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This file is a part of bsc and/or libbsc, a program and a library for
lossless, block-sorting data compression.

bsc is a high performance file compressor based on lossless,
block-sorting data compression algorithms.

libbsc is a library based on bsc, it uses the same algorithms
as bsc and enables you to compress memory blocks.

Copyright (c) 2009-2024 Ilya Grebnov <>

See file AUTHORS for a full list of contributors.

See the bsc and libbsc web site: for more information.

Software License:

Copyright (c) 2009-2024 Ilya Grebnov <>

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
See the License for the specific language governing permissions and
limitations under the License.

Please see the file LICENSE for full copyright information and file AUTHORS
for full list of contributors.

See also the bsc and libbsc web site: for more information.

Memory usage:

bsc compresses large files in blocks. Multiple blocks can be processed in
parallel on multiple-core CPU. At decompression time, the block size used
for compression is read from the header of the compressed file. The block
size and number of blocks processed in parallel affects both the compression
ratio achieved, and the amount of memory needed for compression and decompression.
Compression and decompression requirements are the same and in bytes, can
be estimated as 16Mb + 5 x block size x number of blocks processed in parallel.

GPU memory usage for NVIDIA CUDA technology is different from CPU memory usage
and can be estimated as 20 x block size for ST, 21 x block size for forward BWT
and 7 x block size for inverse BWT.

NVIDIA GPU acceleration:

1. libbsc uses NVIDIA CUDA technology, resulting in a performance boost on computers
with NVIDIA GPU of compute capability 5.0 or higher. Lists of supported GPUs
can be found on the NVIDIA website
You also need to install latest graphics drivers that support CUDA.

2. Individual kernels are limited to a 2-second runtime by Windows. Kernels that run for
longer than 2 seconds will trigger the Timeout Detection and Recovery (TDR) mechanism.
Detailed information on disabling the Windows TDR is available at: