2005-04-16 15:20:36 -07:00
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2009-03-06 17:21:46 +01:00
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2005-04-16 15:20:36 -07:00
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2009-07-13 11:35:12 +01:00
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2006-12-08 02:36:25 -08:00
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2009-06-11 14:51:15 +01:00
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2008-04-25 13:12:53 +02:00
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2008-10-15 22:01:38 -07:00
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2008-04-25 13:12:53 +02:00
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2008-10-15 22:01:38 -07:00
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2008-04-25 13:12:53 +02:00
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2011-03-23 16:41:59 -07:00
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2009-01-01 10:12:19 +10:30
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2005-04-16 15:20:36 -07:00
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2005-08-17 15:17:26 +04:00
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2008-06-25 11:22:42 -04:00
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2006-06-12 16:17:04 +02:00
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2005-04-16 15:20:36 -07:00
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2006-12-08 02:36:25 -08:00
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2005-04-16 15:20:36 -07:00
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2007-07-17 04:04:03 -07:00
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2005-04-16 15:20:36 -07:00
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2008-11-13 22:05:13 +08:00
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2008-11-07 15:11:47 +08:00
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2005-04-16 15:20:36 -07:00
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2006-09-12 03:04:40 -04:00
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2005-04-16 15:20:36 -07:00
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2007-07-10 17:22:24 -07:00
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2011-01-12 17:01:22 -08:00
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2009-01-05 13:48:31 -08:00
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2009-01-07 00:01:43 -08:00
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2009-01-05 13:48:31 -08:00
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decompressors: add boot-time XZ support
This implements the API defined in <linux/decompress/generic.h> which is
used for kernel, initramfs, and initrd decompression. This patch together
with the first patch is enough for XZ-compressed initramfs and initrd;
XZ-compressed kernel will need arch-specific changes.
The buffering requirements described in decompress_unxz.c are stricter
than with gzip, so the relevant changes should be done to the
arch-specific code when adding support for XZ-compressed kernel.
Similarly, the heap size in arch-specific pre-boot code may need to be
increased (30 KiB is enough).
The XZ decompressor needs memmove(), memeq() (memcmp() == 0), and
memzero() (memset(ptr, 0, size)), which aren't available in all
arch-specific pre-boot environments. I'm including simple versions in
decompress_unxz.c, but a cleaner solution would naturally be nicer.
Signed-off-by: Lasse Collin <lasse.collin@tukaani.org>
Cc: "H. Peter Anvin" <hpa@zytor.com>
Cc: Alain Knaff <alain@knaff.lu>
Cc: Albin Tonnerre <albin.tonnerre@free-electrons.com>
Cc: Phillip Lougher <phillip@lougher.demon.co.uk>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2011-01-12 17:01:23 -08:00
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2010-01-08 14:42:46 -08:00
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2005-06-21 17:15:02 -07:00
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2005-04-16 15:20:36 -07:00
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lib: add shared BCH ECC library
This is a new software BCH encoding/decoding library, similar to the shared
Reed-Solomon library.
Binary BCH (Bose-Chaudhuri-Hocquenghem) codes are widely used to correct
errors in NAND flash devices requiring more than 1-bit ecc correction; they
are generally better suited for NAND flash than RS codes because NAND bit
errors do not occur in bursts. Latest SLC NAND devices typically require at
least 4-bit ecc protection per 512 bytes block.
This library provides software encoding/decoding, but may also be used with
ASIC/SoC hardware BCH engines to perform error correction. It is being
currently used for this purpose on an OMAP3630 board (4bit/8bit HW BCH). It
has also been used to decode raw dumps of NAND devices with on-die BCH ecc
engines (e.g. Micron 4bit ecc SLC devices).
Latest NAND devices (including SLC) can exhibit high error rates (typically
a dozen or more bitflips per hour during stress tests); in order to
minimize the performance impact of error correction, this library
implements recently developed algorithms for fast polynomial root finding
(see bch.c header for details) instead of the traditional exhaustive Chien
root search; a few performance figures are provided below:
Platform: arm926ejs @ 468 MHz, 32 KiB icache, 16 KiB dcache
BCH ecc : 4-bit per 512 bytes
Encoding average throughput: 250 Mbits/s
Error correction time (compared with Chien search):
average worst average (Chien) worst (Chien)
----------------------------------------------------------
1 bit 8.5 µs 11 µs 200 µs 383 µs
2 bit 9.7 µs 12.5 µs 477 µs 728 µs
3 bit 18.1 µs 20.6 µs 758 µs 1010 µs
4 bit 19.5 µs 23 µs 1028 µs 1280 µs
In the above figures, "worst" is meant in terms of error pattern, not in
terms of cache miss / page faults effects (not taken into account here).
The library has been extensively tested on the following platforms: x86,
x86_64, arm926ejs, omap3630, qemu-ppc64, qemu-mips.
Signed-off-by: Ivan Djelic <ivan.djelic@parrot.com>
Signed-off-by: David Woodhouse <David.Woodhouse@intel.com>
2011-03-11 11:05:32 +01:00
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2005-06-24 17:39:03 -07:00
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2005-06-23 20:49:30 -07:00
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2005-06-24 17:39:03 -07:00
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2005-04-16 15:20:36 -07:00
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[LIB]: Knuth-Morris-Pratt textsearch algorithm
Implements a linear-time string-matching algorithm due to Knuth,
Morris, and Pratt [1]. Their algorithm avoids the explicit
computation of the transition function DELTA altogether. Its
matching time is O(n), for n being length(text), using just an
auxiliary function PI[1..m], for m being length(pattern),
precomputed from the pattern in time O(m). The array PI allows
the transition function DELTA to be computed efficiently
"on the fly" as needed. Roughly speaking, for any state
"q" = 0,1,...,m and any character "a" in SIGMA, the value
PI["q"] contains the information that is independent of "a" and
is needed to compute DELTA("q", "a") [2]. Since the array PI
has only m entries, whereas DELTA has O(m|SIGMA|) entries, we
save a factor of |SIGMA| in the preprocessing time by computing
PI rather than DELTA.
[1] Cormen, Leiserson, Rivest, Stein
Introdcution to Algorithms, 2nd Edition, MIT Press
[2] See finite automation theory
Signed-off-by: Thomas Graf <tgraf@suug.ch>
Signed-off-by: David S. Miller <davem@davemloft.net>
2005-06-23 20:58:37 -07:00
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2005-06-24 17:39:03 -07:00
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[LIB]: Knuth-Morris-Pratt textsearch algorithm
Implements a linear-time string-matching algorithm due to Knuth,
Morris, and Pratt [1]. Their algorithm avoids the explicit
computation of the transition function DELTA altogether. Its
matching time is O(n), for n being length(text), using just an
auxiliary function PI[1..m], for m being length(pattern),
precomputed from the pattern in time O(m). The array PI allows
the transition function DELTA to be computed efficiently
"on the fly" as needed. Roughly speaking, for any state
"q" = 0,1,...,m and any character "a" in SIGMA, the value
PI["q"] contains the information that is independent of "a" and
is needed to compute DELTA("q", "a") [2]. Since the array PI
has only m entries, whereas DELTA has O(m|SIGMA|) entries, we
save a factor of |SIGMA| in the preprocessing time by computing
PI rather than DELTA.
[1] Cormen, Leiserson, Rivest, Stein
Introdcution to Algorithms, 2nd Edition, MIT Press
[2] See finite automation theory
Signed-off-by: Thomas Graf <tgraf@suug.ch>
Signed-off-by: David S. Miller <davem@davemloft.net>
2005-06-23 20:58:37 -07:00
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2005-08-25 16:12:22 -07:00
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2005-08-25 16:23:11 -07:00
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2005-08-25 16:12:22 -07:00
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2005-06-23 20:59:16 -07:00
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2005-06-24 17:39:03 -07:00
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2005-06-23 20:59:16 -07:00
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2009-11-20 20:13:39 +01:00
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2007-02-11 15:41:31 +00:00
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2006-12-13 00:35:00 -08:00
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2007-02-11 15:41:31 +00:00
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2006-12-13 00:35:00 -08:00
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2007-05-06 14:49:09 -07:00
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2007-08-22 14:01:36 -07:00
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2008-12-13 21:20:27 +10:30
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2009-01-01 10:12:30 +10:30
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2011-01-19 11:03:25 +00:00
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2009-03-04 14:53:30 +08:00
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2009-06-12 21:10:05 +00:00
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2009-09-25 16:07:19 -07:00
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2010-11-16 10:58:37 +09:00
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2011-03-01 20:03:05 +01:00
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2010-11-16 10:58:37 +09:00
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2005-06-23 20:49:30 -07:00
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