This repository contains the source code for the BITS (Binary Interval Search) algorithm developed in the Quinlan laboratory at the University of Virginia.
BITS installation requires the GNU Scientific Library (GSL) as well as NVidia GPU drivers and libraries. Below is a step-by-step tutorial for how to install the necessary drivers, SDK and libraries to run BITS on an NVidia CUDA GPU. If you have questions, email me.
Install the GNU Scientific Libraries (GSL).
- This is typically quite simple, as one can use package managers.
- e.g., for OS X using Homebrew: brew install gsl
- e.g., for Ubuntu: apt-get install gsl
Download and install the CUDA toolkit.
- The CUDA toolkit for multiple platforms is available at:
- e.g., for OS X: http://developer.download.nvidia.com/compute/cuda/4_2/rel/toolkit/cudatoolkit_4.2.9_macos.pkg
Download and install the CUDA drivers for you system.
- Likewise available for many platforms at:
- e.g., for OS X: http://developer.download.nvidia.com/compute/cuda/4_2/rel/drivers/devdriver_4.2.10_macos.dmg
Download and install the CUDA SDK.
- Likewise available for many platforms at:
- e.g., for OS X: http://developer.download.nvidia.com/compute/cuda/4_2/rel/sdk/gpucomputingsdk_4.2.9_macos.pkg
- Important: Take note of the installation path - you will need this when we update the BITS Makefile.
- The default path for OSX is /Developer/GPUComputing/.
Download and install the cudapp library at: http://code.google.com/p/cudpp/. Once downloaded, do
cd cudpp_src_2.0 cmake . make *Important*: Take note of the path to which you placed cudpp, as you will need this when we update the BITS Makefile.
Update your PATH (rec. you save in .bash_profile for permanence) as follows
export PATH=/usr/local/cuda/bin:$PATH export DYLD_LIBRARY_PATH=/usr/local/cuda/lib:$DYLD_LIBRARY_PATH
Clone the BITS repository
git clone git://github.com/arq5x/bits.git
Navigate into the bits directory
cd bits
- Edit the defs.cuda file in accordance with your configuration.
- Edit the PLATFORM environment variable.
- if OSX, set PLATFORM=darwin
- if Linux, set PLATFORM=linux
- if Windows, sorry this is unsupported.
- Edit the SDK_PATH environment variable.
- This is the installation path that you should have taken note of in step #4.
- e.g., for OS X, this should be: SDK_PATH=/Developer/GPUComputing/
- Edit the SDK_PATH environment variable.
- This is the path to which you downloaded and compiled cudpp in step #5.
- EDIT the CUDA_LIB environment variable.
- If OS X, this should be: /usr/local/cuda/lib
- If Linux, this should be: /usr/local/cuda/lib64
At this point, you should be ready to compile BITS
make
Now, you can test both the sequential and CUDA versions of the tools by running the bits_tests scripts. Also, this shell script demonstrates how to run each of the BITS tools
sh bits_tests
If all works well, you should see the following
sh bits_tests bits_count 72534 bits_count_cuda 72534 bits_count_per_interval 72534 bits_count_per_interval_cuda 72534 bits_enumerate 72534 bits_enumerate_cuda 72534 bits_test O:72534 E:1124.853000 sd:33.680585 p:0.000999 bits_test_cuda O:72534 E:1124.081000 sd:36.552024 p:0.000999
If you want to run the BITS CUDA Monte Carlo simulation tool for a single pairwise comparison of two BED files, run the following, where -n is the number of MC iterations and -g is the name and size of each chromosome:
bin/bits_test_cuda -a a.bed -b b.bed -g chrom.sizes -n 1000
If you want to run the BITS CUDA Monte Carlo simulation tool for a _many_ pairwise comparison of multiple BED files, just create a shell script that loops over every pairwise set of files and calls the program as above. For example:
for file1 in `cat file_list.txt`
do
for file2 in `cat file_list.txt`
do
bin/bits_test_cuda -a $file1 -b $file2 -g chrom.sizes -n 1000
done
done
OS X: If you get the "no CUDA-capable device is detected" after installing the drivers, try turning off "Automatic graphics switching." Go to launchpad/System Preferences/Energy Saver and uncheck Automatic graphics switching. Thanks to Stéphane Plaisance for this fix.