Showing 4 open source projects for "bazel"

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    Algorithms & data structures project

    Algorithms & data structures project

    A collection of algorithms and data structures

    ...Complexity information is documented for many algorithms to help users understand performance characteristics. Implementations can be compiled with a standard JDK or managed and tested through Bazel. Many topics also include companion video explanations for learners who want additional conceptual guidance.
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  • 2
    Double Conversion

    Double Conversion

    Efficient binary-decimal & decimal-binary conversion routines for IEEE

    ...The codebase includes detailed documentation and comprehensive unit tests to validate correctness across various platforms. With flexible build options using SCons, CMake, or Bazel, Double Conversion integrates seamlessly into modern C++ development workflows.
    Downloads: 0 This Week
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  • 3
    Muduo

    Muduo

    Event-driven network library for multi-threaded Linux server in C++11

    Muduo is a multithreaded C++ network library based on the reactor pattern. Use of this source code is governed by a BSD-style license that can be found in the License file. Requires Linux kernel version equal or above 2.6.28. Tested on Debian 7 and above, Unbuntu 14.04 and above, and CentOS 7 and above. Install required packages Debian, Ubuntu, etc. See .travis.yml for additional packages for building more examples.
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  • 4
    TF Quant Finance

    TF Quant Finance

    High-performance TensorFlow library for quantitative finance

    ...Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. With hardware acceleration and differentiable models, it enables modern techniques like gradient-based calibration and end-to-end learning of market dynamics.
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