swMATH ID: 28758
Software Authors: Yalamanchili, P, Arshad, U, Mohammed, Z, Garigipati, P, Entschev, P, Kloppenborg, B, James, J and Melonakos, J
Description: 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.
Homepage: http://arrayfire.com/the-arrayfire-library/
Source Code:  https://github.com/arrayfire/arrayfire
Related Software: CUDA; Thrust; TensorFlow; GitHub; Chapel; Legion; UPC++; Kokkos; Trilinos; OpenACC; PyTorch; Numba; Python; Slurm; DistributedArrays.jl; ForwardDiff; CUBLAS; CUDAnative.jl; Julia; CuArrays.jl
Cited in: 1 Document

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1 Zaspel, Peter

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