Benchmarks for Blaze, A high-performance C++ math library
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Benchmarks for Blaze, A high-performance C++ math library
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Re: Benchmarks for Blaze, A high-performance C++ math library
#2I've had great success with Blaze, despite the fact that it has received little publicity compared to alternatives like Eigen, Armadillo, etc. Blaze is consistently the leader of the pack in benchmarks, and even outperforms Intel MKL on the Xeon E5-2660 (the CPU for which the benchmark results are shown).
Re: Benchmarks for Blaze, A high-performance C++ math library
#3better link: https://bitbucket.org/blaze-lib/blaze
Re: Benchmarks for Blaze, A high-performance C++ math library
#4It would be interesting to see benchmarks of sparse operations, as well.
Re: Benchmarks for Blaze, A high-performance C++ math library
#5[deleted]
Re: Benchmarks for Blaze, A high-performance C++ math library
#6I am considering converting a C++03 math library to C++14 as a side project to learn C++14 and I examined Eigen and Blaze. Eigen's code size seems to be a fraction of Blaze, even though their functionalities are similar. Eigen also has some design documents while Blaze has papers but not much more. It seems I will try my hands on Eigen library for now. It is amazing that a couple of people could do in a few years; Blaze has hundred of thousands of lines of code.
Re: Benchmarks for Blaze, A high-performance C++ math library
#7In the first plot, why do all libraries slow down at the n=1000 mark? something to do with cache?
Re: Benchmarks for Blaze, A high-performance C++ math library
#8I am considering converting a C++03 math library to C++14 as a side project to learn C++14 and I examined Eigen and Blaze. Eigen's code size seems to be a fraction of Blaze, even though their functionalities are similar. Eigen also has some design documents while Blaze has papers but not much more. It seems I will try my hands on Eigen library for now. It is amazing that a couple of people could do in a few years; Bl…
Eigen is header only and heavily templated, which certainly keeps the source down.
However, SLOC is a poor metric for the quality of a codebase, especially scientific ones. I've certainly found many instances where longer line counts are more performant, for instance with hand-unrolling loops (very rare edge case, not suggesting doing this as a rule!).
Unless you intend to become involved in development of the library, I see no reason you would care about the lines of code. Even at that point, design philosophy, features, etc. are more likely to be major factors in your choice.
FYI: Computational Scientist here. I am neither affiliated with Blaze nor Eigen.
Re: Benchmarks for Blaze, A high-performance C++ math library
#9I am considering converting a C++03 math library to C++14 as a side project to learn C++14 and I examined Eigen and Blaze. Eigen's code size seems to be a fraction of Blaze, even though their functionalities are similar. Eigen also has some design documents while Blaze has papers but not much more. It seems I will try my hands on Eigen library for now. It is amazing that a couple of people could do in a few years; Bl…
Take a look at Armadillo as well. I did the same thing about a year ago, and looked at all of them. In the end, Armadillo made writing things very easy. Of course, I was really only focused on matrix multiplication, so you may have different requirements.
Re: Benchmarks for Blaze, A high-performance C++ math library
#10I've had great success with Blaze, despite the fact that it has received little publicity compared to alternatives like Eigen, Armadillo, etc. Blaze is consistently the leader of the pack in benchmarks, and even outperforms Intel MKL on the Xeon E5-2660 (the CPU for which the benchmark results are shown).
For what problems? General statements like this are hard to back up, especially in the wild world of numerical linear algebra.
From my experience, there are currently no good distributed-memory open source sparse-direct solvers.
No good distributed-memory ILU implementation, either. Scalability is almost non-existant beyond 100 cores.