Search Results for "android arm"

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...

...Native support for Windows & *nix (with macOS, Linux, Android, *BSD & Solaris confirmed). High performance by using the Just-In-Time compiler technique. Support fine-grained instrumentation at various levels. Thread-safe by design. Distributed under free software license GPLv2. Another significant change on this version is the addition of some new APIs to allow better control on how the core engine works.

Capstone is a disassembly framework with the target of becoming the ultimate disasm engine for binary analysis and reversing in the security community. Created by Nguyen Anh Quynh, then developed and maintained by a small community, Capstone offers some unparalleled features. Support multiple hardware architectures: ARM, ARM64 (ARMv8), Ethereum VM, M68K, Mips, MOS65XX, PPC, Sparc, SystemZ, TMS320C64X, M680X, XCore and X86 (including X86_64). Having clean/simple/lightweight/intuitive...

MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR...

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...