# Tag: Performance and Architecture

## Learning paths

- [Get started with Servers and Cloud Computing](https://learn.arm.com/learning-paths/servers-and-cloud-computing/intro/)
- [Profile Unity application performance on Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/)
- [Accelerate multimodal Voice Assistant performance with KleidiAI and SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-assistant/)
- [Generate audio with Stable Audio Open Small using ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-with-executorch/)
- [Generate audio with Stable Audio Open Small on LiteRT](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/)
- [Optimize graphics performance using Frame Advisor render graphs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/render-graph-optimization/)
- [Install and Use Arm integration packages for Unity](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/unity_packages/)
- [Explore Arm Memory Tagging Extension with an example C program](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/mte/)
- [Profile Android game performance in Godot with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/godot_packages/)
- [Accelerate matrix multiplication performance with SME2](https://learn.arm.com/learning-paths/cross-platform/multiplying-matrices-with-sme2/)
- [Optimize graphics vertex efficiency for Arm GPUs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/optimizing-vertex-efficiency/)
- [Enable Memory Tagging Extension on Google Pixel 8](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/mte_on_pixel8/)
- [Query Arm GPU configuration information](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/libgpuinfo/)
- [Debug with MTE on Google Pixel 8](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/debugging_with_mte_on_pixel8/)
- [Optimize a sample C++ application on an Arm-based server with Arm Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-get-started/)
- [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/)
- [Convert uvprojx-based projects to csolution](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/)
- [Get started with Raspberry Pi Pico](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi_pico/)
- [Migrating x86_64 workloads to aarch64](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/migration/)
- [Learn about the impact of stack buffer overflows](https://learn.arm.com/learning-paths/servers-and-cloud-computing/exploiting-stack-buffer-overflow-aarch64/)
- [Add new debug targets to Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/new_debug_targets_armds/)
- [Get started with Microcontrollers](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/intro/)
- [Deploy Elasticsearch on Azure Cobalt 100 Arm virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/elasticsearch-on-azure/)
- [Analyze a frame from an Android application with Frame Advisor](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/analyze_a_frame_with_frame_advisor/)
- [Sampling CPython with WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf_sampling_cpython/)
- [Get started with the Windows Performance Analyzer plugin for WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf_wpa_plugin/)
- [Analyze performance data with the Visual Studio extension for WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf-vs-extension/)
- [Optimize application performance using Arm Performix CPU microarchitecture analysis](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-microarchitecture/)
- [Optimize AArch64 binaries with LLVM BOLT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bolt/)
- [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/)
- [Learn about optimization techniques using the g++ compiler](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cplusplus_compilers_flags/)
- [Learn about Large System Extensions (LSE)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/lse/)
- [Implement Code level Performance Analysis using the PMUv3 plugin](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pmuv3_plugin_learning_path/)
- [Enable Arm SPE for Performix memory access analysis](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spe-on-performix/)
- [Compare Arm Neoverse and Intel x86 top-down performance analysis with PMU counters](https://learn.arm.com/learning-paths/cross-platform/topdown-compare/)
- [Optimize C++ applications on Windows on Arm using profile-guided optimization](https://learn.arm.com/learning-paths/laptops-and-desktops/win_profile_guided_optimisation/)
- [Get started with WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf/)
- [Get started with Laptops and Desktops](https://learn.arm.com/learning-paths/laptops-and-desktops/intro/)
- [Optimize AArch64 code with LLVM link-time optimization and profile-guided optimization](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pgo/)
- [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/)
- [Accelerate Denoising, Background Blur and Low-Light Camera Effects with SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/)
- [Sample Instructions with WindowsPerf and Arm SPE](https://learn.arm.com/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/)
- [Profile an Android application with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ams/)
- [Get started with Scalable Vector Extension 2 on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_sve2/)
- [Optimize image processing on Android using Halide](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_halide/)
- [Optimize SIMD code with vectorization-friendly data layout](https://learn.arm.com/learning-paths/cross-platform/vectorization-friendly-data-layout/)
- [Build and deploy multi-node Zenoh systems on Raspberry Pi](https://learn.arm.com/learning-paths/cross-platform/zenoh-multinode-ros2/)
- [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/)
- [Run Java applications on Google Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-on-axion/)
- [Learn about integer and floating-point conversions](https://learn.arm.com/learning-paths/cross-platform/integer-vs-floats/)
- [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/)
- [Memory latency for application software developers](https://learn.arm.com/learning-paths/cross-platform/memory-latency/)
- [Learn SVE and SME programming with SIMD Loops](https://learn.arm.com/learning-paths/cross-platform/simd-loops/)
- [Build an embedded application with Rust and debug with Arm Development Studio](https://learn.arm.com/learning-paths/cross-platform/rust_armds/)
- [Optimize an Adler-32 checksum function with SVE intrinsics using the Arm MCP server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/adler32-kiro/)
- [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/)
- [Use LLVM Machine Code Analyzer to analyze assembly performance on Arm](https://learn.arm.com/learning-paths/cross-platform/mca-godbolt/)
- [Run custom software for simulation with Arm IP Explorer](https://learn.arm.com/learning-paths/cross-platform/ipexplorer/)
- [Porting architecture specific intrinsics](https://learn.arm.com/learning-paths/cross-platform/intrinsics/)
- [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/)
- [Validate PAC/BTI security features in OpenJDK on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openjdk-pacbti-gcp/)
- [Understand Arm Pointer Authentication](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pac/)
- [Tune the Performance of the Java Garbage Collector](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-gc-tuning/)
- [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/)
- [Optimize exponential functions with FEXPA](https://learn.arm.com/learning-paths/servers-and-cloud-computing/fexpa/)
- [Optimize application performance with CPU affinity](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pinning-threads/)
- [Migrate containers to Arm using KubeArchInspect](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kubearchinspect/)
- [Migrate applications that leverage performance libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/using-and-porting-performance-libs/)
- [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/)
- [Microbenchmark storage performance with fio on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/disk-io-benchmark/)
- [Microbenchmark and tune network performance with iPerf3 and Linux traffic control](https://learn.arm.com/learning-paths/servers-and-cloud-computing/microbenchmark-network-iperf3/)
- [Measure and modify Go garbage collection behavior on AWS Graviton-based compute](https://learn.arm.com/learning-paths/servers-and-cloud-computing/go-gc-default-settings/)
- [Get started with parallel application development](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mpi/)
- [Get ready for performance analysis with Sysreport](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sysreport/)
- [Deploy Rust on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rust-on-gcp/)
- [Deploy Puppet on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/puppet-on-gcp/)
- [Deploy OpenTelemetry on Google Cloud C4A Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/opentelemetry/)
- [Deploy Java applications on Azure Cobalt 100 processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-on-azure/)
- [Deploy High-Performance Analytics with Apache Arrow and Arrow Flight on Google Cloud C4A Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/apache_arrow_and_flight/)
- [Deploy Golang on Azure Cobalt 100 on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/golang-on-azure/)
- [Deploy Apache Spark on Google Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/)
- [Deploy Apache Flink on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/flink-on-gcp/)
- [Deploy an AWS IoT Greengrass custom component to Arm devices and verify PAC/BTI support](https://learn.arm.com/learning-paths/cross-platform/aws-greengrass-pacbti-test/)
- [Building and Benchmarking DLRM on Arm Neoverse V2 with MLPerf](https://learn.arm.com/learning-paths/servers-and-cloud-computing/dlrm/)
- [Build Linux kernels for Arm cloud instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kernel-build/)
- [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/)
- [Benchmark Linux kernel performance on Arm servers with Fastpath](https://learn.arm.com/learning-paths/servers-and-cloud-computing/fastpath/)
- [Benchmark Go performance with Sweet and Benchstat](https://learn.arm.com/learning-paths/servers-and-cloud-computing/go-benchmarking-with-sweet/)
- [Analyze cache behavior with Perf C2C on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/false-sharing-arm-spe/)
- [Access running containers using Supervisor, SSH, and Remote.It](https://learn.arm.com/learning-paths/servers-and-cloud-computing/supervisord/)
- [Accelerate search performance with SVE2 MATCH on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve2-match/)
- [Accelerate Bitmap Scanning with Neon and SVE Instructions on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bitmap_scan_sve2/)
- [Optimize memory access behavior using Arm Performix and the Arm MCP Server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-memory-access/)
- [Identify and optimize code hotspots using Arm Performix through the Arm MCP Server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-mcp-agent/)
- [Find Code Hotspots with Arm Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cpu_hotspot_performix/)
- [Accelerate random number generation with OpenRNG and Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openrng-with-performix/)
- [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/)
- [Build and test KleidiCV on macOS](https://learn.arm.com/learning-paths/laptops-and-desktops/kleidicv-on-mac/)
- [Generate Arm Performix AI insights in Visual Studio Code with Codex](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-agentic-dynamic-insights-codex/)
- [Get started with the arm-performix agent skill for profiling and improving Arm workloads](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-llm-agent-skill/)
- [Optimize Arm applications and shared libraries with BOLT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bolt-merge/)
- [Profiling for Neoverse with Streamline CLI Tools](https://learn.arm.com/learning-paths/servers-and-cloud-computing/profiling-for-neoverse/)
- [Benchmark Arm CPU performance with Geekbench](https://learn.arm.com/learning-paths/servers-and-cloud-computing/geekbench/)
- [Profile GPT-2 inference with the Arm Performix Instruction Mix recipe](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-instruction-mix/)
- [Analyze Java performance on Arm servers using flame graphs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-perf-flamegraph/)
- [Create an Armv8-A embedded application](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/bare-metal/)
- [Design an AXI-Lite peripheral to control GPIOs](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/advanced_soc/)
- [Write Arm Assembler functions](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/asm/)
- [Learn about context switching on Arm Cortex-M processors](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/context-switch-cortex-m/)
- [Get started with Keil MDK Code Coverage](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/coverage_mdk/)
- [Get started with Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/armds/)
- [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/)
- [Learn about function multiversioning](https://learn.arm.com/learning-paths/cross-platform/function-multiversioning/)
- [Boost C++ performance by optimizing loops with boundary information](https://learn.arm.com/learning-paths/cross-platform/cpp-loop-size-context/)
- [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 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](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/)
- [Write Neon intrinsics using GitHub Copilot to improve Adler32 performance](https://learn.arm.com/learning-paths/cross-platform/adler32/)
- [Write a Dynamic Memory Allocator](https://learn.arm.com/learning-paths/cross-platform/dynamic-memory-allocator/)
- [Get started with Realm Management Extension (RME)](https://learn.arm.com/learning-paths/cross-platform/cca_rme/)
- [Get started with CCA Attestation and Veraison](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-veraison/)
- [Run an application in a Realm using the Arm Confidential Compute Architecture (CCA)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-container/)
- [How to use the Arm Performance Monitoring Unit and System Counter](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm_pmu/)
- [Explore performance gains by increasing the Linux kernel page size on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm_linux_page_size/)
- [Automate x86-to-Arm application migration using Arm MCP Server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm-mcp-server/)
- [Debug Arm Zena CSS Reference Software Stack with Arm Development Studio](https://learn.arm.com/learning-paths/automotive/zenacssdebug/)
- [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/)
- [Run Process watch on your Arm machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/processwatch/)
- [Optimize performance using Link-Time Optimization with GCC](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gcc-lto/)
- [Optimize network interrupt handling on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/irq-tuning-guide/)
- [Learn the Arm Neoverse N1 performance analysis methodology](https://learn.arm.com/learning-paths/servers-and-cloud-computing/top-down-n1/)
- [Learn how to create a virtual machine in a Realm using Arm Confidential Compute Architecture (CCA)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rme-cca-basics/)
- [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/)
- [Learn about glibc with Large System Extensions (LSE) for performance improvement](https://learn.arm.com/learning-paths/servers-and-cloud-computing/glibc-with-lse/)
- [Get started with the Neoverse Reference Design software stack](https://learn.arm.com/learning-paths/servers-and-cloud-computing/refinfra-quick-start/)
- [Get started with the Arm 5G RAN Acceleration Library (ArmRAL)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ran/)
- [Get started with Arm hardware](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/intro/)
- [Explore Thread Synchronization in the Arm memory model](https://learn.arm.com/learning-paths/servers-and-cloud-computing/memory_consistency/)
- [Enable reproducible math functions across vector extensions with Arm Performance Libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/reproducible-libamath/)
- [Debug Neoverse N2 Reference Design with Arm Development Studio](https://learn.arm.com/learning-paths/servers-and-cloud-computing/refinfra-debug/)
- [Control floating-point accuracy modes in Arm Performance Libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/)
- [Characterize the memory subsystem of an Arm Linux system using ASCT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/memory-subsystem/)
- [Characterize system performance with Arm Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-system-characterization/)