ArrayFire nighty
- API changes:
approx split into approx1 (for 1D y=f(x)) and approx2 (for 2D z=f(x,y))
ArrayFire 1.9 -- 20 Nov 2012
- CUDA 5.0 required (CUDA toolkit download now includes CUDA driver)
- API changes:
interp changed to approx
ones/zeros changed to constant
hostFree obsolete free() for all allocations: pinned(), host(), alloc()
- standardize convention for for
af_morph_t, af_resize_t, af_rprops_t, af_interp_t, af_solve_t, etc..
- New Image Processing Functions
- New pinned memory option for faster transfer
- Better performance when using erode and dilate
resize, approx1, approx2 now support linear (L), nearest neighbor (N), and cubic (C) interpolation
- Known issue: startup delay fixed in drivers 304.x and later
- Bug fixes:
ArrayFire 1.2 -- 14 June 2012
- CUDA 4.2 required
- Kepler GPU (Compute capability 3.0) support
- New machine learning examples
- Improved example directory layout
- New color space conversions colorspace() added for image processing
- Known issue: startup delay fixed in drivers 304.x and later
ArrayFire 1.1 -- 3 May 2012
- CUDA 4.1 required
- 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
- verified code samples in documentation
- added common machine-independent constants: Pi, NaN, Inf
- major work on Python and Fortran interfaces
ArrayFire 1.0 -- 14 November 2011
- CUDA 4.0 required
- See our announcement
- integers (32-bit signed and unsigned)
- sparse matrices