Peng Meng created SPARK-21389: --------------------------------- Summary: ALS recommendForAll optimization uses Native BLAS Key: SPARK-21389 URL: https://issues.apache.org/jira/browse/SPARK-21389 Project: Spark Issue Type: Improvement Components: ML, MLlib Affects Versions: 2.3.0 Reporter: Peng Meng
In Spark 2.2, we have optimized ALS recommendForAll, which uses a handwriting matrix multiplication, and get the topK items for each matrix. The method effectively reduce the GC problem. However, Native BLAS GEMM, like Intel MKL, and OpenBLAS, the performance of matrix multiplication is about 10X comparing with handwriting method. I have rewritten the code of recommendForAll with GEMM, and got about 20%-30% improvement comparing with the master recommendForAll method. Will clean the code and submit for discussion. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org