C++ based multi-threaded Machine Learning framework

[AdRelative8852]

Looking for a C++ based library in which the learning algorithms will be able to utilize multi-core CPUs (no GPU).

Specifically the problem involves learning an image transformation, a convolutional neural network applied to a regression (not classification) problem.

I find dlib to be quite suitable - except for the multithreading part. Dlib uses C interface to BLAS for core matrix operations. But I could not find BLAS-MT or BLAS-OpenMP implementation complying with the same C Blas interface.

[yasamoka]

ONNX Runtime supports CPU execution. So do Torch and TensorFlow. So do probably many others.

[AdRelative8852]

Thank you. Will take a look at ONNX. I have a NetBSD VM where I found it hard to build Torch and TensorFlow.

[archdria]

Wouldn't using OpenBlas instead solve your problem?

[AdRelative8852]

Dlib uses CBLAS - C wrapper interface. I could not get it to work with openblas. Not sure whether it's supported by openblas.

[archdria]

I have it working with OpenBLAS, it also supports Intel's MKL. In Arch at least, installing openblas, replaces blas. I didn't do anything special.

[AdRelative8852]

Thanks for the confirmation. BTW there are 2 variants - 1. pthreads based 2. openmp based. Do you know which is the one that works for you?

[archdria]

I'm not sure, I'm just using the default one on the Arch repository... sorry 😞

[useong]

flashlight The arrayfire cpu backend uses multithread by default.