Learn to write fast and run fast on Arm
How to use the Python wrapper for CMSIS-DSP with biquads
Learn how to use the CMSIS-DSP Python wrapper, and how a CMSIS-DSP API is represented in Python.
View the guideBuilding your first embedded image
Learn how to write, compile, and run a simple program for an embedded system based on Arm technology.
View the guideRetargeting output to UART
Understand how to modify the output mechanism to use the UART capability of the target system.
View the guideCreating an event driven embedded image
This guide is the third in a collection of related guides. Learn how to write event-driven embedded system code.
View the guideChanging exception level and security state in an embedded image
This guide is the fourth in a collection of related guides. Understand how to use exceptions to move through different exception levels and switch between the Secure and Non-secure worlds.
View the guideImplement embedded continuous integration: Docker and Jenkins
Learn how to use Jenkins and Docker in a continuous integration development flow with Arm Fast Models to help minimize problems during software development and provide a consistent and automated foundation for your embedded software development work.
Learn moreImprove embedded software unit testing efficiency
Learn how to increase your unit testing throughput, by running more tests in less time.
View the guideAndroid on Arm Tutorials
Learn more with our collection of guides for Arm CPU and GPU Architecture.
Learn more64-bit Android Development
Learn more about how to make sure your app is ready to support 64-bit devices.
Learn moreAutomated performance advice for Android games
Learn more about Performance Advisor, and how to generate easy-to-read performance reports.
Learn moreLaunching performance analysis for Android CI
Learn more about Android automated performance analysis.
Learn moreGet started with Streamline
Learn how to use Streamline to capture a profile of a debuggable Android application.
View the guideGetting started with Docker
Learn how you can use Docker to simplify multi-architecture application deployment on both embedded devices and servers.
View the guideAnalyze performance on the Raspberry Pi with Arm Streamline
Explore Linux application and system performance analysis and learn how to find where a system is spending time.
View the guideDebugging and optimizing performance of applications on AWS Graviton2
Learn more about Arm AWS instances, the tools available to develop applications for Arm-based servers, and how easily they can be used in the cloud.
Learn moreGet started with Arm Fast Models
Learn how to download, license, and install Arm Fast Models, and then run an example system with a simple bare-metal hello world software application.
Learn moreGet started with Graphics Analyzer
Look at the graphics API calls in an application and identify any rendering defects.
Learn moreGet started with Streamline
Capture a profile of your application running on an unrooted Android device, and analyze it using Streamline's interactive charts and data views.
Learn moreGet started with Mali Offline Compiler
Perform offline performance analysis for shader programs.
Learn moreGet started with Performance Advisor
Generate an easy-to-read performance summary from a Streamline capture.
Learn moreAdvanced VR graphics techniques
Standalone and mobile virtual reality (VR) requires high performance and efficiency from a GPU for the highest quality end user experience. Read our guide on creating VR applications on Arm Mali GPUs with Unity.
View the guideReal-time 3D art best practices: texturing
This guide discusses texture optimizations that can help your games and look better, and run more smoothly.
View the guideReal-time 3D art best practices: geometry
This guide highlights some key geometry optimizations for 3D assets. Geometry optimizations can make a game both more efficient, and perform better on mobile platforms.
View the guideReal-time 3D art best practices: materials and shaders
This guide discusses material and shader optimizations that can help your games to look great, and run more efficiently.
View the guideConfigure the Arm NN SDK build environment
This guide shows you how to download and configure Arm NN from start to finish so that you can use the TensorFlow Lite and ONNX frameworks with Arm NN.
View the guideCross-Compiling Arm NN for the Raspberry Pi and TensorFlow
Work around the limited memory of the Raspberry Pi by cross-compiling Arm NN and TensorFlow.
View the guide
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| Answered | Keil MDK 5 – useful links that help getting started Latest 1 months ago by rkopsch | 3 replies 2595 views |
| Answered | Forum FAQs Latest 3 months ago by Oliver Beirne | 1 replies 1599 views |
| Answered | Forum FAQs Latest 3 months ago by Oliver Beirne | 1 replies 1337 views |
| Answered | Forum FAQs Latest 3 months ago by Oliver Beirne | 1 replies 2373 views |
| Answered | Forum FAQs Latest 3 months ago by Oliver Beirne | 1 replies 1242 views |
| Answered | Where should I ask my question? Latest 8 months ago by Andy Neil | 5 replies 11744 views |