agv_navigation_ws/fast_gicp/thirdparty/nvbio/nvLighter/nvLighter.dox

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/// \page nvlighter_page nvLighter
///
///\htmlonly
/// <img src="nvidia_cubes.png" style="position:relative; bottom:-10px; border:0px;"/>
///\endhtmlonly
///
///\par
///\n
/// <a href="https://github.com/NVlabs/nvbio/tree/master/nvLighter">nvLighter</a> is a GPU-accelerated re-engineering of
/// <a href="https://github.com/mourisl/Lighter">Lighter</a>, a very low memory footprint error corrector, implementing
/// the algorithms described in: \n \n
///   <a href="http://genomebiology.com/2014/15/11/509">Lighter: fast and memory-efficient sequencing error correction without counting</a> \n
///   Li Song, Liliana Florea and Ben Langmead \n
///   <i>Genome Biology</i>, 2014, 15:509
///\par
/// nvLighter can use both multiple CPU threads as well as multiple GPUs to concurrently
/// correct large sets of reads.
/// In practice, the error correction algorithm is so fast it can be easily bottlenecked by I/O:
/// hence, we recommend using nvLighter on an SSD-equipped system in order to appreciate
/// maximum acceleration.
///
/// \section nvLighterUsage Usage
///
///\par
/// At the moment, the command line options of nvLighter differ from those of Lighter,
/// as nvLighter is designed to handle a single input file at the time.
/// Moreover, nvLighter supports many file formats for both input and output, among which
/// plain .txt files (with one read per row), FASTA, and FASTQ.
/// Additionally, as <i>slow gzip compression</i> can quickly become a bottleneck, nvLighter supports
/// LZ4 compression on any of the above formats.
///
///\verbatim
/// ./nvLighter --help
///
/// nvLighter - Copyright 2015, NVIDIA Corporation
/// usage:
///    nvLighter [options] input_file output_file
///    options:
///     -v         int (0-6) [5]              # verbosity level
///     -zlib      string    [1R]             # e.g. "1", ..., "9", "1R"
///     -t         int       [auto]           # number of CPU threads
///     -d         int       [0]              # add the specified GPU device
///     -k         k-mer genome-size alpha    # error correction parameters
///     -K         k-mer genome-size          # error correction parameters
///     -maxcor                               # maximum correction factor
///     -newQual                              # new quality score value
///     -no-cpu                               # disable CPU usage
///     -no-gpu                               # disable GPU usage
///\endverbatim
///\par
/// For example:
///
///\verbatim
/// nvLighter -t 20 -d 0 -d 1 -k 31 3500000000 0.2 NA12878.fq.gz NA12878.corrected.fq.lz4
///\endverbatim
///\par
/// will use 20 CPU threads and GPU 0 and 1 to correct a 35x coverage human dataset and output the result to an LZ4-compressed FASTQ file;
/// whereas the command:
///
///\verbatim
/// nvLighter -no-cpu -d 0 -k 31 3500000000 0.2 NA12878.fq.gz NA12878.corrected.txt.lz4
///\endverbatim
///\par
/// will use only GPU 0 to correct the same 35x coverage human reads and output the result to an LZ4-compressed .txt file.
///\par
/// As described in the original paper, the <i>alpha</i> parameter should be generally set as 7.0/C, where C is the coverage of the genome.
/// If alpha is not specified, it will be computed with an additional streaming pass through the input reads.
///
///
/// \section nvLighterArchitecture Architecture
///
/// nvLighter's class hierarchy is documented in the \ref nvLighterModule "nvLighter module".
///