ArrayFire 1.1 has been released

[Old posts from the commercial version of ArrayFire] Discussion of ArrayFire using CUDA or OpenCL.

Moderator: pavanky

ArrayFire 1.1 has been released

Postby pavanky » Tue May 08, 2012 3:13 pm

ArrayFire 1.1 has been released for with updated versons for C/C++, Fortran and Python.

C/C++ Documentation and Release Notes
CUDA 4.1 support and performance enhancements (see more)
API changes
-- switch operator*() to matrix multiply by default (instead of element-wise, see more)
-- newdims() switched to reshape()
-- convert() switched to as() and asfloat()
-- alltrue() switched to all()
-- allfalse() switched to any()
-- mpow() switched to matpow()
-- std() switched to stdev()
-- afDevicePointer and afHostPointer have changed to afDevice and afHost

- extended and organized documentation
- simplified and verified all examples
-- support for both Windows Visual 2008 and 2010
-- use timeit() where possible
- integer rand()
- expanded licensing documentation
- expanded Graphics documentation
- various complex operations added
- various subscripting bug fixes and performance enhancements
- documented gfor usage and limitations
- Improved code samples in documentation
- added common machine-independent constants: Pi, NaN, Inf

Python Documentation and Release Notes
API Changes
- * operator now performs element wise multiplication not Matrix multiply
- matmul() is introduced for Matrix multiplication
- reshape() has been moved from a method to a function

New additions
- join() function has been added. Supports joining two matrices.
- det() routine has been added.
- Factorizations now returns complete factorization information
-- lu() now returns L (lower), U (upper), p (permutation) matrices
-- qr() now returns Q (Orthogonal), R (upper triangular) matrices

Bug fixes
-pinv() (psuedo inverse) now satisfies all Moore-Penrose conditions

Fortran Documentation and Release Notes
API Changes
- rand is now renamed as randu.
- rand(num), randn(num), ones(num), zeros(num) no longer supported.
- lu_inplace and cholesky_inplace now overload lu and cholesky.

New features
- Double precision and complex support added.
- Relational operations (<, >, ==, /=)
- Logical operations (.and., .or., .not.)
- Array Indexing
- New Data Analysis functions
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