MKL Accelerated Math Libraries for Java...

Question

I've looked at the related threads on StackOverflow and Googled with not much luck. I'm also very new to Java (I'm coming from a C# and .NET background) so please bear with me. There is so much available in the Java world it's pretty overwhelming.

I'm starting on a new Java-on-Linux project that requires some heavy and highly repetitious numerical calculations (i.e. statistics, FFT, Linear Algebra, Matrices, etc.). So maximizing the performance of the mathematical operations is a requirement, as is ensuring the math is correct. So hence I have an interest in finding a Java library that perhaps leverages native acceleration such as MKL, and is proven (so commercial options are definitely a possibility here).

In the .NET space there are highly optimized and MKL accelerated commercial Mathematical libraries such as Centerspace NMath and Extreme Optimization. Is there anything comparable in Java?

Most of the math libraries I have found for Java either do not seem to be actively maintained (such as Colt) or do not appear to leverage MKL or other native acceleration (such as Apache Commons Math).

I have considered trying to leverage MKL directly from Java myself (e.g. JNI), but me being new to Java (let alone interoperating between Java and native libraries) it seemed smarter finding a Java library that has already done this correctly, efficiently, and is proven.

Again I apologize if I am mistaken or misguided (even in regarding any libraries I've mentioned) and my ignorance of the Java offerings. It's a whole new world for me coming from the heavily commercialized Microsoft stack so I could easily be mistaken on where to look and regarding the Java libraries I've mentioned. I would greatly appreciate any help or advice.

Answer 1

You'd probably be better off avoiding them I think. I could be wrong, it's not a bit I'm too familiar with, so don't take too much from this unless a few others agree with me, but calling up the JNI has quite a large overhead, since it has to go outside of the JRE and everything to do it, so unless you're grouping a lot of things together into a single function to put through at once, the slight benefit of the external library's will be outweighed hugely by the cost of calling them. I'd give up looking for an MKL library and find an optimized pure Java library. I can't say I know of any better than the standard one to recommend though, sorry.

Answer 2

For things like FFT (bulk operations on arrays), the range check in java might kill your performance (at least recently it did). You probably want to look for libraries which optimize the provability of their index bounds.

According to the The HotSpot spec

The Java programming language specification requires array bounds checking to be performed with each array access. An index bounds check can be eliminated when the compiler can prove that an index used for an array access is within bounds.

I would actually look at JNI, and do your bulk operations there if they are individually very large. The longer the operation takes (i.e. solving a large linear system, or large FFT) the more its worth it to use JNI (even if you have to memcpy there and back).

Answer 3

Personally, I agree with your general approach, offloading the heavyweight maths from Java to a commercial-grade library.

Googling around for Java / MKL integration I found this so what you propose is technically possible. Another option to consider would be the NAG libraries. I use the MKL all the time, though I program in Fortran so there are no integration issues. I can certainly recommend their quality and performance. We tested, for instance, the MKL version of FFTW against a version we built from sources ourselves. The MKL implementation was faster by a small integer multiple.

If you have concerns about the performance of calling a library through JNI, then you should plan to structure your application to make fewer larger calls in preference to more smaller ones. As to the difficulties of using JNI, my view (I've done some JNI programming) is that the initial effort you have to make in learning how to use the interface will be well rewarded.

I note that you don't seem to be overwhelmed yet with suggestions of what Java maths libraries you could use. Like you I would be suspicious of research-quality, low-usage Java libraries trawled from the net.