linux/lib/lzo/lzo1x_decompress_safe.c

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// SPDX-License-Identifier: GPL-2.0-only
/*
* LZO1X Decompressor from LZO
*
* Copyright (C) 1996-2012 Markus F.X.J. Oberhumer <markus@oberhumer.com>
*
* The full LZO package can be found at:
* http://www.oberhumer.com/opensource/lzo/
*
* Changed for Linux kernel use by:
* Nitin Gupta <nitingupta910@gmail.com>
* Richard Purdie <rpurdie@openedhand.com>
*/
lib: add support for LZO-compressed kernels This patch series adds generic support for creating and extracting LZO-compressed kernel images, as well as support for using such images on the x86 and ARM architectures, and support for creating and using LZO-compressed initrd and initramfs images. Russell King said: : Testing on a Cortex A9 model: : - lzo decompressor is 65% of the time gzip takes to decompress a kernel : - lzo kernel is 9% larger than a gzip kernel : : which I'm happy to say confirms your figures when comparing the two. : : However, when comparing your new gzip code to the old gzip code: : - new is 99% of the size of the old code : - new takes 42% of the time to decompress than the old code : : What this means is that for a proper comparison, the results get even better: : - lzo is 7.5% larger than the old gzip'd kernel image : - lzo takes 28% of the time that the old gzip code took : : So the expense seems definitely worth the effort. The only reason I : can think of ever using gzip would be if you needed the additional : compression (eg, because you have limited flash to store the image.) : : I would argue that the default for ARM should therefore be LZO. This patch: The lzo compressor is worse than gzip at compression, but faster at extraction. Here are some figures for an ARM board I'm working on: Uncompressed size: 3.24Mo gzip 1.61Mo 0.72s lzo 1.75Mo 0.48s So for a compression ratio that is still relatively close to gzip, it's much faster to extract, at least in that case. This part contains: - Makefile routine to support lzo compression - Fixes to the existing lzo compressor so that it can be used in compressed kernels - wrapper around the existing lzo1x_decompress, as it only extracts one block at a time, while we need to extract a whole file here - config dialog for kernel compression [akpm@linux-foundation.org: coding-style fixes] [akpm@linux-foundation.org: cleanup] Signed-off-by: Albin Tonnerre <albin.tonnerre@free-electrons.com> Tested-by: Wu Zhangjin <wuzhangjin@gmail.com> Acked-by: "H. Peter Anvin" <hpa@zytor.com> Cc: Ingo Molnar <mingo@elte.hu> Cc: Thomas Gleixner <tglx@linutronix.de> Tested-by: Russell King <rmk@arm.linux.org.uk> Acked-by: Russell King <rmk@arm.linux.org.uk> Cc: Ralf Baechle <ralf@linux-mips.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2010-01-08 23:42:42 +01:00
#ifndef STATIC
#include <linux/module.h>
#include <linux/kernel.h>
lib: add support for LZO-compressed kernels This patch series adds generic support for creating and extracting LZO-compressed kernel images, as well as support for using such images on the x86 and ARM architectures, and support for creating and using LZO-compressed initrd and initramfs images. Russell King said: : Testing on a Cortex A9 model: : - lzo decompressor is 65% of the time gzip takes to decompress a kernel : - lzo kernel is 9% larger than a gzip kernel : : which I'm happy to say confirms your figures when comparing the two. : : However, when comparing your new gzip code to the old gzip code: : - new is 99% of the size of the old code : - new takes 42% of the time to decompress than the old code : : What this means is that for a proper comparison, the results get even better: : - lzo is 7.5% larger than the old gzip'd kernel image : - lzo takes 28% of the time that the old gzip code took : : So the expense seems definitely worth the effort. The only reason I : can think of ever using gzip would be if you needed the additional : compression (eg, because you have limited flash to store the image.) : : I would argue that the default for ARM should therefore be LZO. This patch: The lzo compressor is worse than gzip at compression, but faster at extraction. Here are some figures for an ARM board I'm working on: Uncompressed size: 3.24Mo gzip 1.61Mo 0.72s lzo 1.75Mo 0.48s So for a compression ratio that is still relatively close to gzip, it's much faster to extract, at least in that case. This part contains: - Makefile routine to support lzo compression - Fixes to the existing lzo compressor so that it can be used in compressed kernels - wrapper around the existing lzo1x_decompress, as it only extracts one block at a time, while we need to extract a whole file here - config dialog for kernel compression [akpm@linux-foundation.org: coding-style fixes] [akpm@linux-foundation.org: cleanup] Signed-off-by: Albin Tonnerre <albin.tonnerre@free-electrons.com> Tested-by: Wu Zhangjin <wuzhangjin@gmail.com> Acked-by: "H. Peter Anvin" <hpa@zytor.com> Cc: Ingo Molnar <mingo@elte.hu> Cc: Thomas Gleixner <tglx@linutronix.de> Tested-by: Russell King <rmk@arm.linux.org.uk> Acked-by: Russell King <rmk@arm.linux.org.uk> Cc: Ralf Baechle <ralf@linux-mips.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2010-01-08 23:42:42 +01:00
#endif
#include <asm/unaligned.h>
lib: add support for LZO-compressed kernels This patch series adds generic support for creating and extracting LZO-compressed kernel images, as well as support for using such images on the x86 and ARM architectures, and support for creating and using LZO-compressed initrd and initramfs images. Russell King said: : Testing on a Cortex A9 model: : - lzo decompressor is 65% of the time gzip takes to decompress a kernel : - lzo kernel is 9% larger than a gzip kernel : : which I'm happy to say confirms your figures when comparing the two. : : However, when comparing your new gzip code to the old gzip code: : - new is 99% of the size of the old code : - new takes 42% of the time to decompress than the old code : : What this means is that for a proper comparison, the results get even better: : - lzo is 7.5% larger than the old gzip'd kernel image : - lzo takes 28% of the time that the old gzip code took : : So the expense seems definitely worth the effort. The only reason I : can think of ever using gzip would be if you needed the additional : compression (eg, because you have limited flash to store the image.) : : I would argue that the default for ARM should therefore be LZO. This patch: The lzo compressor is worse than gzip at compression, but faster at extraction. Here are some figures for an ARM board I'm working on: Uncompressed size: 3.24Mo gzip 1.61Mo 0.72s lzo 1.75Mo 0.48s So for a compression ratio that is still relatively close to gzip, it's much faster to extract, at least in that case. This part contains: - Makefile routine to support lzo compression - Fixes to the existing lzo compressor so that it can be used in compressed kernels - wrapper around the existing lzo1x_decompress, as it only extracts one block at a time, while we need to extract a whole file here - config dialog for kernel compression [akpm@linux-foundation.org: coding-style fixes] [akpm@linux-foundation.org: cleanup] Signed-off-by: Albin Tonnerre <albin.tonnerre@free-electrons.com> Tested-by: Wu Zhangjin <wuzhangjin@gmail.com> Acked-by: "H. Peter Anvin" <hpa@zytor.com> Cc: Ingo Molnar <mingo@elte.hu> Cc: Thomas Gleixner <tglx@linutronix.de> Tested-by: Russell King <rmk@arm.linux.org.uk> Acked-by: Russell King <rmk@arm.linux.org.uk> Cc: Ralf Baechle <ralf@linux-mips.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2010-01-08 23:42:42 +01:00
#include <linux/lzo.h>
#include "lzodefs.h"
#define HAVE_IP(x) ((size_t)(ip_end - ip) >= (size_t)(x))
#define HAVE_OP(x) ((size_t)(op_end - op) >= (size_t)(x))
#define NEED_IP(x) if (!HAVE_IP(x)) goto input_overrun
#define NEED_OP(x) if (!HAVE_OP(x)) goto output_overrun
#define TEST_LB(m_pos) if ((m_pos) < out) goto lookbehind_overrun
/* This MAX_255_COUNT is the maximum number of times we can add 255 to a base
* count without overflowing an integer. The multiply will overflow when
* multiplying 255 by more than MAXINT/255. The sum will overflow earlier
* depending on the base count. Since the base count is taken from a u8
* and a few bits, it is safe to assume that it will always be lower than
* or equal to 2*255, thus we can always prevent any overflow by accepting
* two less 255 steps. See Documentation/lzo.txt for more information.
*/
#define MAX_255_COUNT ((((size_t)~0) / 255) - 2)
int lzo1x_decompress_safe(const unsigned char *in, size_t in_len,
unsigned char *out, size_t *out_len)
{
unsigned char *op;
const unsigned char *ip;
size_t t, next;
size_t state = 0;
const unsigned char *m_pos;
const unsigned char * const ip_end = in + in_len;
unsigned char * const op_end = out + *out_len;
lib/lzo: implement run-length encoding Patch series "lib/lzo: run-length encoding support", v5. Following on from the previous lzo-rle patchset: https://lkml.org/lkml/2018/11/30/972 This patchset contains only the RLE patches, and should be applied on top of the non-RLE patches ( https://lkml.org/lkml/2019/2/5/366 ). Previously, some questions were raised around the RLE patches. I've done some additional benchmarking to answer these questions. In short: - RLE offers significant additional performance (data-dependent) - I didn't measure any regressions that were clearly outside the noise One concern with this patchset was around performance - specifically, measuring RLE impact separately from Matt Sealey's patches (CTZ & fast copy). I have done some additional benchmarking which I hope clarifies the benefits of each part of the patchset. Firstly, I've captured some memory via /dev/fmem from a Chromebook with many tabs open which is starting to swap, and then split this into 4178 4k pages. I've excluded the all-zero pages (as zram does), and also the no-zero pages (which won't tell us anything about RLE performance). This should give a realistic test dataset for zram. What I found was that the data is VERY bimodal: 44% of pages in this dataset contain 5% or fewer zeros, and 44% contain over 90% zeros (30% if you include the no-zero pages). This supports the idea of special-casing zeros in zram. Next, I've benchmarked four variants of lzo on these pages (on 64-bit Arm at max frequency): baseline LZO; baseline + Matt Sealey's patches (aka MS); baseline + RLE only; baseline + MS + RLE. Numbers are for weighted roundtrip throughput (the weighting reflects that zram does more compression than decompression). https://drive.google.com/file/d/1VLtLjRVxgUNuWFOxaGPwJYhl_hMQXpHe/view?usp=sharing Matt's patches help in all cases for Arm (and no effect on Intel), as expected. RLE also behaves as expected: with few zeros present, it makes no difference; above ~75%, it gives a good improvement (50 - 300 MB/s on top of the benefit from Matt's patches). Best performance is seen with both MS and RLE patches. Finally, I have benchmarked the same dataset on an x86-64 device. Here, the MS patches make no difference (as expected); RLE helps, similarly as on Arm. There were no definite regressions; allowing for observational error, 0.1% (3/4178) of cases had a regression > 1 standard deviation, of which the largest was 4.6% (1.2 standard deviations). I think this is probably within the noise. https://drive.google.com/file/d/1xCUVwmiGD0heEMx5gcVEmLBI4eLaageV/view?usp=sharing One point to note is that the graphs show RLE appears to help very slightly with no zeros present! This is because the extra code causes the clang optimiser to change code layout in a way that happens to have a significant benefit. Taking baseline LZO and adding a do-nothing line like "__builtin_prefetch(out_len);" immediately before the "goto next" has the same effect. So this is a real, but basically spurious effect - it's small enough not to upset the overall findings. This patch (of 3): When using zram, we frequently encounter long runs of zero bytes. This adds a special case which identifies runs of zeros and encodes them using run-length encoding. This is faster for both compression and decompresion. For high-entropy data which doesn't hit this case, impact is minimal. Compression ratio is within a few percent in all cases. This modifies the bitstream in a way which is backwards compatible (i.e., we can decompress old bitstreams, but old versions of lzo cannot decompress new bitstreams). Link: http://lkml.kernel.org/r/20190205155944.16007-2-dave.rodgman@arm.com Signed-off-by: Dave Rodgman <dave.rodgman@arm.com> Cc: David S. Miller <davem@davemloft.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Herbert Xu <herbert@gondor.apana.org.au> Cc: Markus F.X.J. Oberhumer <markus@oberhumer.com> Cc: Matt Sealey <matt.sealey@arm.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Nitin Gupta <nitingupta910@gmail.com> Cc: Richard Purdie <rpurdie@openedhand.com> Cc: Sergey Senozhatsky <sergey.senozhatsky.work@gmail.com> Cc: Sonny Rao <sonnyrao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-03-08 01:30:40 +01:00
unsigned char bitstream_version;
op = out;
ip = in;
if (unlikely(in_len < 3))
goto input_overrun;
lib/lzo: implement run-length encoding Patch series "lib/lzo: run-length encoding support", v5. Following on from the previous lzo-rle patchset: https://lkml.org/lkml/2018/11/30/972 This patchset contains only the RLE patches, and should be applied on top of the non-RLE patches ( https://lkml.org/lkml/2019/2/5/366 ). Previously, some questions were raised around the RLE patches. I've done some additional benchmarking to answer these questions. In short: - RLE offers significant additional performance (data-dependent) - I didn't measure any regressions that were clearly outside the noise One concern with this patchset was around performance - specifically, measuring RLE impact separately from Matt Sealey's patches (CTZ & fast copy). I have done some additional benchmarking which I hope clarifies the benefits of each part of the patchset. Firstly, I've captured some memory via /dev/fmem from a Chromebook with many tabs open which is starting to swap, and then split this into 4178 4k pages. I've excluded the all-zero pages (as zram does), and also the no-zero pages (which won't tell us anything about RLE performance). This should give a realistic test dataset for zram. What I found was that the data is VERY bimodal: 44% of pages in this dataset contain 5% or fewer zeros, and 44% contain over 90% zeros (30% if you include the no-zero pages). This supports the idea of special-casing zeros in zram. Next, I've benchmarked four variants of lzo on these pages (on 64-bit Arm at max frequency): baseline LZO; baseline + Matt Sealey's patches (aka MS); baseline + RLE only; baseline + MS + RLE. Numbers are for weighted roundtrip throughput (the weighting reflects that zram does more compression than decompression). https://drive.google.com/file/d/1VLtLjRVxgUNuWFOxaGPwJYhl_hMQXpHe/view?usp=sharing Matt's patches help in all cases for Arm (and no effect on Intel), as expected. RLE also behaves as expected: with few zeros present, it makes no difference; above ~75%, it gives a good improvement (50 - 300 MB/s on top of the benefit from Matt's patches). Best performance is seen with both MS and RLE patches. Finally, I have benchmarked the same dataset on an x86-64 device. Here, the MS patches make no difference (as expected); RLE helps, similarly as on Arm. There were no definite regressions; allowing for observational error, 0.1% (3/4178) of cases had a regression > 1 standard deviation, of which the largest was 4.6% (1.2 standard deviations). I think this is probably within the noise. https://drive.google.com/file/d/1xCUVwmiGD0heEMx5gcVEmLBI4eLaageV/view?usp=sharing One point to note is that the graphs show RLE appears to help very slightly with no zeros present! This is because the extra code causes the clang optimiser to change code layout in a way that happens to have a significant benefit. Taking baseline LZO and adding a do-nothing line like "__builtin_prefetch(out_len);" immediately before the "goto next" has the same effect. So this is a real, but basically spurious effect - it's small enough not to upset the overall findings. This patch (of 3): When using zram, we frequently encounter long runs of zero bytes. This adds a special case which identifies runs of zeros and encodes them using run-length encoding. This is faster for both compression and decompresion. For high-entropy data which doesn't hit this case, impact is minimal. Compression ratio is within a few percent in all cases. This modifies the bitstream in a way which is backwards compatible (i.e., we can decompress old bitstreams, but old versions of lzo cannot decompress new bitstreams). Link: http://lkml.kernel.org/r/20190205155944.16007-2-dave.rodgman@arm.com Signed-off-by: Dave Rodgman <dave.rodgman@arm.com> Cc: David S. Miller <davem@davemloft.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Herbert Xu <herbert@gondor.apana.org.au> Cc: Markus F.X.J. Oberhumer <markus@oberhumer.com> Cc: Matt Sealey <matt.sealey@arm.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Nitin Gupta <nitingupta910@gmail.com> Cc: Richard Purdie <rpurdie@openedhand.com> Cc: Sergey Senozhatsky <sergey.senozhatsky.work@gmail.com> Cc: Sonny Rao <sonnyrao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-03-08 01:30:40 +01:00
if (likely(in_len >= 5) && likely(*ip == 17)) {
lib/lzo: implement run-length encoding Patch series "lib/lzo: run-length encoding support", v5. Following on from the previous lzo-rle patchset: https://lkml.org/lkml/2018/11/30/972 This patchset contains only the RLE patches, and should be applied on top of the non-RLE patches ( https://lkml.org/lkml/2019/2/5/366 ). Previously, some questions were raised around the RLE patches. I've done some additional benchmarking to answer these questions. In short: - RLE offers significant additional performance (data-dependent) - I didn't measure any regressions that were clearly outside the noise One concern with this patchset was around performance - specifically, measuring RLE impact separately from Matt Sealey's patches (CTZ & fast copy). I have done some additional benchmarking which I hope clarifies the benefits of each part of the patchset. Firstly, I've captured some memory via /dev/fmem from a Chromebook with many tabs open which is starting to swap, and then split this into 4178 4k pages. I've excluded the all-zero pages (as zram does), and also the no-zero pages (which won't tell us anything about RLE performance). This should give a realistic test dataset for zram. What I found was that the data is VERY bimodal: 44% of pages in this dataset contain 5% or fewer zeros, and 44% contain over 90% zeros (30% if you include the no-zero pages). This supports the idea of special-casing zeros in zram. Next, I've benchmarked four variants of lzo on these pages (on 64-bit Arm at max frequency): baseline LZO; baseline + Matt Sealey's patches (aka MS); baseline + RLE only; baseline + MS + RLE. Numbers are for weighted roundtrip throughput (the weighting reflects that zram does more compression than decompression). https://drive.google.com/file/d/1VLtLjRVxgUNuWFOxaGPwJYhl_hMQXpHe/view?usp=sharing Matt's patches help in all cases for Arm (and no effect on Intel), as expected. RLE also behaves as expected: with few zeros present, it makes no difference; above ~75%, it gives a good improvement (50 - 300 MB/s on top of the benefit from Matt's patches). Best performance is seen with both MS and RLE patches. Finally, I have benchmarked the same dataset on an x86-64 device. Here, the MS patches make no difference (as expected); RLE helps, similarly as on Arm. There were no definite regressions; allowing for observational error, 0.1% (3/4178) of cases had a regression > 1 standard deviation, of which the largest was 4.6% (1.2 standard deviations). I think this is probably within the noise. https://drive.google.com/file/d/1xCUVwmiGD0heEMx5gcVEmLBI4eLaageV/view?usp=sharing One point to note is that the graphs show RLE appears to help very slightly with no zeros present! This is because the extra code causes the clang optimiser to change code layout in a way that happens to have a significant benefit. Taking baseline LZO and adding a do-nothing line like "__builtin_prefetch(out_len);" immediately before the "goto next" has the same effect. So this is a real, but basically spurious effect - it's small enough not to upset the overall findings. This patch (of 3): When using zram, we frequently encounter long runs of zero bytes. This adds a special case which identifies runs of zeros and encodes them using run-length encoding. This is faster for both compression and decompresion. For high-entropy data which doesn't hit this case, impact is minimal. Compression ratio is within a few percent in all cases. This modifies the bitstream in a way which is backwards compatible (i.e., we can decompress old bitstreams, but old versions of lzo cannot decompress new bitstreams). Link: http://lkml.kernel.org/r/20190205155944.16007-2-dave.rodgman@arm.com Signed-off-by: Dave Rodgman <dave.rodgman@arm.com> Cc: David S. Miller <davem@davemloft.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Herbert Xu <herbert@gondor.apana.org.au> Cc: Markus F.X.J. Oberhumer <markus@oberhumer.com> Cc: Matt Sealey <matt.sealey@arm.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Nitin Gupta <nitingupta910@gmail.com> Cc: Richard Purdie <rpurdie@openedhand.com> Cc: Sergey Senozhatsky <sergey.senozhatsky.work@gmail.com> Cc: Sonny Rao <sonnyrao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-03-08 01:30:40 +01:00
bitstream_version = ip[1];
ip += 2;
} else {
bitstream_version = 0;
}
if (*ip > 17) {
t = *ip++ - 17;
if (t < 4) {
next = t;
goto match_next;
}
goto copy_literal_run;
}
for (;;) {
t = *ip++;
if (t < 16) {
if (likely(state == 0)) {
if (unlikely(t == 0)) {
size_t offset;
const unsigned char *ip_last = ip;
while (unlikely(*ip == 0)) {
ip++;
NEED_IP(1);
}
offset = ip - ip_last;
if (unlikely(offset > MAX_255_COUNT))
return LZO_E_ERROR;
offset = (offset << 8) - offset;
t += offset + 15 + *ip++;
}
t += 3;
copy_literal_run:
#if defined(CONFIG_HAVE_EFFICIENT_UNALIGNED_ACCESS)
if (likely(HAVE_IP(t + 15) && HAVE_OP(t + 15))) {
const unsigned char *ie = ip + t;
unsigned char *oe = op + t;
do {
COPY8(op, ip);
op += 8;
ip += 8;
COPY8(op, ip);
op += 8;
ip += 8;
} while (ip < ie);
ip = ie;
op = oe;
} else
#endif
{
NEED_OP(t);
NEED_IP(t + 3);
do {
*op++ = *ip++;
} while (--t > 0);
}
state = 4;
continue;
} else if (state != 4) {
next = t & 3;
m_pos = op - 1;
m_pos -= t >> 2;
m_pos -= *ip++ << 2;
TEST_LB(m_pos);
NEED_OP(2);
op[0] = m_pos[0];
op[1] = m_pos[1];
op += 2;
goto match_next;
} else {
next = t & 3;
m_pos = op - (1 + M2_MAX_OFFSET);
m_pos -= t >> 2;
m_pos -= *ip++ << 2;
t = 3;
}
} else if (t >= 64) {
next = t & 3;
m_pos = op - 1;
m_pos -= (t >> 2) & 7;
m_pos -= *ip++ << 3;
t = (t >> 5) - 1 + (3 - 1);
} else if (t >= 32) {
t = (t & 31) + (3 - 1);
if (unlikely(t == 2)) {
size_t offset;
const unsigned char *ip_last = ip;
while (unlikely(*ip == 0)) {
ip++;
NEED_IP(1);
}
offset = ip - ip_last;
if (unlikely(offset > MAX_255_COUNT))
return LZO_E_ERROR;
offset = (offset << 8) - offset;
t += offset + 31 + *ip++;
NEED_IP(2);
}
m_pos = op - 1;
next = get_unaligned_le16(ip);
ip += 2;
m_pos -= next >> 2;
next &= 3;
} else {
lib/lzo: implement run-length encoding Patch series "lib/lzo: run-length encoding support", v5. Following on from the previous lzo-rle patchset: https://lkml.org/lkml/2018/11/30/972 This patchset contains only the RLE patches, and should be applied on top of the non-RLE patches ( https://lkml.org/lkml/2019/2/5/366 ). Previously, some questions were raised around the RLE patches. I've done some additional benchmarking to answer these questions. In short: - RLE offers significant additional performance (data-dependent) - I didn't measure any regressions that were clearly outside the noise One concern with this patchset was around performance - specifically, measuring RLE impact separately from Matt Sealey's patches (CTZ & fast copy). I have done some additional benchmarking which I hope clarifies the benefits of each part of the patchset. Firstly, I've captured some memory via /dev/fmem from a Chromebook with many tabs open which is starting to swap, and then split this into 4178 4k pages. I've excluded the all-zero pages (as zram does), and also the no-zero pages (which won't tell us anything about RLE performance). This should give a realistic test dataset for zram. What I found was that the data is VERY bimodal: 44% of pages in this dataset contain 5% or fewer zeros, and 44% contain over 90% zeros (30% if you include the no-zero pages). This supports the idea of special-casing zeros in zram. Next, I've benchmarked four variants of lzo on these pages (on 64-bit Arm at max frequency): baseline LZO; baseline + Matt Sealey's patches (aka MS); baseline + RLE only; baseline + MS + RLE. Numbers are for weighted roundtrip throughput (the weighting reflects that zram does more compression than decompression). https://drive.google.com/file/d/1VLtLjRVxgUNuWFOxaGPwJYhl_hMQXpHe/view?usp=sharing Matt's patches help in all cases for Arm (and no effect on Intel), as expected. RLE also behaves as expected: with few zeros present, it makes no difference; above ~75%, it gives a good improvement (50 - 300 MB/s on top of the benefit from Matt's patches). Best performance is seen with both MS and RLE patches. Finally, I have benchmarked the same dataset on an x86-64 device. Here, the MS patches make no difference (as expected); RLE helps, similarly as on Arm. There were no definite regressions; allowing for observational error, 0.1% (3/4178) of cases had a regression > 1 standard deviation, of which the largest was 4.6% (1.2 standard deviations). I think this is probably within the noise. https://drive.google.com/file/d/1xCUVwmiGD0heEMx5gcVEmLBI4eLaageV/view?usp=sharing One point to note is that the graphs show RLE appears to help very slightly with no zeros present! This is because the extra code causes the clang optimiser to change code layout in a way that happens to have a significant benefit. Taking baseline LZO and adding a do-nothing line like "__builtin_prefetch(out_len);" immediately before the "goto next" has the same effect. So this is a real, but basically spurious effect - it's small enough not to upset the overall findings. This patch (of 3): When using zram, we frequently encounter long runs of zero bytes. This adds a special case which identifies runs of zeros and encodes them using run-length encoding. This is faster for both compression and decompresion. For high-entropy data which doesn't hit this case, impact is minimal. Compression ratio is within a few percent in all cases. This modifies the bitstream in a way which is backwards compatible (i.e., we can decompress old bitstreams, but old versions of lzo cannot decompress new bitstreams). Link: http://lkml.kernel.org/r/20190205155944.16007-2-dave.rodgman@arm.com Signed-off-by: Dave Rodgman <dave.rodgman@arm.com> Cc: David S. Miller <davem@davemloft.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Herbert Xu <herbert@gondor.apana.org.au> Cc: Markus F.X.J. Oberhumer <markus@oberhumer.com> Cc: Matt Sealey <matt.sealey@arm.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Nitin Gupta <nitingupta910@gmail.com> Cc: Richard Purdie <rpurdie@openedhand.com> Cc: Sergey Senozhatsky <sergey.senozhatsky.work@gmail.com> Cc: Sonny Rao <sonnyrao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-03-08 01:30:40 +01:00
NEED_IP(2);
next = get_unaligned_le16(ip);
if (((next & 0xfffc) == 0xfffc) &&
((t & 0xf8) == 0x18) &&
likely(bitstream_version)) {
NEED_IP(3);
t &= 7;
t |= ip[2] << 3;
t += MIN_ZERO_RUN_LENGTH;
NEED_OP(t);
memset(op, 0, t);
op += t;
next &= 3;
ip += 3;
goto match_next;
} else {
m_pos = op;
m_pos -= (t & 8) << 11;
t = (t & 7) + (3 - 1);
if (unlikely(t == 2)) {
size_t offset;
const unsigned char *ip_last = ip;
lib/lzo: implement run-length encoding Patch series "lib/lzo: run-length encoding support", v5. Following on from the previous lzo-rle patchset: https://lkml.org/lkml/2018/11/30/972 This patchset contains only the RLE patches, and should be applied on top of the non-RLE patches ( https://lkml.org/lkml/2019/2/5/366 ). Previously, some questions were raised around the RLE patches. I've done some additional benchmarking to answer these questions. In short: - RLE offers significant additional performance (data-dependent) - I didn't measure any regressions that were clearly outside the noise One concern with this patchset was around performance - specifically, measuring RLE impact separately from Matt Sealey's patches (CTZ & fast copy). I have done some additional benchmarking which I hope clarifies the benefits of each part of the patchset. Firstly, I've captured some memory via /dev/fmem from a Chromebook with many tabs open which is starting to swap, and then split this into 4178 4k pages. I've excluded the all-zero pages (as zram does), and also the no-zero pages (which won't tell us anything about RLE performance). This should give a realistic test dataset for zram. What I found was that the data is VERY bimodal: 44% of pages in this dataset contain 5% or fewer zeros, and 44% contain over 90% zeros (30% if you include the no-zero pages). This supports the idea of special-casing zeros in zram. Next, I've benchmarked four variants of lzo on these pages (on 64-bit Arm at max frequency): baseline LZO; baseline + Matt Sealey's patches (aka MS); baseline + RLE only; baseline + MS + RLE. Numbers are for weighted roundtrip throughput (the weighting reflects that zram does more compression than decompression). https://drive.google.com/file/d/1VLtLjRVxgUNuWFOxaGPwJYhl_hMQXpHe/view?usp=sharing Matt's patches help in all cases for Arm (and no effect on Intel), as expected. RLE also behaves as expected: with few zeros present, it makes no difference; above ~75%, it gives a good improvement (50 - 300 MB/s on top of the benefit from Matt's patches). Best performance is seen with both MS and RLE patches. Finally, I have benchmarked the same dataset on an x86-64 device. Here, the MS patches make no difference (as expected); RLE helps, similarly as on Arm. There were no definite regressions; allowing for observational error, 0.1% (3/4178) of cases had a regression > 1 standard deviation, of which the largest was 4.6% (1.2 standard deviations). I think this is probably within the noise. https://drive.google.com/file/d/1xCUVwmiGD0heEMx5gcVEmLBI4eLaageV/view?usp=sharing One point to note is that the graphs show RLE appears to help very slightly with no zeros present! This is because the extra code causes the clang optimiser to change code layout in a way that happens to have a significant benefit. Taking baseline LZO and adding a do-nothing line like "__builtin_prefetch(out_len);" immediately before the "goto next" has the same effect. So this is a real, but basically spurious effect - it's small enough not to upset the overall findings. This patch (of 3): When using zram, we frequently encounter long runs of zero bytes. This adds a special case which identifies runs of zeros and encodes them using run-length encoding. This is faster for both compression and decompresion. For high-entropy data which doesn't hit this case, impact is minimal. Compression ratio is within a few percent in all cases. This modifies the bitstream in a way which is backwards compatible (i.e., we can decompress old bitstreams, but old versions of lzo cannot decompress new bitstreams). Link: http://lkml.kernel.org/r/20190205155944.16007-2-dave.rodgman@arm.com Signed-off-by: Dave Rodgman <dave.rodgman@arm.com> Cc: David S. Miller <davem@davemloft.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Herbert Xu <herbert@gondor.apana.org.au> Cc: Markus F.X.J. Oberhumer <markus@oberhumer.com> Cc: Matt Sealey <matt.sealey@arm.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Nitin Gupta <nitingupta910@gmail.com> Cc: Richard Purdie <rpurdie@openedhand.com> Cc: Sergey Senozhatsky <sergey.senozhatsky.work@gmail.com> Cc: Sonny Rao <sonnyrao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-03-08 01:30:40 +01:00
while (unlikely(*ip == 0)) {
ip++;
NEED_IP(1);
}
offset = ip - ip_last;
if (unlikely(offset > MAX_255_COUNT))
return LZO_E_ERROR;
lib/lzo: implement run-length encoding Patch series "lib/lzo: run-length encoding support", v5. Following on from the previous lzo-rle patchset: https://lkml.org/lkml/2018/11/30/972 This patchset contains only the RLE patches, and should be applied on top of the non-RLE patches ( https://lkml.org/lkml/2019/2/5/366 ). Previously, some questions were raised around the RLE patches. I've done some additional benchmarking to answer these questions. In short: - RLE offers significant additional performance (data-dependent) - I didn't measure any regressions that were clearly outside the noise One concern with this patchset was around performance - specifically, measuring RLE impact separately from Matt Sealey's patches (CTZ & fast copy). I have done some additional benchmarking which I hope clarifies the benefits of each part of the patchset. Firstly, I've captured some memory via /dev/fmem from a Chromebook with many tabs open which is starting to swap, and then split this into 4178 4k pages. I've excluded the all-zero pages (as zram does), and also the no-zero pages (which won't tell us anything about RLE performance). This should give a realistic test dataset for zram. What I found was that the data is VERY bimodal: 44% of pages in this dataset contain 5% or fewer zeros, and 44% contain over 90% zeros (30% if you include the no-zero pages). This supports the idea of special-casing zeros in zram. Next, I've benchmarked four variants of lzo on these pages (on 64-bit Arm at max frequency): baseline LZO; baseline + Matt Sealey's patches (aka MS); baseline + RLE only; baseline + MS + RLE. Numbers are for weighted roundtrip throughput (the weighting reflects that zram does more compression than decompression). https://drive.google.com/file/d/1VLtLjRVxgUNuWFOxaGPwJYhl_hMQXpHe/view?usp=sharing Matt's patches help in all cases for Arm (and no effect on Intel), as expected. RLE also behaves as expected: with few zeros present, it makes no difference; above ~75%, it gives a good improvement (50 - 300 MB/s on top of the benefit from Matt's patches). Best performance is seen with both MS and RLE patches. Finally, I have benchmarked the same dataset on an x86-64 device. Here, the MS patches make no difference (as expected); RLE helps, similarly as on Arm. There were no definite regressions; allowing for observational error, 0.1% (3/4178) of cases had a regression > 1 standard deviation, of which the largest was 4.6% (1.2 standard deviations). I think this is probably within the noise. https://drive.google.com/file/d/1xCUVwmiGD0heEMx5gcVEmLBI4eLaageV/view?usp=sharing One point to note is that the graphs show RLE appears to help very slightly with no zeros present! This is because the extra code causes the clang optimiser to change code layout in a way that happens to have a significant benefit. Taking baseline LZO and adding a do-nothing line like "__builtin_prefetch(out_len);" immediately before the "goto next" has the same effect. So this is a real, but basically spurious effect - it's small enough not to upset the overall findings. This patch (of 3): When using zram, we frequently encounter long runs of zero bytes. This adds a special case which identifies runs of zeros and encodes them using run-length encoding. This is faster for both compression and decompresion. For high-entropy data which doesn't hit this case, impact is minimal. Compression ratio is within a few percent in all cases. This modifies the bitstream in a way which is backwards compatible (i.e., we can decompress old bitstreams, but old versions of lzo cannot decompress new bitstreams). Link: http://lkml.kernel.org/r/20190205155944.16007-2-dave.rodgman@arm.com Signed-off-by: Dave Rodgman <dave.rodgman@arm.com> Cc: David S. Miller <davem@davemloft.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Herbert Xu <herbert@gondor.apana.org.au> Cc: Markus F.X.J. Oberhumer <markus@oberhumer.com> Cc: Matt Sealey <matt.sealey@arm.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Nitin Gupta <nitingupta910@gmail.com> Cc: Richard Purdie <rpurdie@openedhand.com> Cc: Sergey Senozhatsky <sergey.senozhatsky.work@gmail.com> Cc: Sonny Rao <sonnyrao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-03-08 01:30:40 +01:00
offset = (offset << 8) - offset;
t += offset + 7 + *ip++;
NEED_IP(2);
next = get_unaligned_le16(ip);
}
ip += 2;
m_pos -= next >> 2;
next &= 3;
if (m_pos == op)
goto eof_found;
m_pos -= 0x4000;
}
}
TEST_LB(m_pos);
#if defined(CONFIG_HAVE_EFFICIENT_UNALIGNED_ACCESS)
if (op - m_pos >= 8) {
unsigned char *oe = op + t;
if (likely(HAVE_OP(t + 15))) {
do {
COPY8(op, m_pos);
op += 8;
m_pos += 8;
COPY8(op, m_pos);
op += 8;
m_pos += 8;
} while (op < oe);
op = oe;
if (HAVE_IP(6)) {
state = next;
COPY4(op, ip);
op += next;
ip += next;
continue;
}
} else {
NEED_OP(t);
do {
*op++ = *m_pos++;
} while (op < oe);
}
} else
#endif
{
unsigned char *oe = op + t;
NEED_OP(t);
op[0] = m_pos[0];
op[1] = m_pos[1];
op += 2;
m_pos += 2;
do {
*op++ = *m_pos++;
} while (op < oe);
}
match_next:
state = next;
t = next;
#if defined(CONFIG_HAVE_EFFICIENT_UNALIGNED_ACCESS)
if (likely(HAVE_IP(6) && HAVE_OP(4))) {
COPY4(op, ip);
op += t;
ip += t;
} else
#endif
{
NEED_IP(t + 3);
NEED_OP(t);
while (t > 0) {
*op++ = *ip++;
t--;
}
}
}
eof_found:
*out_len = op - out;
return (t != 3 ? LZO_E_ERROR :
ip == ip_end ? LZO_E_OK :
ip < ip_end ? LZO_E_INPUT_NOT_CONSUMED : LZO_E_INPUT_OVERRUN);
input_overrun:
*out_len = op - out;
return LZO_E_INPUT_OVERRUN;
output_overrun:
*out_len = op - out;
return LZO_E_OUTPUT_OVERRUN;
lookbehind_overrun:
*out_len = op - out;
return LZO_E_LOOKBEHIND_OVERRUN;
}
lib: add support for LZO-compressed kernels This patch series adds generic support for creating and extracting LZO-compressed kernel images, as well as support for using such images on the x86 and ARM architectures, and support for creating and using LZO-compressed initrd and initramfs images. Russell King said: : Testing on a Cortex A9 model: : - lzo decompressor is 65% of the time gzip takes to decompress a kernel : - lzo kernel is 9% larger than a gzip kernel : : which I'm happy to say confirms your figures when comparing the two. : : However, when comparing your new gzip code to the old gzip code: : - new is 99% of the size of the old code : - new takes 42% of the time to decompress than the old code : : What this means is that for a proper comparison, the results get even better: : - lzo is 7.5% larger than the old gzip'd kernel image : - lzo takes 28% of the time that the old gzip code took : : So the expense seems definitely worth the effort. The only reason I : can think of ever using gzip would be if you needed the additional : compression (eg, because you have limited flash to store the image.) : : I would argue that the default for ARM should therefore be LZO. This patch: The lzo compressor is worse than gzip at compression, but faster at extraction. Here are some figures for an ARM board I'm working on: Uncompressed size: 3.24Mo gzip 1.61Mo 0.72s lzo 1.75Mo 0.48s So for a compression ratio that is still relatively close to gzip, it's much faster to extract, at least in that case. This part contains: - Makefile routine to support lzo compression - Fixes to the existing lzo compressor so that it can be used in compressed kernels - wrapper around the existing lzo1x_decompress, as it only extracts one block at a time, while we need to extract a whole file here - config dialog for kernel compression [akpm@linux-foundation.org: coding-style fixes] [akpm@linux-foundation.org: cleanup] Signed-off-by: Albin Tonnerre <albin.tonnerre@free-electrons.com> Tested-by: Wu Zhangjin <wuzhangjin@gmail.com> Acked-by: "H. Peter Anvin" <hpa@zytor.com> Cc: Ingo Molnar <mingo@elte.hu> Cc: Thomas Gleixner <tglx@linutronix.de> Tested-by: Russell King <rmk@arm.linux.org.uk> Acked-by: Russell King <rmk@arm.linux.org.uk> Cc: Ralf Baechle <ralf@linux-mips.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2010-01-08 23:42:42 +01:00
#ifndef STATIC
EXPORT_SYMBOL_GPL(lzo1x_decompress_safe);
MODULE_LICENSE("GPL");
MODULE_DESCRIPTION("LZO1X Decompressor");
lib: add support for LZO-compressed kernels This patch series adds generic support for creating and extracting LZO-compressed kernel images, as well as support for using such images on the x86 and ARM architectures, and support for creating and using LZO-compressed initrd and initramfs images. Russell King said: : Testing on a Cortex A9 model: : - lzo decompressor is 65% of the time gzip takes to decompress a kernel : - lzo kernel is 9% larger than a gzip kernel : : which I'm happy to say confirms your figures when comparing the two. : : However, when comparing your new gzip code to the old gzip code: : - new is 99% of the size of the old code : - new takes 42% of the time to decompress than the old code : : What this means is that for a proper comparison, the results get even better: : - lzo is 7.5% larger than the old gzip'd kernel image : - lzo takes 28% of the time that the old gzip code took : : So the expense seems definitely worth the effort. The only reason I : can think of ever using gzip would be if you needed the additional : compression (eg, because you have limited flash to store the image.) : : I would argue that the default for ARM should therefore be LZO. This patch: The lzo compressor is worse than gzip at compression, but faster at extraction. Here are some figures for an ARM board I'm working on: Uncompressed size: 3.24Mo gzip 1.61Mo 0.72s lzo 1.75Mo 0.48s So for a compression ratio that is still relatively close to gzip, it's much faster to extract, at least in that case. This part contains: - Makefile routine to support lzo compression - Fixes to the existing lzo compressor so that it can be used in compressed kernels - wrapper around the existing lzo1x_decompress, as it only extracts one block at a time, while we need to extract a whole file here - config dialog for kernel compression [akpm@linux-foundation.org: coding-style fixes] [akpm@linux-foundation.org: cleanup] Signed-off-by: Albin Tonnerre <albin.tonnerre@free-electrons.com> Tested-by: Wu Zhangjin <wuzhangjin@gmail.com> Acked-by: "H. Peter Anvin" <hpa@zytor.com> Cc: Ingo Molnar <mingo@elte.hu> Cc: Thomas Gleixner <tglx@linutronix.de> Tested-by: Russell King <rmk@arm.linux.org.uk> Acked-by: Russell King <rmk@arm.linux.org.uk> Cc: Ralf Baechle <ralf@linux-mips.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2010-01-08 23:42:42 +01:00
#endif