[GitHub] [spark] srowen commented on a change in pull request #29139: [SPARK-32339][ML][DOC] Improve MLlib BLAS native acceleration docs

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srowen commented on a change in pull request #29139:
URL: https://github.com/apache/spark/pull/29139#discussion_r456923623



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File path: docs/ml-linalg-guide.md
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+# Spark MLlib Linear Algebra Acceleration Guide
+
+## Introduction
+
+This guide provides necessary information to enable accelerated linear algebra processing for Spark MLlib.
+
+Spark MLlib defines Vector and Matrix as basic data types for machine learning algorithms. On top of them, [BLAS](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) and [LAPACK](https://en.wikipedia.org/wiki/LAPACK) operations are implemented and supported by [netlib-java](https://github.com/fommil/netlib-Java).[^1] `netlib-java` can use optimized native linear algebra libraries (refered to as "native libraries" or "BLAS libraries" hereafter) for faster numerical processing. [Intel MKL](https://software.intel.com/content/www/us/en/develop/tools/math-kernel-library.html) and [OpenBLAS](http://www.openblas.net) are two most popular ones.
+
+However due to license restrictions, the official released Spark binaries by default doesn't contain native libraries support for `netlib-java`.
+
+The following sections describe how to enable `netlib-java` with native libraries support for Spark MLlib and how to install native libraries and configure them properly.
+
+[^1]: The algorithms may call Breeze and it will in turn call `netlib-java`.
+
+## Enable `netlib-java` with native library proxies 
+
+`netlib-java` native libraries has a dependency on `libgfortran`. It requires GFORTRAN 1.4 or above. This can be obtained by installing `libgfortran` package. After installation, the following command can be used to verify if it is installed properly.

Review comment:
       Just "`netlib-java` depends on `libgfortran`."




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