Release Notes

# v3.4.0

## Major Updates

- Sparse Matrix and BLAS. 1 2
- Faster JIT for CUDA and OpenCL. 1 2
- Support for random number generator engines. 1 2
- Improvements to graphics. 1 2

## Features

- Sparse Matrix and BLAS 1 2
  - Support for CSR and COO storage types.
  - Sparse-Dense Matrix Multiplication and Matrix-Vector Multiplication as a part of af::matmul() using AF_STORAGE_CSR format for sparse.
  - Conversion to and from dense matrix to CSR and COO storage types.
- Faster JIT 1 2
  - Performance improvements for CUDA and OpenCL JIT functions.
  - Support for evaluating multiple outputs in a single kernel. See af::array::eval() for more.
- Random Number Generation 1 2
  - af::randomEngine(): A random engine class to handle setting the [type](af_random_type) and seed for random number generator engines.
  - Supported engine types are (af_random_engine_type):
    - Philox
    - Threefry
    - Mersenne Twister
- Graphics 1 2
  - Using Forge v0.9.0
  - Vector Field plotting functionality. 1
  - Removed GLEW and replaced with glbinding.
    - Removed usage of GLEW after support for MX (multithreaded) was dropped in v2.0. 1
  - Multiple overlays on the same window are now possible.
    - Overlays support for same type of object (2D/3D)
    - Supported by af::Window::plot, af::Window::hist, af::Window::surface, af::Window::vectorField.
  - New API to set axes limits for graphs.
    - Draw calls do not automatically compute the limits. This is now under user control.
    - af::Window::setAxesLimits can be used to set axes limits automatically or manually.
    - af::Window::setAxesTitles can be used to set axes titles.
  - New API for plot and scatter:
    - af::Window::plot() and af::Window::scatter() now can handle 2D and 3D and determine appropriate order.
    - af_draw_plot_nd()
    - af_draw_plot_2d()
    - af_draw_plot_3d()
    - af_draw_scatter_nd()
    - af_draw_scatter_2d()
    - af_draw_scatter_3d()
- New interpolation methods 1
  - Applies to
    - af::resize()
    - af::transform()
    - af::approx1()
    - af::approx2()
- Support for complex mathematical functions 1
  - Add complex support for Trigonometric functions, af::sqrt(), af::log().
- af::medfilt1(): Median filter for 1-d signals 1
- Generalized scan functions: scan and scanByKey
  - Now supports inclusive or exclusive scans
  - Supports binary operations defined by af_binary_op. 1
- Image Moments functions 1
- Add af::getSizeOf() function for af_dtype 1
- Explicitly extantiate af::array::device() for `void * 1

## Bug Fixes

- Fixes to edge-cases in Morphological Operations. 1
- Makes JIT tree size consistent between devices. 1
- Delegate higher-dimension in Convolutions to correct dimensions. 1
- Indexing fixes with C++11. 1 2
- Handle empty arrays as inputs in various functions. 1
- Fix bug when single element input to af::median. 1
- Fix bug in calculation of time from af::timeit(). 1
- Fix bug in floating point numbers in af::seq. 1
- Fixes for OpenCL graphics interop on NVIDIA devices. 1
- Fix bug when compiling large kernels for AMD devices. 1
- Fix bug in af::bilateral when shared memory is over the limit. 1
- Fix bug in kernel header compilation tool `bin2cpp`. 1
- Fix inital values for Morphological Operations functions. 1
- Fix bugs in af::homography() CPU and OpenCL kernels. 1
- Fix bug in CPU TNJ. 1

## Improvements

- CUDA 8 and compute 6.x(Pascal) support, current installer ships with CUDA 7.5. 1 2 3
- User controlled FFT plan caching. 1
- CUDA performance improvements for wrap, unwrap and Interpolation and approximation. 1
- Fallback for CUDA-OpenGL interop when no devices does not support OpenGL. 1
- Additional forms of batching with the transform functions. New behavior defined here. 1
- Update to OpenCL2 headers. 1
- Support for integration with external OpenCL contexts. 1
- Performance improvements to interal copy in CPU Backend. 1
- Performance improvements to af::select and af::replace CUDA kernels. 1
- Enable OpenCL-CPU offload by default for devices with Unified Host Memory. 1
  - To disable, use the environment variable `AF_OPENCL_CPU_OFFLOAD=0`.

## Build

- Compilation speedups. 1
- Build fixes with MKL. 1
- Error message when CMake CUDA Compute Detection fails. 1
- Several CMake build issues with Xcode generator fixed. 1 2
- Fix multiple OpenCL definitions at link time. 1
- Fix lapacke detection in CMake. 1
- Update build tags of
  - clBLAS
  - clFFT
  - Boost.Compute
  - Forge
  - glbinding
- Fix builds with GCC 6.1.1 and GCC 5.3.0. 1

## Installers

- All installers now ship with ArrayFire libraries build with MKL 2016.
- All installers now ship with Forge development files and examples included.
- CUDA Compute 2.0 has been removed from the installers. Please contact us directly if you have a special need.

## Examples

- Added example simulating gravity for demonstration of vector field.
- Improvements to financial/black_scholes_options.cpp example.
- Improvements to graphics/gravity_sim.cpp example.
- Fix graphics examples to use af::Window::setAxesLimits and af::Window::setAxesTitles functions.

## Documentation & Licensing

- ArrayFire copyright and trademark policy
- Fixed grammar in license.
- Add license information for glbinding.
- Remove license infomation for GLEW.
- Random123 now applies to all backends.
- Random number functions are now under Random Number Generation.

## Deprecations

The following functions have been deprecated and may be modified or removed permanently from future versions of ArrayFire.

- af::Window::plot3(): Use af::Window::plot instead.
- af_draw_plot(): Use af_draw_plot_nd or af_draw_plot_2d instead.
- af_draw_plot3(): Use af_draw_plot_nd or af_draw_plot_3d instead.
- af::Window::scatter3(): Use af::Window::scatter instead.
- af_draw_scatter(): Use af_draw_scatter_nd or af_draw_scatter_2d instead.
- af_draw_scatter3(): Use af_draw_scatter_nd or af_draw_scatter_3d instead.

## Known Issues

Certain CUDA functions are known to be broken on Tegra K1. The following ArrayFire tests are currently failing:

- assign_cuda
- harris_cuda
- homography_cuda
- median_cuda
- orb_cudasort_cuda
- sort_by_key_cuda
- sort_index_cuda

# v3.3.2

## Improvements

- Family of Sort functions now support higher order dimensions.
- Improved performance of batched sort on dim 0 for all Sort functions.
- Median now also supports higher order dimensions.

## Bug Fixes

- Fixes to error handling in C++ API for binary functions.
- Fixes to external OpenCL context management.
- Fixes to JPEG_GREYSCALE for FreeImage versions <= 3.154.
- Fixed for non-float inputs to af::rgb2gray().

## Build

- Disable CPU Async when building with GCC < 4.8.4.
- Add option to disable CPUID from CMake.
- More verbose message when CUDA Compute Detection fails.
- Print message to use CUDA library stub from CUDA Toolkit if CUDA Library is not found from default paths.
- Build Fixes on Windows.
  - For compiling tests our of source.
  - For compiling ArrayFire with static MKL.
- Exclude <sys/sysctl.h> when building on GNU Hurd.
- Add manual CMake options to build DEB and RPM packages.

## Documentation

- Fixed documentation for af::replace().
- Fixed images in Using on OSX page.

## Installer

- Linux x64 installers will now be compiled with GCC 4.9.2.
- OSX installer gives better error messages on brew failures and now includes link to Fixing OS X Installer Failures for brew installation failures.

# v3.3.1

## Bug Fixes

- Fixes to af::array::device()
  - CPU Backend: evaluate arrays before returning pointer with asynchronous calls in CPU backend.
  - OpenCL Backend: fix segfaults when requested for device pointers on empty arrays.
- Fixed af::array::operator%() from using rem to mod.
- Fixed array destruction when backends are switched in Unified API.
- Fixed indexing after af::moddims() is called.
- Fixes FFT calls for CUDA and OpenCL backends when used on multiple devices.
- Fixed unresolved external for some functions from af::array::array_proxy class.

## Build

- CMake compiles files in alphabetical order.
- CMake fixes for BLAS and LAPACK on some Linux distributions.

## Improvements

- Fixed OpenCL FFT performance regression.
- af::array::device() on OpenCL backend returns `cl_mem` instead of `(void*)cl::Buffer*`.
- In Unified backend, load versioned libraries at runtime.

## Documentation

- Reorganized, cleaner README file.
- Replaced non-free lena image in assets with free-to-distribute lena image.

# v3.3.0

## Major Updates

- CPU backend supports aysnchronous execution.
- Performance improvements to OpenCL BLAS and FFT functions.
- Improved performance of memory manager.
- Improvements to visualization functions.
- Improved sorted order for OpenCL devices.
- Integration with external OpenCL projects.

## Features

- af::getActiveBackend(): Returns the current backend being used.
- Scatter plot added to graphics.
- af::transform() now supports perspective transformation matrices.
- af::infoString(): Returns `af::info()` as a string.
- af::printMemInfo(): Print a table showing information about buffer from the memory manager
  - The AF_MEM_INFO macro prints numbers and total sizes of all buffers (requires including af/macros.h)
- af::allocHost(): Allocates memory on host.
- af::freeHost(): Frees host side memory allocated by arrayfire.
- OpenCL functions can now use CPU implementation.
  - Currently limited to Unified Memory devices (CPU and On-board Graphics).
  - Functions: af::matmul() and all LAPACK functions.
  - Takes advantage of optimized libraries such as MKL without doing memory copies.
  - Use the environment variable `AF_OPENCL_CPU_OFFLOAD=1` to take advantage of this feature.
- Functions specific to OpenCL backend.
  - afcl::addDevice(): Adds an external device and context to ArrayFire's device manager.
  - afcl::deleteDevice(): Removes an external device and context from ArrayFire's device manager.
  - afcl::setDevice(): Sets an external device and context from ArrayFire's device manager.
  - afcl::getDeviceType(): Gets the device type of the current device.
  - afcl::getPlatform(): Gets the platform of the current device.
- af::createStridedArray() allows array creation user-defined strides and device pointer.
- Expose functions that provide information about memory layout of Arrays.
  - af::getStrides(): Gets the strides for each dimension of the array.
  - af::getOffset(): Gets the offsets for each dimension of the array.
  - af::getRawPtr(): Gets raw pointer to the location of the array on device.
  - af::isLinear(): Returns true if all elements in the array are contiguous.
  - af::isOwner(): Returns true if the array owns the raw pointer, false if it is a sub-array.
  - af::getStrides(): Gets the strides of the array.
  - af::getStrides(): Gets the strides of the array.
- af::getDeviceId(): Gets the device id on which the array resides.
- af::isImageIOAvailable(): Returns true if ArrayFire was compiled with Freeimage enabled
- af::isLAPACKAvailable(): Returns true if ArrayFire was compiled with LAPACK functions enabled

## Bug Fixes

- Fixed errors when using 3D / 4D arrays in select and replace
- Fixed JIT errors on AMD devices for OpenCL backend.
- Fixed imageio bugs for 16 bit images.
- Fixed bugs when loading and storing images natively.
- Fixed bug in FFT for NVIDIA GPUs when using OpenCL backend.
- Fixed bug when using external context with OpenCL backend.
- Fixed memory leak in af_median_all().
- Fixed memory leaks and performance in graphics functions.
- Fixed bugs when indexing followed by moddims.
- af_get_revision() now returns actual commit rather than AF_REVISION.
- Fixed releasing arrays when using different backends.
- OS X OpenCL: LAPACK functions on CPU devices use OpenCL offload (previously threw errors).
- Add support for 32-bit integer image types in Image IO.
- Fixed set operations for row vectors
- Fixed bugs in af::meanShift() and af::orb().

## Improvements

- Optionally offload BLAS and LAPACK functions to CPU implementations to improve performance.
- Performance improvements to the memory manager.
- Error messages are now more detailed.
- Improved sorted order for OpenCL devices.
- JIT heuristics can now be tweaked using environment variables. See Environment Variables tutorial.
- Add `BUILD_<BACKEND>` options to examples and tests to toggle backends when compiling independently.

## Examples

- New visualization example simulating gravity.

## Build

- Support for Intel `icc` compiler
- Support to compile with Intel MKL as a BLAS and LAPACK provider
- Tests are now available for building as standalone (like examples)
- Tests can now be built as a single file for each backend
- Better handling of NONFREE build options
- Searching for GLEW in CMake default paths
- Fixes for compiling with MKL on OSX.

## Installers

- Improvements to OSX Installer
  - CMake config files are now installed with libraries
  - Independent options for installing examples and documentation components

## Deprecations

- `af_lock_device_arr` is now deprecated to be removed in v4.0.0. Use af_lock_array() instead.
- `af_unlock_device_arr` is now deprecated to be removed in v4.0.0. use af_unlock_array() instead.

## Documentation

- Fixes to documentation for matchTemplate().
- Improved documentation for deviceInfo.
- Fixes to documentation for exp().

## Known Issues

- Solve OpenCL fails on NVIDIA Maxwell devices for f32 and c32 when M > N and K % 4 is 1 or 2.

# v3.2.2

## Bug Fixes

- Fixed memory leak in CUDA Random number generators
- Fixed bug in af::select() and af::replace() tests
- Fixed exception thrown when printing empty arrays with af::print()
- Fixed bug in CPU random number generation. Changed the generator to mt19937
- Fixed exception handling (internal)
  - Exceptions now show function, short file name and line number
  - Added AF_RETURN_ERROR macro to handle returning errors.
  - Removed THROW macro, and renamed AF_THROW_MSG to AF_THROW_ERR.
- Fixed bug in af::identity() that may have affected CUDA Compute 5.2 cards

## Build

- Added a MIN_BUILD_TIME option to build with minimum optimization compiler flags resulting in faster compile times
- Fixed issue in CBLAS detection by CMake
- Fixed tests failing for builds without optional components FreeImage and LAPACK
- Added a test for unified backend
- Only info and backend tests are now built for unified backend
- Sort tests execution alphabetically
- Fixed compilation flags and errors in tests and examples
- Moved AF_REVISION and AF_COMPILER_STR into src/backend. This is because as revision is updated with every commit, entire ArrayFire would have to be rebuilt in the old code.
  - v3.3 will add a af_get_revision() function to get the revision string.
- Clean up examples
  - Remove getchar for Windows (this will be handled by the installer)
  - Other miscellaneous code cleanup
  - Fixed bug in plot3.cpp example
- Rename clBLAS/clFFT external project suffix from external -> ext
- Add OpenBLAS as a lapack/lapacke alternative

## Improvements

- Added AF_MEM_INFO macro to print memory info from ArrayFire's memory manager (cross issue)
- Added additional paths for searching for `libaf*` for Unified backend on unix-style OS.
  - Note: This still requires dependencies such as forge, CUDA, NVVM etc to be in `LD_LIBRARY_PATH` as described in Unified Backend
- Create streams for devices only when required in CUDA Backend

## Documentation

- Hide scrollbars appearing for pre and code styles
- Fix documentation for af::replace
- Add code sample for converting the output of af::getAvailableBackends() into bools
- Minor fixes in documentation

# v3.2.1

## Bug Fixes

- Fixed bug in homography()
- Fixed bug in behavior of af::array::device()
- Fixed bug when indexing with span along trailing dimension
- Fixed bug when indexing in GFor
- Fixed bug in CPU information fetching
- Fixed compilation bug in unified backend caused by missing link library
- Add missing symbol for af_draw_surface()

## Build

- Tests can now be used as a standalone project
  - Tests can now be built using pre-compiled libraries
  - Similar to how the examples are built
- The install target now installs the examples source irrespective of the BUILD_EXAMPLES value
  - Examples are not built if BUILD_EXAMPLES is off

## Documentation

- HTML documentation is now built and installed in docs/html
- Added documentation for af::seq class
- Updated Matrix Manipulation tutorial
- Examples list is now generated by CMake
  - Examples are now listed as dir/example.cpp
- Removed dummy groups used for indexing documentation (affcted doxygen < 1.8.9)

# v3.2.0

## Major Updates

- Added Unified backend
  - Allows switching backends at runtime
  - Read Unified Backend for more.
- Support for 16-bit integers (s16 and u16)
  - All functions that support 32-bit interger types (s32, u32), now also support 16-bit interger types

## Function Additions

- Unified Backend
  - setBackend() - Sets a backend as active
  - getBackendCount() - Gets the number of backends available for use
  - getAvailableBackends() - Returns information about available backends
  - getBackendId() - Gets the backend enum for an array
- Vision
  - homography() - Homography estimation
  - gloh() - GLOH Descriptor for SIFT
- Image Processing
  - loadImageNative() - Load an image as native data without modification
  - saveImageNative() - Save an image without modifying data or type
- Graphics
  - af::Window::plot3() - 3-dimensional line plot
  - af::Window::surface() - 3-dimensional curve plot
- Indexing
  - af_create_indexers()
  - af_set_array_indexer()
  - af_set_seq_indexer()
  - af_set_seq_param_indexer()
  - af_release_indexers()
- CUDA Backend Specific
  - setNativeId() - Set the CUDA device with given native id as active
    - ArrayFire uses a modified order for devices. The native id for a device can be retreived using `nvidia-smi`
- OpenCL Backend Specific
  - setDeviceId() - Set the OpenCL device using the `clDeviceId`

## Other Improvements

- Added c32 and c64 support for isNaN(), isInf() and iszero()
- Added CPU information for `x86` and `x86_64` architectures in CPU backend's info()
- Batch support for approx1() and approx2()
  - Now can be used with gfor as well
- Added s64 and u64 support to:
  - sort() (along with sort index and sort by key)
  - setUnique(), setUnion(), setIntersect()
  - convolve() and fftConvolve()
  - histogram() and histEqual()
  - lookup()
  - mean()
- Added AF_MSG macro

## Build Improvements

- Submodules update is now automatically called if not cloned recursively
- Fixes for compilation on Visual Studio 2015
- Option to use fallback to CPU LAPACK for linear algebra functions in case of CUDA 6.5 or older versions.

## Bug Fixes

- Fixed memory leak in susan()
- Fixed failing test in lower() and upper() for CUDA compute 53
- Fixed bug in CUDA for indexing out of bounds
- Fixed dims check in iota()
- Fixed out-of-bounds access in sift()
- Fixed memory allocation in fast() OpenCL
- Fixed memory leak in image I/O functions
- dog() now returns float-point type arrays

## Documentation Updates

- Improved tutorials documentation
  - More detailed Using on Linux, OSX, Windows pages.
- Added return type information for functions that return different type arrays

## New Examples

- Graphics
  - Plot3
  - Surface
- Shallow Water Equation
- Basic as a Unified backend example

## Installers

- All installers now include the Unified backend and corresponding CMake files
- Visual Studio projects include Unified in the Platform Configurations
- Added installer for Jetson TX1
- SIFT and GLOH do not ship with the installers as SIFT is protected by patents that do not allow commercial distribution without licensing.

# v3.1.3

## Bug Fixes

- Fixed bugs in various OpenCL kernels without offset additions
- Remove ARCH_32 and ARCH_64 flags
- Fix missing symbols when freeimage is not found
- Use CUDA driver version for Windows
- Improvements to SIFT
- Fixed memory leak in median
- Fixes for Windows compilation when not using MKL #1047
- Fixed for building without LAPACK

## Other

- Documentation: Fixed documentation for select and replace
- Documentation: Fixed documentation for af_isnan

# v3.1.2

## Bug Fixes

- Fixed bug in assign that was causing test to fail
- Fixed bug in convolve. Frequency condition now depends on kernel size only
- Fixed bug in indexed reductions for complex type in OpenCL backend
- Fixed bug in kernel name generation in ireduce for OpenCL backend
- Fixed non-linear to linear indices in ireduce
- Fixed bug in reductions for small arrays
- Fixed bug in histogram for indexed arrays
- Fixed compiler error CPUID for non-compliant devices
- Fixed failing tests on i386 platforms
- Add missing AFAPI

## Other

- Documentation: Added missing examples and other corrections
- Documentation: Fixed warnings in documentation building
- Installers: Send error messages to log file in OSX Installer

# v3.1.1

## Installers

- CUDA backend now depends on CUDA 7.5 toolkit
- OpenCL backend now require OpenCL 1.2 or greater

## Bug Fixes

- Fixed bug in reductions after indexing
- Fixed bug in indexing when using reverse indices

## Build

- `cmake` now includes `PKG_CONFIG` in the search path for CBLAS and LAPACKE libraries
- heston_model.cpp example now builds with the default ArrayFire cmake files after installation

## Other

- Fixed bug in image_editing.cpp

# v3.1.0

## Function Additions

- Computer Vision Functions
  - nearestNeighbour() - Nearest Neighbour with SAD, SSD and SHD distances
  - harris() - Harris Corner Detector
  - susan() - Susan Corner Detector
  - sift() - Scale Invariant Feature Transform (SIFT)
    - Method and apparatus for identifying scale invariant features" "in an image and use of same for locating an object in an image," David" "G. Lowe, US Patent 6,711,293 (March 23, 2004). Provisional application" "filed March 8, 1999. Asignee: The University of British Columbia. For" "further details, contact David Lowe (lowe@.nosp@m.cs.u.nosp@m.bc.ca) or the" "University-Industry Liaison Office of the University of British" "Columbia.")
    - SIFT is available for compiling but does not ship with ArrayFire hosted installers/pre-built libraries
  - dog() - Difference of Gaussians
- Image Processing Functions
  - ycbcr2rgb() and rgb2ycbcr() - RGB <->YCbCr color space conversion
  - wrap() and unwrap() Wrap and Unwrap
  - sat() - Summed Area Tables
  - loadImageMem() and saveImageMem() - Load and Save images to/from memory
    - af_image_format - Added imageFormat (af_image_format) enum
- Array & Data Handling
  - copy() - Copy
  - array::lock() and array::unlock() - Lock and Unlock
  - select() and replace() - Select and Replace
  - Get array reference count (af_get_data_ref_count)
- Signal Processing
  - fftInPlace() - 1D in place FFT
  - fft2InPlace() - 2D in place FFT
  - fft3InPlace() - 3D in place FFT
  - ifftInPlace() - 1D in place Inverse FFT
  - ifft2InPlace() - 2D in place Inverse FFT
  - ifft3InPlace() - 3D in place Inverse FFT
  - fftR2C() - Real to complex FFT
  - fftC2R() - Complex to Real FFT
- Linear Algebra
  - svd() and svdInPlace() - Singular Value Decomposition
- Other operations
  - sigmoid() - Sigmoid
  - Sum (with option to replace NaN values)
  - Product (with option to replace NaN values)
- Graphics
  - Window::setSize() - Window resizing using Forge API
- Utility
  - Allow users to set print precision (print, af_print_array_gen)
  - saveArray() and readArray() - Stream arrays to binary files
  - toString() - toString function returns the array and data as a string
- CUDA specific functionality
  - getStream() - Returns default CUDA stream ArrayFire uses for the current device
  - getNativeId() - Returns native id of the CUDA device

## Improvements

- dot
  - Allow complex inputs with conjugate option
- AF_INTERP_LOWER interpolation
  - For resize, rotate and transform based functions
- 64-bit integer support
  - For reductions, random, iota, range, diff1, diff2, accum, join, shift and tile
- convolve
  - Support for non-overlapping batched convolutions
- Complex Arrays
  - Fix binary ops on complex inputs of mixed types
  - Complex type support for exp
- tile
  - Performance improvements by using JIT when possible.
- Add AF_API_VERSION macro
  - Allows disabling of API to maintain consistency with previous versions
- Other Performance Improvements
  - Use reference counting to reduce unnecessary copies
- CPU Backend
  - Device properties for CPU
  - Improved performance when all buffers are indexed linearly
- CUDA Backend
  - Use streams in CUDA (no longer using default stream)
  - Using async cudaMem ops
  - Add 64-bit integer support for JIT functions
  - Performance improvements for CUDA JIT for non-linear 3D and 4D arrays
- OpenCL Backend
  - Improve compilation times for OpenCL backend
  - Performance improvements for non-linear JIT kernels on OpenCL
  - Improved shared memory load/store in many OpenCL kernels (PR 933)
  - Using cl.hpp v1.2.7

## Bug Fixes

- Common
  - Fix compatibility of c32/c64 arrays when operating with scalars
  - Fix median for all values of an array
  - Fix double free issue when indexing (30cbbc7)
  - Fix bug in rank
  - Fix default values for scale throwing exception
  - Fix conjg raising exception on real input
  - Fix bug when using conjugate transpose for vector input
  - Fix issue with const input for array_proxy::get()
- CPU Backend
  - Fix randn generating same sequence for multiple calls
  - Fix setSeed for randu
  - Fix casting to and from complex
  - Check NULL values when allocating memory
  - Fix offset issue for CPU element-wise operations

## New Examples

- Match Template
- Susan
- Heston Model (contributed by Michael Nowotny)

## Installer

- Fixed bug in automatic detection of ArrayFire when using with CMake in Windows
- The Linux libraries are now compiled with static version of FreeImage

## Known Issues

- OpenBlas can cause issues with QR factorization in CPU backend
- FreeImage older than 3.10 can cause issues with loadImageMem and saveImageMem
- OpenCL backend issues on OSX
  - AMD GPUs not supported because of driver issues
  - Intel CPUs not supported
  - Linear algebra functions do not work on Intel GPUs.
- Stability and correctness issues with open source OpenCL implementations such as Beignet, GalliumCompute.

# v3.0.2

## Bug Fixes

- Added missing symbols from the compatible API
- Fixed a bug affecting corner rows and elements in grad()
- Fixed linear interpolation bugs affecting large images in the following:
  - approx1()
  - approx2()
  - resize()
  - rotate()
  - scale()
  - skew()
  - transform()

## Documentation

- Added missing documentation for constant()
- Added missing documentation for `array::scalar()`
- Added supported input types for functions in `arith.h`

# v3.0.1

## Bug Fixes

- Fixed header to work in Visual Studio 2015
- Fixed a bug in batched mode for FFT based convolutions
- Fixed graphics issues on OSX
- Fixed various bugs in visualization functions

## Other improvements

- Improved fractal example
- New OSX installer
- Improved Windows installer
  - Default install path has been changed
- Fixed bug in machine learning examples

# v3.0.0

## Major Updates

- ArrayFire is now open source
- Major changes to the visualization library
- Introducing handle based C API
- New backend: CPU fallback available for systems without GPUs
- Dense linear algebra functions available for all backends
- Support for 64 bit integers

## Function Additions

- Data generation functions
  - range()
  - iota()
- Computer Vision Algorithms
  - features()
    - A data structure to hold features
  - fast()
    - FAST feature detector
  - orb()
    - ORB A feature descriptor extractor
- Image Processing
  - convolve1(), convolve2(), convolve3()
    - Specialized versions of convolve() to enable better batch support
  - fftconvolve1(), fftconvolve2(), fftconvolve3()
    - Convolutions in frequency domain to support larger kernel sizes
  - dft(), idft()
    - Unified functions for calling multi dimensional ffts.
  - matchTemplate()
    - Match a kernel in an image
  - sobel()
    - Get sobel gradients of an image
  - rgb2hsv(), hsv2rgb(), rgb2gray(), gray2rgb()
    - Explicit function calls to colorspace conversions
  - erode3d(), dilate3d()
    - Explicit erode and dilate calls for image morphing
- Linear Algebra
  - matmulNT(), matmulTN(), matmulTT()
    - Specialized versions of matmul() for transposed inputs
  - luInPlace(), choleskyInPlace(), qrInPlace()
    - In place factorizations to improve memory requirements
  - solveLU()
    - Specialized solve routines to improve performance
  - OpenCL backend now Linear Algebra functions
- Other functions
  - lookup() - lookup indices from a table
  - batchFunc() - helper function to perform batch operations
- Visualization functions
  - Support for multiple windows
  - window.hist()
    - Visualize the output of the histogram
- C API
  - Removed old pointer based C API
  - Introducing handle base C API
  - Just In Time compilation available in C API
  - C API has feature parity with C++ API
  - bessel functions removed
  - cross product functions removed
  - Kronecker product functions removed

## Performance Improvements

- Improvements across the board for OpenCL backend

## API Changes

- `print` is now af_print()
- seq(): The step parameter is now the third input
  - seq(start, step, end) changed to seq(start, end, step)
- gfor(): The iterator now needs to be seq()

## Deprecated Function APIs

Deprecated APIs are in af/compatible.h

- devicecount() changed to getDeviceCount()
- deviceset() changed to setDevice()
- deviceget() changed to getDevice()
- loadimage() changed to loadImage()
- saveimage() changed to saveImage()
- gaussiankernel() changed to gaussianKernel()
- alltrue() changed to allTrue()
- anytrue() changed to anyTrue()
- setunique() changed to setUnique()
- setunion() changed to setUnion()
- setintersect() changed to setIntersect()
- histequal() changed to histEqual()
- colorspace() changed to colorSpace()
- filter() deprecated. Use convolve1() and convolve2()
- mul() changed to product()
- deviceprop() changed to deviceProp()

## Known Issues

- OpenCL backend issues on OSX
  - AMD GPUs not supported because of driver issues
  - Intel CPUs not supported
  - Linear algebra functions do not work on Intel GPUs.
- Stability and correctness issues with open source OpenCL implementations such as Beignet, GalliumCompute.