README

===================
clMAGMA README FILE
===================

* To INSTALL clMAGMA, modify the make.inc file to indicate where
  OpenCL BLAS, CPU BLAS, and LAPACK are installed on your system.
  Examples are given in make.inc.acml and make.inc.mkl, showing how
  to link correspondingly to ACML and MKL. After proper modification
  of the make.inc file, typing 'make', will create
   1) the libclmagma.a and libclmagmablas.a libraries in directory 'lib'
   2) testing drivers in directory 'testing'.

* To TEST clMAGMA, go to directory 'testing'. Provided are a number of
  drivers testing different routines. These drivers are also useful
  as examples on how to use clMAGMA, as well as to benchmark the performance.
  Before running set environment variable MAGMA_CL_DIR to point at
  cl_magma/interface_opencl.

* To TUNE clMAGMA, you can modify the blocking factors for the algorithms of
  interest in file 'control/get_nb_tahiti.cpp'. The default values are tuned for
  AMD Radeon 7970 (Tahiti) GPUs. You can also compare your performance to
  what we get, given in file
  'testing/results_clmagma.txt', as an easy check for your installation.

* To autotune clAcmlBlas, set the AMD_CLBLAS_STORAGE_PATH environment variable
  to a working directory and run clblas tune. Subsequent clMAGMA runs will
  use the optimized routines (as long as AMD_CLBLAS_STORAGE_PATH points
  to the directory storing the results from the clblas tune runs).

* To use a GPU on a server, disable X forwarding when you ssh to the server,
  using 'ssh -x hostname'. To see whether OpenCL finds your GPU, use 'clinfo'.

For more INFORMATION, please refer to the MAGMA homepage and user forum:

  http://icl.cs.utk.edu/magma/
  http://icl.cs.utk.edu/magma/forum/

The MAGMA project supports the package in the sense that reports of
errors or poor performance will gain immediate attention from the
developers. Such reports, descriptions of interesting applications,
and other comments should be posted on the MAGMA user forum.