Code Monkey home page Code Monkey logo

mlsl's Introduction

Intel(R) Machine Learning Scaling Library for Linux* OS

Introduction

Intel(R) Machine Learning Scaling Library (Intel(R) MLSL) is a library providing an efficient implementation of communication patterns used in deep learning.

- Built on top of MPI, allows for use of other communication libraries
- Optimized to drive scalability of communication patterns
- Works across various interconnects: Intel(R) Omni-Path Architecture,
  InfiniBand*, and Ethernet
- Common API to support Deep Learning frameworks (Caffe*, Theano*,
  Torch*, etc.)

Intel(R) MLSL package comprises the Intel MLSL Software Development Kit (SDK) and the Intel(R) MPI Library Runtime components.

SOFTWARE SYSTEM REQUIREMENTS

This section describes the required software.

Operating Systems:

- Red Hat* Enterprise Linux* 6 or 7
- SuSE* Linux* Enterprise Server 12
- Ubuntu* 16

Compilers:

- GNU*: C, C++ 4.4.0 or higher
- Intel(R) C++ Compiler for Linux* OS 16.0 through 17.0 or higher

Virtual Environments: - Docker* - KVM*

Installing Intel(R) Machine Learning Scaling Library

Installing Intel(R) MLSL by building from source:

    $ make all
    $ [MLSL_INSTALL_PATH=/path] make install

By default MLSL_INSTALL_PATH=$PWD/_install

Binary releases are available on our release page.

Installing Intel(R) MLSL using RPM Package Manager (root mode):

1. Log in as root

2. Install the package:

    $ rpm -i intel-mlsl-devel-64-<version>.<update>-<package#>.x86_64.rpm

    where <version>.<update>-<package#> is a string, such as: 2017.0-009

3. Uninstalling Intel(R) MLSL using the RPM Package Manager

    $ rpm -e intel-mlsl-devel-64-<version>.<update>-<package#>.x86_64

Installing Intel(R) MLSL using the tar file (user mode):

    $ tar zxf l_mlsl-devel-64-<version>.<update>.<package#>.tgz
    $ cd l_mlsl_<version>.<update>.<package#>
    $ ./install.sh

There is no uninstall script. To uninstall Intel(R) MLSL, delete the
full directory you have installed the package into.

Launching Sample Application

The sample application needs python with the numpy package installed. You can use [Intel Distribution for Python] (https://software.intel.com/en-us/distribution-for-python), Anaconda, or the python and numpy that comes with your OS. Before you start using Intel(R) MLSL, make sure to set up the library environment.

Use the command:

$ source <install_dir>/intel64/bin/mlslvars.sh
$ cd <install_dir>/test
$ make run

If the test fails, look in the log files in the same directory. Here <install_dir> is the Intel MLSL installation directory.

License

Intel MLSL is licensed under Apache License Version 2.0.

Optimization Notice

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804

*Other names and brands may be claimed as the property of others.

mlsl's People

Contributors

jimmycasey avatar mshiryaev avatar rscohn2 avatar shirosankaku avatar ykiryano avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.