Showing 4 open source projects for "android arm"

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  • 1
    Unicorn Engine

    Unicorn Engine

    Unicorn CPU emulator framework (ARM, AArch64, M68K, Mips, Sparc

    ...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.
    Downloads: 1 This Week
    Last Update:
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  • 2
    Capstone

    Capstone

    Capstone disassembly/disassembler framework

    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...
    Downloads: 5 This Week
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  • 3
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    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...
    Downloads: 5 This Week
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  • 4
    MACE

    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...
    Downloads: 0 This Week
    Last Update:
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