xuyang1706 commented on issue #8631: [FLINK-12745][ml] add sparse and dense 
vector class, and dense matrix class with basic operations.
URL: https://github.com/apache/flink/pull/8631#issuecomment-521635674
 
 
   > > Do you have any benchmark or performance tests? it would be helpful for 
understanding performance this logic
   > 
   > I would like to compare old lineal algebra primitives (e.g. from 
https://github.com/apache/flink/tree/47db1ab7ce523390bd957380eea1f6153ffdc7c2/flink-libraries/flink-ml/src/main/scala/org/apache/flink/ml/math)
 and this implementation.
   > 
   > Also I cannot find any discussion of design and use cases for classes. Do 
we have?
   > and related to performance
   > 
   > > Did you look linear algebra entities implementations from other 
libraries? I understand the risks to use other libraries in flink, but we can 
get well tested and performance-optimized implementation of vectors and matrix 
as an improvement .
   
   @ex00 we compared with the old flinkml lineal algebra's Vector 
implementation, same vector data and repeat 10000 times. 
   
   | vector op          | org.apache.flink.ml.math | 
com.alibaba.alink.common.linalg |
   | ------------------ | ------------------------ | 
------------------------------- |
   | DenseVector dot     | 12.4s                    | 8.2s                      
      |
   | DenseVector axpy   | 10.8s                   | 9.9s                        
   |
   | DenseVector scale  | 7.5s                     | 5.9s                       
     |
   | SparseVector dot   |    15.5s                 |    11.5s                   
       |
   | SparseVector scale |  0.67s                    | 0.40s                     
      |
   
   Environment:
   *machine*
   - 2.2 GHz Intel Core i7
   - 16 GB 1600 MHz DDR3 
   - mac os
   
   *jvm*
   java version "1.8.0_121"
   Java(TM) SE Runtime Environment (build 1.8.0_121-b13)
   Java HotSpot(TM) 64-Bit Server VM (build 25.121-b13, mixed mode)

----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org


With regards,
Apache Git Services

Reply via email to