Today we are pleased to announce the release of ArrayFire v3.4, our open source library of parallel computing functions supporting CUDA, OpenCL, and CPU devices. This new version of ArrayFire improves features and performance for applications in machine learning, computer vision, signal processing, statistics, finance, and more.
This release focuses on 5 major components of the library that are common to many areas of mathematical, scientific, and financial computing: sparse matrix operations, random number generation, image processing, just-in-time (JIT) compilation, and visualizations.
Major Updates and Features
- Sparse Matrix and BLAS (see blog post)
- Support for CSR and COO storage types
- Sparse-Dense Matrix Multiplication and Matrix-Vector Multiplication
- Conversion to and from dense matrix to CSR and COO storage types
- Support for Random Number Generator Engines (see blog post)
- Mersenne Twister
- Image Processing (see blog post)
- New interpolation functions
- Image moments
- Faster JIT for CUDA and OpenCL (see blog post)
- Performance improvements
- Support for evaluating multiple outputs in a single kernel
- Improvements to Graphics (see blog post)
- Using Forge v0.9.0
- Vector Field plotting functionality
- Multiple overlays on the same window are now possible
- New API to set axes limits for graphs
- New API for plot and scatter
For the comprehensive list of new features and updates, please refer to our release notes.
While we are happy for reaching this milestone, we are not complacent. Work on the next milestone has already commenced, and we hope to exceed the expectations of our community.
ArrayFire v3.4 can be downloaded from these locations:
ArrayFire is continually improving through the addition of new functions and features. We welcome your feedback:
- General discussion forums on the ArrayFire Google Group
- Live discussion chat on the ArrayFire Gitter
- Issue reports on the ArrayFire GitHub
Finally, as you find success with ArrayFire, we invite you to contribute a post to this blog to share with the broader community. Email firstname.lastname@example.org to contribute to this blog.