Showing 3 open source projects for "large integer factorization"

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  • 1
    Annoy

    Annoy

    Approximate Nearest Neighbors in C++/Python optimized for memory usage

    Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given query point. It also creates large read-only file-based data structures that are mmapped into memory so that many processes may share the same data. There are some other libraries to do nearest neighbor search. Annoy is almost as fast as the fastest libraries, (see below), but there is actually another feature that really sets Annoy apart: it has the...
    Downloads: 1 This Week
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  • 2
    Albedo

    Albedo

    A recommender system for discovering GitHub repos

    Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. ...
    Downloads: 0 This Week
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  • 3

    FFT for ARMv6

    Fixed point 16/32 integer FFT library for the Raspberry Pi and Android

    This library is being created as I have a need to do very fast FFTs on low end devices not supporting the NEON instruction set. The Raspberry Pi is an ideal candidate for developing in gcc before porting to JNI for low spec Android devices, hence it's inclusion. Fixed point 16/32 integer FFT library suitable for the Raspberry Pi and Android devices. Includes test stubs for gcc on the Raspberry Pi and a Basic4Android wrapper from JNI. It includes hand optimised ARMv6 assembler, demonstrating techniques such as pipeline stuffing to achieve maximum performance. It also demonstrates how to include large chunks of assembler inline with C/C++ thus avoiding ABI issues between platforms.
    Downloads: 0 This Week
    Last Update:
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