ArrayFire v3.4 Parallel Computing Library Speeds Machine Learning
Today ArrayFire released the latest version of their ArrayFire open source library of parallel computing functions supporting CUDA, OpenCL, and CPU devices. ArrayFire v3.4 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. A complete list of ArrayFire v3.4 updates and new features can be found in the product Release Notes. “ArrayFire is a model example of how open sourcing scientific libraries should work,” said Kent Knox, Senior Member of Technical Staff from AMD. “They have made their own code open to the public for review by the…
Link to Full Article: ArrayFire v3.4 Parallel Computing Library Speeds Machine Learning
ArrayFire v3.4 Parallel Computing Library Speeds Machine Learning
