654
 Status: Downloaded newer image for hello-world:latest
 

content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/3-build.md

@@ -73,15 +73,26 @@ Leave the container by pressing `Ctrl+D`.
 
 ## Notes on the cmake configuration options
 
-- `-DENABLE_SME2=$ENABLE_SME2` with `ENABLE_SME2=0`: SME2 (Scalable Matrix Extension 2) is disabled in this build (`0`).  
-- `-DARMNN_TFLITE_PARSER=0`: Configures the `ai-camera-pipelines` repository to use LiteRT with XNNPack instead of ArmNN.
-- `-DENABLE_KLEIDICV:BOOL=ON`: Enables KleidiCV for optimized image processing.
-- `-DXNNPACK_ENABLE_KLEIDIAI:BOOL=ON`:  Enables KleidiAI acceleration for LiteRT workloads via XNNPack.
+The `cmake` command line options relevant to this learning path are:
+
+| Command line option                 | Description                                                                                  |
+|-------------------------------------|----------------------------------------------------------------------------------------------|
+| `ENABLE_SME2=$ENABLE_SME2`          | SME2 (Scalable Matrix Extension 2) is disabled in this build with `ENABLE_SME2=0`.           |
+| `ARMNN_TFLITE_PARSER=0`             | Configures the `ai-camera-pipelines` repository to use LiteRT with XNNPack instead of ArmNN. |
+| `ENABLE_KLEIDICV:BOOL=ON`           | Enables KleidiCV for optimized image processing.                                             |
+| `XNNPACK_ENABLE_KLEIDIAI:BOOL=ON`   | Enables KleidiAI acceleration for LiteRT workloads via XNNPack.                              |
 
 ## Install the pipelines
 
 ```bash
 cd $HOME
 tar xfz ai-camera-pipelines.git/install.tar.gz
 mv install ai-camera-pipelines
-```
+```
+
+## Diving further in the AI camera pipelines
+
+The AI camera pipelines
+[repository](https://git.gitlab.arm.com/kleidi/kleidi-examples/ai-camera-pipelines)
+contains more information in its README file should you wish to dive deeper into
+it.

content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/4-run.md

@@ -30,4 +30,5 @@ cd $HOME/ai-camera-pipelines
 bin/low_light_image_enhancement resources/test_input2.ppm test_output2_lime.ppm resources/HDRNetLIME_lr_coeffs_v1_1_0_mixed_low_light_perceptual_l2_loss_int8_only_ptq.tflite
 ```
 
+![example image alt-text#center](test_input2.png "Original picture")
 ![example image alt-text#center](test_output2_lime.png "Picture with low-light enhancement applied")

content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md

@@ -1,5 +1,5 @@
 ---
-title: Tomcat benchmark set up
+title: Set up Tomcat
 weight: 2
 
 ### FIXED, DO NOT MODIFY
@@ -9,16 +9,16 @@ layout: learningpathall
 
 ## Overview 
 
-There are numerouse client-server and network-based workloads, and Tomcat is a typical example of such applications, which provide services via HTTP/HTTPS network requests.
+There are numerous client-server and network-based workloads, with Tomcat being a typical example of such applications. Tomcat provides services via HTTP/HTTPS network requests.
 
-In this section, you'll set up a benchmark environment using Apache Tomcat and `wrk2` to simulate HTTP load and evaluate performance on an Arm-based bare-metal (**__`Nvidia-Grace`__**).
+In this section, you will set up a benchmark environment using `Apache Tomcat` and `wrk2` to simulate an HTTP load and evaluate performance on an Arm-based bare metal instance. This Learning Path was tested on an AWS `c8g.metal-48xl` instance.
 
-## Set up the Tomcat benchmark server on **Nvidia Grace**
+## Set up the Tomcat benchmark server
 [Apache Tomcat](https://tomcat.apache.org/) is an open-source Java Servlet container that runs Java web applications, handles HTTP requests, and serves dynamic content. It supports technologies such as Servlet, JSP, and WebSocket.
 
 ## Install the Java Development Kit (JDK)
 
-Install OpenJDK 21 on your Arm-based Ubuntu 24 bare-metal: 
+Install OpenJDK 21 on your Arm-based Ubuntu 24.04 bare-metal instance: 
 
 ```bash
 sudo apt update
@@ -30,8 +30,8 @@ sudo apt install -y openjdk-21-jdk
 Download and extract Tomcat:
 
 ```bash
-wget -c https://dlcdn.apache.org/tomcat/tomcat-11/v11.0.9/bin/apache-tomcat-11.0.9.tar.gz
-tar xzf apache-tomcat-11.0.9.tar.gz
+wget -c https://dlcdn.apache.org/tomcat/tomcat-11/v11.0.10/bin/apache-tomcat-11.0.10.tar.gz
+tar xzf apache-tomcat-11.0.10.tar.gz
 ```
 Alternatively, you can build Tomcat [from source](https://github.com/apache/tomcat).
 
@@ -41,16 +41,19 @@ To access the built-in examples from your local network or external IP, use a te
 
 The file is at:
 ```bash
-apache-tomcat-11.0.9/webapps/examples/META-INF/context.xml
+~/apache-tomcat-11.0.10/webapps/examples/META-INF/context.xml
 ```
 
+Replace the existing allow value as shown:
 ```xml
-<!-- Before -->
 <Valve className="org.apache.catalina.valves.RemoteAddrValve" allow="127\.\d+\.\d+\.\d+|::1|0:0:0:0:0:0:0:1" />
+```
 
-<!-- After -->
+With:
+```xml
 <Valve className="org.apache.catalina.valves.RemoteAddrValve" allow=".*" />
 ```
+Save the changes to your file.
 
 ## Start the Tomcat server
 {{% notice Note %}}
@@ -60,17 +63,17 @@ To achieve maximum performance of Tomcat, the maximum number of file descriptors
 Start the server:
 
 ```bash
-ulimit -n 65535 && ./apache-tomcat-11.0.9/bin/startup.sh
+ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
 ```
 
 You should see output like:
 
 ```output
-Using CATALINA_BASE:   /home/ubuntu/apache-tomcat-11.0.9
-Using CATALINA_HOME:   /home/ubuntu/apache-tomcat-11.0.9
-Using CATALINA_TMPDIR: /home/ubuntu/apache-tomcat-11.0.9/temp
+Using CATALINA_BASE:   /home/ubuntu/apache-tomcat-11.0.10
+Using CATALINA_HOME:   /home/ubuntu/apache-tomcat-11.0.10
+Using CATALINA_TMPDIR: /home/ubuntu/apache-tomcat-11.0.10/temp
 Using JRE_HOME:        /usr
-Using CLASSPATH:       /home/ubuntu/apache-tomcat-11.0.9/bin/bootstrap.jar:/home/ubuntu/apache-tomcat-11.0.9/bin/tomcat-juli.jar
+Using CLASSPATH:       /home/ubuntu/apache-tomcat-11.0.10/bin/bootstrap.jar:/home/ubuntu/apache-tomcat-11.0.10/bin/tomcat-juli.jar
 Using CATALINA_OPTS:
 Tomcat started.
 ```
@@ -91,7 +94,7 @@ You should see the Tomcat welcome page and examples, as shown below:
 [Wrk2](https://github.com/giltene/wrk2) is a high-performance HTTP benchmarking tool specialized in generating constant throughput loads and measuring latency percentiles for web services. `wrk2` is an enhanced version of `wrk` that provides accurate latency statistics under controlled request rates, ideal for performance testing of HTTP servers.
 
 {{% notice Note %}}
-Currently `wrk2` is only supported on x86 machines. Run the benchmark client steps below on an `x86_64` server running Ubuntu 24.
+Currently `wrk2` is only supported on x86 machines. Run the benchmark client steps below on a bare metal `x86_64` server running Ubuntu 24.04
 {{% /notice %}}
 
 ## Install dependencies 
@@ -132,28 +135,28 @@ ulimit -n 65535 && wrk -c32 -t16 -R50000 -d60 http://${tomcat_ip}:8080/examples/
 You should see output similar to:
 
 ```console
-Running 1m test @ http://172.26.203.139:8080/examples/servlets/servlet/HelloWorldExample
+Running 1m test @ http://172.31.46.193:8080/examples/servlets/servlet/HelloWorldExample
   16 threads and 32 connections
-  Thread calibration: mean lat.: 0.986ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.984ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.999ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.994ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.983ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.989ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.991ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.993ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.985ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.990ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.987ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.990ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.984ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.991ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.978ms, rate sampling interval: 10ms
-  Thread calibration: mean lat.: 0.976ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.381ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.626ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.020ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.578ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.166ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.275ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.454ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.655ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.334ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.089ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.365ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.382ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.342ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.349ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.023ms, rate sampling interval: 10ms
+  Thread calibration: mean lat.: 3.275ms, rate sampling interval: 10ms
   Thread Stats   Avg      Stdev     Max   +/- Stdev
-    Latency     1.00ms  454.90us   5.09ms   63.98%
-    Req/Sec     3.31k   241.68     4.89k    63.83%
-  2999817 requests in 1.00m, 1.56GB read
-Requests/sec:  49997.08
+    Latency     1.02ms  398.88us   4.24ms   66.77%
+    Req/Sec     3.30k   210.16     4.44k    70.04%
+  2999776 requests in 1.00m, 1.56GB read
+Requests/sec:  49996.87
 Transfer/sec:     26.57MB
 ```