# Tag: Advanced

## Learning paths

- [Integrate a KleidiAI SME2 kernel into XNNPACK](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/integrate-kleidiai-kernel-xnnpack-qd8-f16-qc4w/)
- [Classify pet images with DeiT-Tiny and Arm VGF using ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/deploy-deit-tiny-with-vgf/)
- [Train and evaluate Neural Frame Rate Upscaling models using Model Gym](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/model-training-gym-nfru/)
- [Analyze Neural Frame Rate Upscaling using Project Moku](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/nfru-cases-study/)
- [Accelerate matrix multiplication performance with SME2](https://learn.arm.com/learning-paths/cross-platform/multiplying-matrices-with-sme2/)
- [Deploy Unity Machine Learning Agents on Arm Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/using_unity_machine_learning_agents/)
- [Deploy a LLM-based vision chatbot with PyTorch and Hugging Face transformers on Google Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/llama-vision/)
- [Explore thread synchronization in the Arm memory model](https://learn.arm.com/learning-paths/servers-and-cloud-computing/memory_consistency/)
- [Get started with parallel application development](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mpi/)
- [Deploy Memcached as a cache for MySQL and PostgreSQL on Arm-based servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/memcached_cache/)
- [Characterize the memory subsystem of an Arm Linux system using ASCT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/memory-subsystem/)
- [Decode low-bit weights with Arm SME2 lookup-table instructions](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/luti/)
- [Learn SVE and SME programming with SIMD Loops](https://learn.arm.com/learning-paths/cross-platform/simd-loops/)
- [Porting architecture specific intrinsics](https://learn.arm.com/learning-paths/cross-platform/intrinsics/)
- [Learn how to tune Redis](https://learn.arm.com/learning-paths/servers-and-cloud-computing/redis_tune/)
- [Run parallel vision inference on an Alif Ensemble E8 with Zephyr](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/alif-dual-npu-vision/)
- [Detect and resolve false sharing in Java on Arm Neoverse](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-detect-false-sharing/)
- [Profile llama.cpp performance with Arm Streamline and KleidiAI LLM kernels](https://learn.arm.com/learning-paths/servers-and-cloud-computing/llama_cpp_streamline/)
- [Deploy a Kafka Cluster on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kafka/)
- [Build Linux kernels for Arm cloud instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kernel-build/)
- [Increase application performance with libhugetlbfs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/libhugetlbfs/)
- [Deploy Apache Kafka on Arm-based Microsoft Azure Cobalt 100 virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kafka-azure/)
- [Deploy and validate Jenkins on Arm-based cloud servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/jenkins/)
- [Convert SmolVLA to ExecuTorch for inference on Arm CPUs](https://learn.arm.com/learning-paths/laptops-and-desktops/smolvla-executorch-conversion/)
- [Migrate x86 workloads to Arm on Google Kubernetes Engine with Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gke-multi-arch-axion/)
- [Learn how to migrate an x86 application to multi-architecture with Arm-based on Google Axion Processor on GKE](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gke-multi-arch/)
- [Create an Arm-based Kubernetes cluster on Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gke/)
- [Benchmark Linux kernel performance on Arm servers with Fastpath](https://learn.arm.com/learning-paths/servers-and-cloud-computing/fastpath/)
- [Identify and optimize code hotspots using the Arm Performix MCP server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-mcp-agent/)
- [Learn about glibc with Large System Extensions for performance improvement](https://learn.arm.com/learning-paths/servers-and-cloud-computing/glibc-with-lse/)
- [Compare KleidiCV Gaussian blur performance across Neon, SVE2, and SME on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/explore-kleidicv-gaussian-blur-on-android/)
- [Use Clair to scan container images and generate vulnerability reports](https://learn.arm.com/learning-paths/servers-and-cloud-computing/clair/)
- [Understand Arm Pointer Authentication](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pac/)
- [Tune PostgreSQL performance on Arm-based platforms](https://learn.arm.com/learning-paths/servers-and-cloud-computing/postgresql_tune/)
- [Tune NGINX performance on Arm-based platforms](https://learn.arm.com/learning-paths/servers-and-cloud-computing/nginx_tune/)
- [Tune MySQL performance on Arm-based platforms](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mysql_tune/)
- [Run Spark applications on Microsoft Azure Cobalt 100 processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-azure/)
- [Run Apache Spark SQL workloads on Azure Cobalt 100 Arm64 using Gluten and Velox for accelerated analytics](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-velox-cobalt/)
- [Perform Sentiment Analysis on X on Arm-based EKS clusters](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/)
- [Optimize application performance with CPU affinity](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pinning-threads/)
- [Migrate applications between Arm platforms using Kiro Arm SoC Migration Power](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm-soc-migration-learning-path/)
- [Migrate and optimize a .NET nopCommerce application on Microsoft Azure](https://learn.arm.com/learning-paths/servers-and-cloud-computing/dotnet-migration-nopcommerce/)
- [Migrate a .NET application to Azure Cobalt 100](https://learn.arm.com/learning-paths/servers-and-cloud-computing/dotnet-migration/)
- [Learn how to tune Envoy](https://learn.arm.com/learning-paths/servers-and-cloud-computing/envoy_tune/)
- [Learn how to build and deploy a multi-architecture application on Amazon EKS](https://learn.arm.com/learning-paths/servers-and-cloud-computing/eks-multi-arch/)
- [Develop and Validate Firmware Pre-Silicon on Arm Neoverse CSS V3](https://learn.arm.com/learning-paths/servers-and-cloud-computing/neoverse-rdv3-swstack/)
- [Deploy Tinkerblox UltraEdge HPC-I for AI and mixed workloads on Arm](https://learn.arm.com/learning-paths/cross-platform/tinkerblox_ultraedge/)
- [Deploy Redis as a cache for MySQL and PostgreSQL on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/redis_cache/)
- [Deploy Phi-4-mini model with ONNX Runtime on Azure Cobalt 100](https://learn.arm.com/learning-paths/servers-and-cloud-computing/onnx/)
- [Deploy Arm virtual machines on Microsoft Azure with Terraform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/azure-terraform/)
- [Deploy Arm Instances on Oracle Cloud Infrastructure (OCI) using Terraform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/oci-terraform/)
- [Deploy Arm Instances on AWS using Terraform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/aws-terraform/)
- [Deploy Apache Spark on Google Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/)
- [Deploy an Amazon EKS cluster with AWS Graviton-based nodes using Rafay](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rafay-eks/)
- [Deploy a RAG-based Chatbot with llama-cpp-python using KleidiAI on Google Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rag/)
- [Deploy a mixed-placement AI shopping assistant on Google Kubernetes Engine with Axion-based compute](https://learn.arm.com/learning-paths/servers-and-cloud-computing/storefront-ai-assistant-gke-axion/)
- [Deploy a .NET application on Microsoft Azure Cobalt 100 VMs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/azure-cobalt-cicd-aks/)
- [Create an Azure Linux 3.0 virtual machine with Cobalt 100 processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/azure-vm/)
- [Create an Arm-based Kubernetes cluster on Microsoft Azure Kubernetes Service](https://learn.arm.com/learning-paths/servers-and-cloud-computing/aks/)
- [Build NVIDIA JetPack Yocto images for Jetson Orin NX, Orin Nano, and Thor platforms](https://learn.arm.com/learning-paths/cross-platform/nvidia-jetpack-yocto-build/)
- [Build multi-architecture applications with Red Hat OpenShift Pipelines on AWS](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openshift/)
- [Build and share Docker images using AWS CodeBuild](https://learn.arm.com/learning-paths/servers-and-cloud-computing/codebuild/)
- [Build a CI/CD pipeline with GitLab on Google Axion](https://learn.arm.com/learning-paths/cross-platform/gitlab/)
- [Build a CCA Attestation Service on AWS with Veraison](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-veraison-aws/)
- [Benchmark QuantLib on Azure Cobalt](https://learn.arm.com/learning-paths/servers-and-cloud-computing/quantlib/)
- [Automate x86 to Arm Migration with Docker MCP Toolkit, VS Code and GitHub Copilot](https://learn.arm.com/learning-paths/servers-and-cloud-computing/docker-mcp-toolkit/)
- [Automate x86-to-Arm application migration using Arm MCP Server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm-mcp-server/)
- [Train multi-agent reinforcement learning policies with MAPPO on an Arm-based cloud instance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/train-mappo-navigation-arm-cloud/)
- [Run Confidential Containers with encrypted images using Arm CCA and Trustee](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-kata/)
- [Run an end-to-end attestation flow with Arm CCA and Trustee](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-trustee/)
- [Run an end-to-end Attestation Flow with Arm CCA](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-essentials/)
- [Explore secure device attach in Arm CCA Realms](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-device-attach/)
- [Understand KleidiAI SME2 matmul microkernels](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/kai_sme2_matmul_ukernel_explained/)
- [Export and quantize SmolVLA for ONNX Runtime on Arm](https://learn.arm.com/learning-paths/cross-platform/smolvla-onnx-conversion/)
- [Fine-tune SmolVLA for an SO-101 pick-and-place task on an NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/finetune-smolvla-lerobot/)
- [Quantize neural upscaling models with ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/quantize-neural-upscaling-models/)
- [Optimize Unity applications on Android using Neon intrinsics](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/using-neon-intrinsics-to-optimize-unity-on-android/)
- [Implement ray tracing effects with Vulkan on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ray_tracing/)
- [Enable neural graphics using ML Extensions for Vulkan](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/vulkan-ml-sample/)
- [Build a Sentiment-Aware Voice Assistant with On-Device LLMs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-sentiment-analysis-with-llm/)
- [Prepare models for neural graphics with Arm neural technology](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/preparing-models-for-nt/)
- [Run ExecuTorch Llama 3.2 1B Instruct on an Android phone with Vulkan](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/executorch-vulkan-learning-path/)
- [Profile ONNX model performance with SME2 using KleidiAI and ONNX Runtime](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/performance_onnxruntime_kleidiai_sme2/)
- [Measure LLM inference performance with KleidiAI and SME2 on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/performance_llama_cpp_sme2/)
- [Run LLM inference on Android with KleidiAI, MediaPipe, and XNNPACK](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/kleidiai-on-android-with-mediapipe-and-xnnpack/)
- [Benchmark a KleidiAI micro-kernel in ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/measure-kleidiai-kernel-performance-on-executorch/)
- [Accelerate LiteRT Models on Android with KleidiAI and SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/litert-sme/)
- [Get started with Arm Accuracy Super Resolution](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/get-started-with-arm-asr/)
- [Deploy optimized ML models with ONNX Runtime on Arm platforms](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/)
- [Optimize graphics vertex efficiency for Arm GPUs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/optimizing-vertex-efficiency/)
- [Advance robotics reinforcement learning with Isaac Lab on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_isaac_robotics2/)
- [Build Robot Simulation and Reinforcement Learning Workflows with Isaac Sim and Isaac Lab on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_isaac_robotics/)
- [Fine-tune neural graphics models using Model Gym](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/model-training-gym/)
- [Debug with MTE on Google Pixel 8](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/debugging_with_mte_on_pixel8/)
- [Start debugging with µVision](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/uv_debug/)
- [Profile the Linux kernel with Arm Streamline](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/streamline-kernel-module/)
- [Install tools on the command line using vcpkg](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/vcpkg-tool-installation/)
- [Convert uvprojx-based projects to csolution](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/)
- [Build embedded Linux applications on an Arm server](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-mxnet/)
- [Build and run a letter recognition NN model on an STM32L4 Discovery board](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/tflow_nn_stcube/)
- [Migrating x86_64 workloads to aarch64](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/migration/)
- [Build and run an image classification NN model on an STM32L4 Discovery board](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/img_nn_stcube/)
- [Migrating Projects to CMSIS v6](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/project-migration-cmsis-v6/)
- [Migrating CMSIS-Packs to CMSIS v6](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/pack-migration-cmsis-v6/)
- [Learn about the impact of stack buffer overflows](https://learn.arm.com/learning-paths/servers-and-cloud-computing/exploiting-stack-buffer-overflow-aarch64/)
- [Implement post-quantum cryptography on Arm Cortex-M4](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/pqc_pqm4/)
- [Get started with Windows Subsystem for Linux on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/wsl2/)
- [Learn about the C++ memory model for porting applications to Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm-cpp-memory-model/)
- [Implement Code level Performance Analysis using the PMUv3 plugin](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pmuv3_plugin_learning_path/)
- [Compare Arm Neoverse and Intel x86 top-down performance analysis with PMU counters](https://learn.arm.com/learning-paths/cross-platform/topdown-compare/)
- [Run Phi-3 on Windows on Arm using ONNX Runtime](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/)
- [Extend OpenClaw for a local-first AI assistant across Arm platforms](https://learn.arm.com/learning-paths/laptops-and-desktops/openclaw_continuum/)
- [Measure and compare performance per watt on an Arm Linux system](https://learn.arm.com/learning-paths/servers-and-cloud-computing/perf-per-watt/)
- [Secure Realms during boot using Arm Confidential Compute Architecture BootSync](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-bootsync/)
- [Build a Hands-Free Selfie Android Application with MediaPipe](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-android-selfie-app-using-mediapipe-multimodality/)
- [Learn about Arm Fixed Rate Compression (AFRC)](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/afrc/)
- [Build an Android chat application with ONNX Runtime API](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-android-chat-app-using-onnxruntime/)
- [Build and profile a simple WebGPU Android Application](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_webgpu_dawn/)
- [Optimize SIMD code with vectorization-friendly data layout](https://learn.arm.com/learning-paths/cross-platform/vectorization-friendly-data-layout/)
- [Use SIMD.info to port SIMD intrinsics across Arm architectures](https://learn.arm.com/learning-paths/cross-platform/simd-info-demo/)
- [Understand the `restrict` keyword in C99](https://learn.arm.com/learning-paths/cross-platform/restrict-keyword-c99/)
- [Learn about integer and floating-point conversions](https://learn.arm.com/learning-paths/cross-platform/integer-vs-floats/)
- [Install Arch Linux with the i3 window manager on a Pinebook Pro](https://learn.arm.com/learning-paths/laptops-and-desktops/pinebook-pro/)
- [Memory latency for application software developers](https://learn.arm.com/learning-paths/cross-platform/memory-latency/)
- [Develop a native C++ library on an Arm-based machine](https://learn.arm.com/learning-paths/cross-platform/matrix/)
- [Write SIMD code on Arm using Rust](https://learn.arm.com/learning-paths/cross-platform/simd-on-rust/)
- [Profile ExecuTorch models with SME2 on Arm](https://learn.arm.com/learning-paths/cross-platform/sme-executorch-profiling/)
- [Optimize C and C++ code using compiler autovectorization techniques](https://learn.arm.com/learning-paths/cross-platform/loop-reflowing/)
- [Migrate x86-64 SIMD to Arm64](https://learn.arm.com/learning-paths/cross-platform/vectorization-comparison/)
- [Create and train a PyTorch model for digit classification using the MNIST dataset](https://learn.arm.com/learning-paths/cross-platform/pytorch-digit-classification-arch-training/)
- [Build a multimodal retail restocking assistant on Armv9 with MNN](https://learn.arm.com/learning-paths/cross-platform/multimodel_mnn_v9/)
- [Use AWS Lambda for IoT applications running on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_lambda/)
- [Use Amazon DynamoDB for your IoT applications running on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_dynamodb/)
- [Run ASP.NET Core Web Server on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_asp_net8/)
- [Orchestrate a persistent local AI agent with Hermes on NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_persistent_agent/)
- [Fine-tune PyTorch models on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/pytorch-finetuning-on-spark/)
- [Build an offline voice chatbot with faster-whisper and vLLM on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_voicechatbot/)
- [Adding Memory Tagging to a Dynamic Memory Allocator](https://learn.arm.com/learning-paths/laptops-and-desktops/memory-tagged-dynamic-memory-allocator/)
- [Use Amazon S3 for your IoT applications running Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_s3/)
- [Build a RAG pipeline on Arm-based NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_rag/)
- [Integrate AWS Lambda with DynamoDB for IoT applications running Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb/)
- [Create IoT applications with Windows on Arm and AWS IoT Core](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot/)
- [Optimize Arm applications and shared libraries with BOLT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bolt-merge/)
- [Run image classification on an Alif Ensemble E8 DevKit using ExecuTorch and Ethos-U85](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/alif-image-classification/)
- [Getting started with CMSIS-DSP using Python](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cmsisdsp-dev-with-python/)
- [Build IoT Solutions in Azure for Arm Devices](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/azure-iot/)
- [Use the Eigen Linear Algebra Library on Arm](https://learn.arm.com/learning-paths/cross-platform/eigen-linear-algebra-on-arm/)
- [Understand floating-point behavior across x86 and Arm architectures](https://learn.arm.com/learning-paths/cross-platform/floating-point-behavior/)
- [Run ERNIE-4.5 Mixture of Experts model on Armv9 with llama.cpp](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/)
- [Learn about function multiversioning](https://learn.arm.com/learning-paths/cross-platform/function-multiversioning/)
- [How to use the Arm Performance Monitoring Unit and System Counter](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm_pmu/)
- [Prototype safety-critical isolation for autonomous driving systems on Neoverse](https://learn.arm.com/learning-paths/automotive/openadkit2_safetyisolation/)
- [Tune network workloads on Arm-based bare-metal instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/)
- [Simulate OpenBMC and UEFI pre-silicon on Neoverse RD-V3](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openbmc-rdv3/)
- [Learn about Neoverse Non-cache PMU events using C and Assembly Language](https://learn.arm.com/learning-paths/servers-and-cloud-computing/triggering-pmu-events-2/)
- [Learn about Neoverse Cache PMU Events using C and Assembly Language](https://learn.arm.com/learning-paths/servers-and-cloud-computing/triggering-pmu-events/)
- [Debug Neoverse N2 Reference Design with Arm Development Studio](https://learn.arm.com/learning-paths/servers-and-cloud-computing/refinfra-debug/)