NEWS

gputools changes
=================

changes in gputools 1.1
- this is a point release intended to trial cuda run-time compilation (nvrtc)
  it is only used for the kendall correlation option of gpuCor
  but nvrtc will be used for all cuda kernel code in future releases

changes in gputools 0.5
- switched back to autotools options

changes in gputools 0.28
- updated installation procedure
- updated OSX compatibility
- removed CULA dependencies

changes in gputools 0.27
- removed LICENSE file and updated DESCRIPTION file
- fixed R documentation files
- removed nonfunctional svm code

changes in gputools 0.26
- fixes to several potential bugs:  
	There was a variable in the QR code which was never  
	deallocated.  Also, there were several variables freed with  
	the wrong method. Also, added a missing cublasInit/Shutdown pair.
	Thanks to Eunjin Lee's error reporting!

changes in gputools 0.24

- added support for configure argument --with-compiler-bindir and
	environment variable COMPILER_BINDIR to support gcc located somewhere
	other than the user's path. Use one of these to get the package
	installed in flavors of Linux that ship with default gcc version > 4.4.

changes in gputools 0.24

- A couple of changes to the Makefile:
	* added -I. for compatibility with R 2.12
	* switched from CC to NVCC for compat with ~/.R/Makevars

changes in gputools 0.21

- fixed another bug in gpuMi

changes in gputools 0.2

- added some linear and nonlinear regression functions

- added some configure args --with-r-lib and --with-r-include (see INSTALL
notes section)

- fixed a bug in gpuMi

- added a demo of CULA use: fastICA with CULA's svd plugged in.

changes in gputools 0.1.3

- Mac os x and nvidia cards with compute capability less than 1.3 are now
supported. Systems lacking a gpu altogether also recieve some support. See the
file INSTALL for details.

- gpuHclust, gpuDist, and gpuQr now output the same classes as R's base hclust,
dist, and qr functions.

- The c code now uses r's api. Host memory allocation and error reporting
have recieved a facelift.

- gpuGranger now reports the correct p-values and is slightly faster for small
data sets.

- Some bugs with gpuCor's pearson method have been fixed.