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xiepeini / mkl_wrapper_for_non_CDH

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mklWrapper

An MKL wrapper which directly bind with Intel MKL.

Setting and Testing:

  • Assume the MKL installation location is /opt/intel/mkl (you cannot just copy libmkl_rt.so).

    • Copy mkl_wrapper.jar to /opt/intel/mkl/wrapper/mkl_wrapper.jar
    • Copy mkl_wrapper.so to /opt/intel/mkl_wrapper/mkl_wrapper.so
    • By default, the MKL wrapper will search /opt/intel/mkl/wrapper to find mkl_wrapper.so. If you put it on other path, please use -Dcom.intel.mkl.wrapper=/path/to/find/mkl_wrapper.so.

  • Spark configuration. (on each node):

    • Create: /etc/ld.so.conf.d/mkl_blas.conf
    • Input: /opt/intel/mkl/lib/intel64 (your MKL library Dir) to mkl_blas.conf
    • Run: ldconfig

  • A simple sanity check to see if native MKLBLAS/LAPACK libs can be properly loaded:

    bin/spark-shell --driver-class-path $CLASSPATH:/opt/intel/mkl/wrapper/mkl_wrapper.jar

scala> import com.github.fommil.netlib.BLAS;

scala> System.setProperty("com.github.fommil.netlib.BLAS", "com.intel.mkl.MKLBLAS")

scala> System.out.println(BLAS.getInstance().getClass().getName());

   OUTPUT: com.intel.mkl.MKLBLAS

scala> import com.github.fommil.netlib.LAPACK;

scala> System.setProperty("com.github.fommil.netlib.LAPACK", "com.intel.mkl.MKLLAPACK")

scala> System.out.println(LAPACK.getInstance().getClass().getName());

   OUTPUT: com.intel.mkl.MKLLAPACK

How to use it:

  • It is simple to use this MKL Wrapper, just with the following option to submit your job.
    • -Dcom.github.fommil.netlib.BLAS=com.intel.mkl.MKLBLAS
    • -Dcom.github.fommil.netlib.LAPACK=com.intel.mkl.MKLLAPACK

Example 1 (check MKL can be successfully loaded):

  • bin/spark-submit --master spark://sr576:7077
    • --class TestMKLWrapper
    • --conf "spark.executor.extraJavaOptions=-Dcom.github.fommil.netlib.BLAS=com.intel.mkl.MKLBLAS -Dcom.github.fommil.netlib.LAPACK=com.intel.mkl.MKLLAPACK"
    • --conf "spark.executor.extraClassPath=/opt/intel/mkl/wrapper/mkl_wrapper.jar"
    • --conf "spark.executorEnv.MKL_VERBOSE=1"
    • target/scala-2.11/test-netflix-mllib_2.11-1.0.jar

Example 1 (Real test):

  • bin/spark-submit --master spark://sr576:7077
    • --class TestMKLWrapper
    • --conf "spark.executor.extraJavaOptions=-Dcom.github.fommil.netlib.BLAS=com.intel.mkl.MKLBLAS -Dcom.github.fommil.netlib.LAPACK=com.intel.mkl.MKLLAPACK"
    • --conf "spark.executor.extraClassPath=/opt/intel/mkl/wrapper/mkl_wrapper.jar"
    • target/scala-2.11/test-netflix-mllib_2.11-1.0.jar

For some MLLIB algorithm (SVD), you also need to set driver extraJavaOptions and driver extraClassPath

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