ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures including CPUs, GPUs, and other hardware acceleration devices. Several of ArrayFire’s benefits include: Easy to use, stable, well-documented API; Rigorously tested for performance and accuracy; Commercially friendly open-source licensing; Commercial support from ArrayFire; Read about more benefits on arrayfire.com. ArrayFire provides software developers with a high-level abstraction of data which resides on the accelerator, the af::array object. Developers write code which performs operations on ArrayFire arrays which, in turn, are automatically translated into near-optimal kernels that execute on the computational device. ArrayFire is successfully used on devices ranging from low-power mobile phones to high-power GPU-enabled supercomputers. ArrayFire runs on CPUs from all major vendors (Intel, AMD, ARM), GPUs from the prominent manufacturers (NVIDIA, AMD, and Qualcomm), as well as a variety of other accelerator devices on Windows, Mac, and Linux.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Mingyuan Wu, Husheng Zhou, Lingming Zhang, Cong Liu, Yuqun Zhang: Charactering and Detecting CUDA Program Bugs (2019) arXiv
- Tim Besard, Valentin Churavy, Alan Edelman, Bjorn De Sutter: Rapid software prototyping for heterogeneous and distributed platforms (2019) not zbMATH
- Zaspel, Peter: Algorithmic patterns for (\mathcalH)-matrices on many-core processors (2019)