Merge branch 'ArmDeveloperEcosystem:main' into main

Author: christophe0606

.wordlist.txt

@@ -3966,4 +3966,46 @@ mesaros
 multilayer
 renderbuffer
 rosdep
-suboptimally
+suboptimally
+AMQP
+AirQualityIndex
+AzureFunctions
+AzureIoT
+AzureWebJobsStorage
+CosmosDBOutput
+DOCUMENTDB
+IoTDatabaee
+IoTDatabase
+IoTHubInput
+IoTStreamAnalyticsJob
+IoTTemperatureAlertFunc
+IsEncrypted
+LRS
+RUs
+SENDGRID
+SendGrid
+SendGridAPIClient
+Servleress
+Twilio
+armiotcosmosdb
+armiotstorage
+asyncio
+autogenerated
+averageTemperature
+averagetemperature
+azcosmosdb
+cardinality
+cosmosdb
+declaratively
+devguide
+differentiator
+etag
+getTempBtn
+hotspots
+iothubowner
+schemas
+sdks
+sendgrid
+soafee
+timestamping
+transactional

content/install-guides/armpl.md

@@ -122,19 +122,19 @@ The instructions shown below are for deb based installers for GCC users.
 In a terminal, run the command shown below to download the Debian package:
 
 ```bash
-wget https://developer.arm.com/-/cdn-downloads/permalink/Arm-Performance-Libraries/Version_25.04/arm-performance-libraries_25.04_deb_gcc.tar
+wget https://developer.arm.com/-/cdn-downloads/permalink/Arm-Performance-Libraries/Version_25.04.1/arm-performance-libraries_25.04.1_deb_gcc.tar
 ```
 
 Use `tar` to extract the file and then change directory:
 
 ```bash
-tar xf arm-performance-libraries_25.04_deb_gcc.tar
+tar xf arm-performance-libraries_25.04.1_deb_gcc.tar
 ```
 
 Run the installation script as a super user:
 
 ```bash
-sudo ./arm-performance-libraries_25.04_deb/arm-performance-libraries_25.04_deb.sh --accept
+sudo ./arm-performance-libraries_25.04.1_deb/arm-performance-libraries_25.04.1_deb.sh --accept
 ```
 
 Using the `--accept` switch you automatically accept the End User License Agreement and the packages are installed to the `/opt/arm` directory.
@@ -190,13 +190,13 @@ module avail
 The output should be similar to:
 
 ```output
-armpl/25.04.0_gcc
+armpl/25.04.1_gcc
 ```
 
 Load the appropriate module:
 
 ```console
-module load armpl/25.04.0_gcc
+module load armpl/25.04.1_gcc
 ```
 
 You can now compile and test the examples included in the `/opt/arm/<armpl_dir>/examples/`, or `<install_dir>/<armpl_dir>/examples/` directory, if you have installed to a different location than the default.

content/learning-paths/automotive/_index.md

@@ -21,5 +21,5 @@ tools_software_languages_filter:
 - Automotive: 1
 - Docker: 1
 - Python: 1
-- ROS2: 1
+- ROS 2: 1
 ---

content/learning-paths/automotive/openadkit1_container/1_sdv_soafee.md

@@ -8,11 +8,11 @@ layout: learningpathall
 
 ## Introduction to Software-Defined Vehicles
 
-In recent years, the automotive industry has been undergoing a transformation driven by software, with the concept of the Software-Defined Vehicle (SDV) emerging as a key paradigm for the future of intelligent cars. As the number of Electronic Control Units (ECUs) increases and vehicle systems become more complex, the traditional hardware-driven development approach is no longer sufficient. To improve development efficiency and product quality, automotive software development is moving to a Shift-Left approach, accelerating validation and deployment processes.
+In recent years, the automotive industry has been undergoing a transformation driven by software, with the concept of the Software-Defined Vehicle (SDV) emerging as a key paradigm for the future of intelligent cars. As the number of Electronic Control Units (ECUs) increases and vehicle systems become more complex, the traditional hardware-driven development approach is no longer sufficient. To improve development efficiency and product quality, automotive software development is moving to a Shift-Left approach, accelerating validation and deployment.
 
 ## The evolution of Software-Defined Vehicles
 
-The core idea of SDV is to make software the primary differentiating factor of a vehicle, enabling continuous feature updates via Over-The-Air (OTA) technology. This approach allows manufacturers to shorten development cycles while continuously improving safety and performance after a vehicle is released. Moreover, SDV promotes the adoption of Service-Oriented Architecture (SOA), enabling modular and scalable software that integrates seamlessly with cloud services.
+The core idea of SDV is to make software the primary differentiator in a vehicle, enabling continuous feature updates via Over-The-Air (OTA) technology. This approach allows manufacturers to shorten development cycles while continuously improving safety and performance after a vehicle is released. Moreover, SDV promotes the adoption of Service-Oriented Architecture (SOA), enabling modular and scalable software that integrates seamlessly with cloud services.
 
 However, this transition introduces new challenges, particularly in software development and validation. The traditional V-model development process struggles to meet SDV demands since defects are often detected late in development, leading to costly fixes. As a result, Shift-Left has become a crucial strategy to address these challenges.
 

content/learning-paths/automotive/openadkit1_container/2_automotive_softwares.md

@@ -46,8 +46,9 @@ Autoware, built on ROS, features a modular AD stack with well-defined interfaces
 Committed to democratizing AD technology, Autoware fosters collaboration among industry, researchers, and developers. By promoting open standards and innovation, the foundation accelerates autonomous driving adoption while ensuring safety, scalability, and real-world usability, driving the future of autonomous mobility through open-source development and ecosystem synergy.
 
 The Open AD Kit Blueprint has evolved through multiple iterations of containerized Autoware software. It supports both cloud and edge deployments in physical and virtual environments, with OTA updates enabling seamless software upgrades.
+
 The Open AD Kit project continues to be developed by the Open AD Kit working group, and the following are the main goals and principles of the collaborative project:
-- Introducing modern cloud-native development and deployment methodologies for the Autoware use
+- Introducing modern cloud-native development and deployment methodologies for Autoware use cases
 - Introducing mixed-critical orchestration, paving the way for safety and certifiability
 - Enabling validation using virtual prototyping platforms to achieve shift-left paradigms
 - Providing a consistent production environment to deploy Autoware using hardware abstraction technologies to enable hardware-agnostic solutions

content/learning-paths/automotive/openadkit1_container/_index.md

@@ -1,10 +1,6 @@
 ---
 title: Deploy Open AD Kit containerized autonomous driving simulation on Arm Neoverse
 
-draft: true
-cascade:
-    draft: true
-
 minutes_to_complete: 60
 
 who_is_this_for: This is an introductory topic for automotive developers, aimed at helping them accelerate autonomous driving software development before automotive hardware is available.

content/learning-paths/cross-platform/cpp-loop-size-context/_index.md

@@ -1,10 +1,6 @@
 ---
 title: Boost C++ performance by optimizing loops with boundary information
 
-draft: true
-cascade:
-    draft: true
-
 minutes_to_complete: 15
 
 who_is_this_for: This is an introductory topic for C++ developers who want to improve the runtime of loops using existing knowledge of the loop size.

content/learning-paths/cross-platform/cpp-loop-size-context/baseline.md

@@ -33,7 +33,7 @@ int main() {
     std::cin >> max_loop_size;
 
     int x[max_loop_size];
-    // Initialise test data
+    // Initialize test data
     for(int i = 0; i < max_loop_size; ++i) x[i] = i;
 
     // Start timing

content/learning-paths/cross-platform/cpp-loop-size-context/loop-boundary-optimization.md

@@ -50,7 +50,7 @@ int main() {
 
     int max_loop_size_div_4 = max_loop_size / 4;
     int x[max_loop_size];
-    // Initialise test data
+    // Initialize test data
     for(int i = 0; i < max_loop_size; ++i) x[i] = i;
 
     // Start timing

content/learning-paths/embedded-and-microcontrollers/_index.md

@@ -10,7 +10,7 @@ key_ip:
 maintopic: true
 operatingsystems_filter:
 - Android: 1
-- Baremetal: 32
+- Baremetal: 29
 - Linux: 25
 - macOS: 5
 - RTOS: 9
@@ -19,9 +19,9 @@ subjects_filter:
 - CI-CD: 5
 - Containers and Virtualization: 6
 - Embedded Linux: 3
-- Libraries: 3
+- Libraries: 2
 - ML: 12
-- Performance and Architecture: 23
+- Performance and Architecture: 21
 - RTOS Fundamentals: 4
 - Security: 2
 - Virtual Hardware: 2
@@ -32,18 +32,18 @@ tools_software_languages_filter:
 - Arm Compiler for Embedded: 7
 - Arm Compiler for Linux: 1
 - Arm Compute Library: 1
-- Arm Development Studio: 9
+- Arm Development Studio: 7
 - Arm Fast Models: 4
-- Arm Virtual Hardware: 11
+- Arm Virtual Hardware: 10
 - AVH: 1
 - C: 1
 - C/C++: 1
 - ChatGPT: 1
 - Clang: 1
-- CMSIS: 5
+- CMSIS: 4
 - CMSIS-Toolbox: 3
 - CNN: 1
-- Coding: 29
+- Coding: 26
 - Containerd: 1
 - DetectNet: 1
 - Docker: 9
@@ -60,11 +60,11 @@ tools_software_languages_filter:
 - Himax SDK: 1
 - IP Explorer: 4
 - K3s: 1
-- Keil: 7
+- Keil: 5
 - Keil MDK: 3
 - Kubernetes: 1
 - LLM: 2
-- MDK: 2
+- MDK: 1
 - MPS3: 1
 - MXNet: 1
 - Neon: 1