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[SPARK-21305][ML][MLLIB]Add options to disable multi-threading of native BLAS #18551

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[SPARK-21305][ML][MLLIB]Add options to disable multi-threading of native BLAS #18551

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d0d94e1
disable multi-threading in spark-env.sh
Jul 6, 2017
adfa6f1
revise the doc
Jul 6, 2017
08e900b
revise the doc
Jul 6, 2017
7ef8b80
add link
Jul 6, 2017
a4d4f50
add OpenBlas multi-threading introduction
Jul 6, 2017
141d92d
add recommended setting for native blas link
Jul 11, 2017
e01a613
fix ml-guide.md
Jul 11, 2017
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4 changes: 4 additions & 0 deletions conf/spark-env.sh.template
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Expand Up @@ -61,3 +61,7 @@
# - SPARK_IDENT_STRING A string representing this instance of spark. (Default: $USER)
# - SPARK_NICENESS The scheduling priority for daemons. (Default: 0)
# - SPARK_NO_DAEMONIZE Run the proposed command in the foreground. It will not output a PID file.
# Options for native BLAS, like Intel MKL, OpenBLAS, and so on.
# You might get better performance to enable these options if using native BLAS (see SPARK-21305).
# - MKL_NUM_THREADS=1 Disable multi-threading of Intel MKL
# - OPENBLAS_NUM_THREADS=1 Disable multi-threading of OpenBLAS
6 changes: 6 additions & 0 deletions docs/ml-guide.md
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Expand Up @@ -61,6 +61,12 @@ To configure `netlib-java` / Breeze to use system optimised binaries, include
project and read the [netlib-java](https://github.com/fommil/netlib-java) documentation for your
platform's additional installation instructions.

The most popular native BLAS such as [Intel MKL](https://software.intel.com/en-us/mkl), [OpenBLAS](http://www.openblas.net), can use multiple threads in a single operation, which can conflict with Spark's execution model.

Configuring these BLAS implementations to use a single thread for operations may actually improve performance (see [SPARK-21305](https://issues.apache.org/jira/browse/SPARK-21305)). It is usually optimal to match this to the number of cores each Spark task is configured to use, which is 1 by default and typically left at 1.

Please refer to resources like the following to understand how to configure the number of threads these BLAS implementations use: [Intel MKL](https://software.intel.com/en-us/articles/recommended-settings-for-calling-intel-mkl-routines-from-multi-threaded-applications) and [OpenBLAS](https://github.com/xianyi/OpenBLAS/wiki/faq#multi-threaded).

To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4 or newer.

[^1]: To learn more about the benefits and background of system optimised natives, you may wish to
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