#c_lang #aarch64 #arduino #arm #embedded #esp32 #esp8266 #interpreter #iot #mips #risc_v #runtime #wasi #wasm #webassembly

https://github.com/wasm3/wasm3

#vue #apple_silicon #apple_silicon_launch #arm #arm64 #compatibility #macos #wwdc

https://github.com/ThatGuySam/doesitarm

#cplusplus #arm #arm_assembly #assembly #assembly_arm #assembly_language #assembly_language_programming #assembly_x86_64 #c #c_plus_plus #cyber #cyber_security #cyber_threat_intelligence #cybersecurity #hack #hacking #malware #reverse_engineering #reverse_engineering_tutorial #x64 #x86

https://github.com/mytechnotalent/Reverse-Engineering-Tutorial

#c_lang #amd #android #arm #cpus #intel #linux #macos #microarchitecture #windows

https://github.com/Dr-Noob/cpufetch

#cplusplus #3d #3d_perception #arm #computer_graphics #cpp #cuda #gpu #gui #machine_learning #mesh_processing #odometry #opengl #pointcloud #python #pytorch #reconstruction #registration #rendering #tensorflow #visualization

https://github.com/isl-org/Open3D

#bicep #arm #azure #bicep_templates #building_block #deployment_automation #iac #microsoft #modules #platform #publishing #testing

https://github.com/Azure/ResourceModules

#c_lang #arm #baremetal #cmsis #ethernet #gcc #gpio #irq #make #stm32 #tutorial #uart #webserber

https://github.com/cpq/bare-metal-programming-guide

#rust #aarch64 #arm #bsd #cargo #cross_compilation #cross_testing #linux #mips #powerpc #s390x #sparc #windows #x86

https://github.com/cross-rs/cross

#cplusplus #arm #c #dos #dosbox #dosbox_staging #emulator #games #linux #macos #meson #opengl #sdl2 #windows #x86

https://github.com/dosbox-staging/dosbox-staging

#cplusplus #aarch64 #arm #arm64 #avx2 #avx512 #c_plus_plus #clang #clang_cl #cpp11 #gcc_compiler #json #json_parser #json_pointer #loongarch #neon #simd #sse42 #vs2019 #x64

The simdjson library is very fast and efficient for parsing JSON files. It uses special computer instructions called SIMD to parse JSON up to 4 times faster than other popular parsers. Here are the key benefits Parses JSON much quicker than other libraries.
- **Easy to Use** Ensures full JSON and UTF-8 validation without losing any data.
- **Automatic Optimization** Designed to avoid unexpected errors and surprises.

Using simdjson can significantly speed up your application's performance when dealing with large amounts of JSON data.

https://github.com/simdjson/simdjson

#cplusplus #arm #convolution #deep_learning #embedded_devices #llm #machine_learning #ml #mnn #transformer #vulkan #winograd_algorithm

MNN is a lightweight and efficient deep learning framework that helps run AI models on mobile devices and other small devices. It supports many types of AI models and can handle tasks like image recognition and language processing quickly and locally on your device. This means you can use AI features without needing to send data to the cloud, which improves privacy and speed. MNN is used in many apps, including those from Alibaba, and supports various platforms like Android and iOS. It also helps reduce the size of AI models, making them faster and more efficient.

https://github.com/alibaba/MNN

#cplusplus #arm #baidu #deep_learning #embedded #fpga #mali #mdl #mobile #mobile_deep_learning #neural_network

Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance.

https://github.com/PaddlePaddle/Paddle-Lite