arrayfire 3.8.0

ArrayFire is a high performance software library for parallel computing with an easy-to-use API. Its array based function set makes parallel programming simple. ArrayFire's multiple backends (CUDA, OpenCL and native CPU) make it platform independent and highly portable. A few lines of code in ArrayFire can replace dozens of lines of parallel computing code, saving you valuable time and lowering development costs. This crate provides Rust bindings for ArrayFire library.
Documentation

arrayfire

There is very little structured metadata to build this page from currently. You should check the main library docs, readme, or Cargo.toml in case the author documented the features in them.

This version has 18 feature flags, 16 of them enabled by default.

default

  • algorithm
  • arithmetic
  • blas
  • data
  • indexing
  • graphics
  • image
  • lapack
  • ml
  • macros
  • random
  • signal
  • sparse
  • statistics
  • vision

algorithm

    This feature flag does not enable additional features.

arithmetic

    This feature flag does not enable additional features.

blas

    This feature flag does not enable additional features.

data

    This feature flag does not enable additional features.

indexing

    This feature flag does not enable additional features.

graphics

    This feature flag does not enable additional features.

image

    This feature flag does not enable additional features.

lapack

    This feature flag does not enable additional features.

ml

    This feature flag does not enable additional features.

macros

    This feature flag does not enable additional features.

random

    This feature flag does not enable additional features.

signal

    This feature flag does not enable additional features.

sparse

    This feature flag does not enable additional features.

statistics

    This feature flag does not enable additional features.

vision

    This feature flag does not enable additional features.

afserde

  • serde

serde

    This feature flag does not enable additional features.