Search Results for "arm-aonly"
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Showing 21 open source projects for "arm-aonly"
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opencv-mobile
The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS
The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS, WebAssembly. This project provides the minimal build of opencv library for the Android, iOS and ARM Linux platforms. Packages for Windows, Linux, MacOS, and WebAssembly are available now. We provide prebuild binary packages for opencv 2.4.13.7, 3.4.18, and 4.6.0. We also provide prebuild binary package for iOS with bitcode enabled, that the official package lacks. -
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples.... -
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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Halide
A language for fast, portable data-parallel computation
...It was designed to make writing high-performance image and array processing code much easier on modern machines. It works on all major operating systems and with several CPU architectures (X86, ARM, MIPS, Hexagon, PowerPC) and GPU Compute APIs (CUDA, OpenCL, OpenGL, among others). It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an in-memory representation of a Halide pipeline using Halide's C++ API. This representation can then be compiled to an object file, or a JIT-compile and run in the same process. ... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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CPU Features
A cross platform C99 library to get cpu features at runtime
...It enables applications to determine which instruction sets (such as SSE, AVX, or NEON) are supported on the host machine, allowing developers to optimize performance dynamically. The library supports numerous architectures—including x86, ARM, AArch64, MIPS, POWER, RISCV, LoongArch, and s390x—and works on major operating systems like Linux, macOS, Windows, FreeBSD, Android, and iOS. Implemented in portable C99, it is thread-safe, has no memory allocations, and raises no exceptions, making it suitable even for use in low-level system libraries. The design emphasizes portability, extensibility, and compatibility with sandboxed or restricted environments where direct CPU access may be limited. -
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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. It supports a wide range of AI tasks including text generation, speech-to-text, vision processing, and retrieval-augmented workflows through a unified API interface. ... -
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Xash3D FWGS Engine
Xash3D FWGS engine
Xash3D FWGS is an open-source fork and extension of the original GoldSrc-based engine (from the classic era of first-person shooters), aimed at providing compatibility with the original engine (e.g. games built on it) while extending and modernizing its capabilities. The engine supports multiple rendering backends (OpenGL, GLES, software fallback), modern platforms (desktop OSes, mobile, etc.), and updated features such as better multiplayer, voice chat, IPv6 support, improved virtual... -
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xrdp
An open source RDP server
...Session resizing (both on-connect and on-the-fly). RDP/VNC proxy (connect to another RDP/VNC server via xrdp). xrdp primarily targets GNU/Linux operating system. x86 (including x86-64) and ARM processors are most mature architecture to run xrdp on. Most Linux distributions should distribute the latest release of xrdp in their repository. -
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XNNPACK
High-efficiency floating-point neural network inference operators
XNNPACK is a highly optimized, low-level neural network inference library developed by Google for accelerating deep learning workloads across a variety of hardware architectures, including ARM, x86, WebAssembly, and RISC-V. Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. ... -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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TBOX
A glib-like multi-platform c library
...Implements the static buffer stream for parsing data. Supports coroutine and implements asynchronous operation. The coroutine library. Provides high-performance coroutine switch. Supports arm, arm64, x86, x86_64. Provides channel interfaces. Provides semaphore and lock interfaces. Supports io socket and stream operation in coroutine. Provides some io servers (http ..) using coroutine. Provides stackfull and stackless coroutines. -
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unidbg
Allows you to emulate an Android native library
Allows you to emulate an Android native library, and an experimental iOS emulation. This is an educational project to learn more about the ELF/MachO file format and ARM assembly. Emulation of the JNI Invocation API so JNI_OnLoad can be called. Support JavaVM, JNIEnv. Emulation of syscalls instruction. Support ARM32 and ARM64. Inline hook, thanks to Dobby. Android import hook, thanks to xHook. iOS fishhook and substrate and whale hook. unicorn backend support simple console debugger, gdb stub, instruction trace, memory read/write trace. ... -
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Hippy
Tool to build cross-platform and high-performance awesome apps
...Hippy is now applied in 27+ Tencent apps such as Mobile QQ, Mobile QQ Browser, Tencent Video App, QQ Music App, Tencent News, reaching hundreds of millions of ordinary users. For Android, we recommend using the real cellphone for better develop experience, because Hippy is using X5 JS engine which can't support x86 simulator, as well as ARM simulator has a low performance. For iOS, we recommend to use iOS simulator when first try. However, you can change the Xcode configuration to install the app to iPhone if you are an iOS expert. -
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Dead Deer 3.14.86.2026
3D modeler, 3D game maker, 3D demo maker
...Intel x86/64, ARMv7/ARM64, RISCV. Linux (Ubuntu/wxWidgets(Gtk3)). iOS /iPasOS (with XCode) (GLES20/METAL) Windows Phone Windows VR (Steam/Oculus) WebAsm/WebGL UWP Windows/XBOX SDL2 Linux ARM 32/64 RISCV OpenXR (Quest?/Pico) 3.14.86.2026 -
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Wildcat- Simple "C" XML reader
Wildcat: Simple "C" XML reader
A simple in C writen XML-Parser. Don't use macros or other non standard C-language extension. Object Oriented implementation. Support only single byte character sets. Tested with ARM-gcc 7.5 and Visual Studio 2019 C compiler. -
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libjpeg-turbo
SIMD-accelerated libjpeg-compatible JPEG codec library
libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, NEON, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, ARM, and PowerPC systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. In many cases, the performance of libjpeg-turbo rivals that of proprietary high-speed JPEG codecs. ... -
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Mixed Reality Toolkit
Accelerate cross-platform MR app development in Unity
...With the MRTK Examples Hub, you can try various example scenes in MRTK without building and deploying each scene. You can download pre-built app packages for HoloLens(x86), HoloLens 2(ARM), and Windows Mixed Reality immersive headsets(x64) by selecting the "Mixed Reality Toolkit Examples" package in the MR Feature Tool. MRTK provides example scenes that demonstrate how to use MRTK's features. You can find the example scenes under Assets/MRTK/Examples/Demos folder. -
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HelloSilicon
An introduction to ARM64 assembly on Apple Silicon Macs
An introduction to assembly on Apple Silicon Macs. In this repository, I will code along with the book Programming with 64-Bit ARM Assembly Language, adjusting all sample code for Apple's ARM64 line of computers. While Apple's marketing material seems to avoid a name for the platform and talks only about the M1 processor, the developer documentation uses the term "Apple Silicon". You need Xcode 12.2 or later, and to make things easier, the command line tools should be installed. ... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes... -
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FastFlow: programming multi-core
Pattern-based multi/many-core parallel programming framework
...Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on commodity multi-core. FastFlow works on x86, x86_64, PPC, ARM, and Linux, Mac and Win XP/7. From Jan 1, 2018 code development migrated on GitHub at https://github.com/fastflow/fastflow -
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builder
Easily build software for your Linux distro repo
...So instead of worrying about how to compile for autoconf, autogen, bootstrap, cmake, or the traditional configure, make, make install, for each software title in your repo, builder will take care of all those details so you can focus on the more important parts of your project! Currently, builder can compile for AMD/Intel 32 and 64 bit along with ARM v6/7 (most notably for the Raspberry PI). The available profiles will successfully build for the XiniX and TC Linux distros, but contributions from others for those variants or others are welcomed and will be added to the database for all to use! Profiles can be found at: http://repo.cliquesoft.org/vanilla/1.1/builder/ [TC|XiniX]
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