Removed dependency on CLTune

1 files changed, 1 insertions, 3 deletions

diff --git a/README.md b/README.md
index 5f4b3d15..6c27af51 100644
--- a/README.md
+++ b/README.md
@@ -180,8 +180,6 @@ If your device is not (yet) among this list or if you want to tune CLBlast for s
 
     cmake -DTUNERS=ON ..
 
-Note that CLBlast's tuners are based on the [CLTune auto-tuning library](https://github.com/CNugteren/CLTune), which has to be installed separately (requires version 2.6.0 or higher).
-
 Compiling with `-DTUNERS=ON` will generate a number of tuners, each named `clblast_tuner_xxxxx`, in which `xxxxx` corresponds to a `.opencl` kernel file as found in `src/kernels`. These kernels corresponds to routines (e.g. `xgemm`) or to common pre-processing or post-processing kernels (`copy` and `transpose`). Running such a tuner will test a number of parameter-value combinations on your device and report which one gave the best performance. Running `make alltuners` runs all tuners for all precisions in one go. You can set the default device and platform for `alltuners` by setting the `CLBLAST_DEVICE` and `CLBLAST_PLATFORM` environmental variables.
 
 The tuners output a JSON-file with the results. The best results need to be added to `src/database/kernels/xxxxx.hpp` in the appropriate section. However, this can be done automatically based on the JSON-data using a Python (2.7 or 3.x) script in `scripts/database/database.py`. If you want the found parameters to be included in future releases of CLBlast, please attach the JSON files to the corresponding issue on GitHub or [email the main author](http://www.cedricnugteren.nl).
@@ -416,7 +414,7 @@ More information
 Further information on CLBlast is available through the following links:
 
 * A 20-minute presentation of CLBlast was given at the GPU Technology Conference in May 2017. A recording is available on the [GTC on-demand website](http://on-demand.gputechconf.com/gtc/2017/video/s7280-nugteren-clblast.mp4) (poor audio quality however) and a full slide-set is also available [as PDF](http://on-demand.gputechconf.com/gtc/2017/presentation/s7280-cedric-nugteren-clblast.pdf).
-* More in-depth information and experimental results are also available in a scientific paper titled [CLBlast: A Tuned OpenCL BLAS Library](https://arxiv.org/abs/1705.05249) (May 2017). For CLTune, see also the [CLTune: A Generic Auto-Tuner for OpenCL Kernels](https://arxiv.org/abs/1703.06503) paper.
+* More in-depth information and experimental results are also available in a scientific paper titled [CLBlast: A Tuned OpenCL BLAS Library](https://arxiv.org/abs/1705.05249) (May 2017). For CLTune, the inspiration for the included auto-tuner, see also the [CLTune: A Generic Auto-Tuner for OpenCL Kernels](https://arxiv.org/abs/1703.06503) paper.
 
 
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