Performance Test

[mroodschild]

Hey Lessthanoptimal,

I've been looking at a benchmark, EJML is the second fastest library. Is it time to do another full benchmark? Maybe you should include ND4J.

Merry Christmas.

https://app.cybench.io/cybench/api/java/matrices

[lessthanoptimal]

I'll start a new benchmark soon and update it. Not sure if ND4J will be included in the first pass since there are some significant issues. Doesn't seem t support many of the operations and documentation is poor. Who knows, maybe that fixed that in the past year.

deeplearning4j/deeplearning4j-examples#1003

[saudet]

BTW, PyTorch is most likely faster than ND4J, its C++ API probably comes with all operations supported by EJML, and can easily be accessed from Java with the JavaCPP Presets for PyTorch:
https://github.com/bytedeco/javacpp-presets/tree/master/pytorch

For example, Cholesky factorization and eigenvalues are documented here:
https://pytorch.org/cppdocs/api/function_namespacetorch_1_1linalg_1a68dbfd70145d5f5850e8a9aecb2a9d1c.html
https://pytorch.org/cppdocs/api/function_namespacetorch_1_1linalg_1a939c327e5926960f1e41a0b076aa85e2.html

And those functions get mapped to these Java methods:
http://bytedeco.org/javacpp-presets/pytorch/apidocs/org/bytedeco/pytorch/global/torch.html#cholesky-org.bytedeco.pytorch.Tensor-boolean-
http://bytedeco.org/javacpp-presets/pytorch/apidocs/org/bytedeco/pytorch/global/torch.html#eig-org.bytedeco.pytorch.Tensor-boolean-