This article was originally published on the School of Haskell.
TL;DR: perf
can be particularly helpful when profiling performance
critical sections of your programs. We show how through an example.
The perf_events
framework in the linux kernel, together with the
perf
userland tools, can be used to profile applications without any
instrumentation – beyond compiling them with debug symbols. The debug
symbols are specified in the DWARF format. Recently, support was added
to GHC to support DWARF debug symbols, thanks to work by Peter Wortmann.
In this article we go through the process of understanding the
performance of a low-level Haskell program – a function computing the
CRC32 digest of a ByteString
. We compare a pure Haskell version,
provided by the digest-pure
package; to a version using a C function
provided by zlib
, provided by the digest
package. After we
understand why the Haskell version is slower we modify it to make it
almost at fast as the C one.
Note that this document is meant to be a showcase of what can be done
with perf
, rather than a tutorial on how to make an Haskell program as
fast as a C one. In this case, the shortest route would have been to
directly replicate the behaviour of the C program in Haskell: we use
perf
to show how it’s possible to understand precisely where and why
time is being spent.
Getting up to speed with perf
and Haskell is easy but tedious and
undocumented. First, GHC HEAD (7.11) is needed, for DWARF support. GHC
7.10.1 has partial DWARF support, but some features are broken, so GHC
HEAD is recommended. The issues with GHC 7.10.1 are resolved in GHC 7.10.2, which will
be released shortly.
Moreover, the RTS and the libraries built as part of the GHC build process should be built with debug symbols. This can be done by adding
GhcRtsHcOpts += -g
GhcLibHcOpts += -g
to your mk/build.mk
file in the ghc
source tree.
Once you have GHC 7.11, special care is needed to install every library
with the right options when using cabal
. Specifically, we want to
pass the -g
options to GHC to generate debug symbols. Moreover, we
must stop cabal
from stripping the object files from debug symbols.
For example, to install the library digest
we’ll use
$ cabal install --disable-library-stripping --ghc-options="-g -rtsopts" digest
Moreover, when debugging Haskell code involving foreign C code, we need
to make sure that we have the debug symbols for the C libraries too.
This can be accomplished in various ways – on Debian systems debug
symbols are packaged separately in -dbg
packages. So if we wanted to
properly debug a program using the digest
library, which uses zlib
,
we would need to issue
$ sudo apt get install zlib1g-dbg
Moreover, if we want to see source code in the perf
tools, as we’ll
see in the following sections, we need to keep the Haskell source files
where they were picked up to be built. The easiest way to do this is
using cabal get
, for example:
$ cabal get zlib
Unpacking to zlib-0.6.1.0/
$ cd zlib-0.6.1.0
$ cabal install --disable-library-stripping --ghc-options="-g -rtsopts"
The same applies for C libraries that we want to debug with source code support.
As an example, we will be testing the digest-pure
library,
implementing the CRC32 algorithm in Haskell; against the digest
library, which also offers the CRC32 algorithm by binding to the zlib
library.
First we’ll build the zlib
library manually to keep the source code in
place, taking care of adding -g
to the CFLAGS
in the Makefile
:
$ wget http://zlib.net/zlib-1.2.8.tar.gz
$ tar xzvf zlib-1.2.8.tar.gz
$ cd zlib-1.2.8
$ nano Makefile.in # Add -g to CFLAGS
$ ./configure
$ make
$ export LD_LIBRARY_PATH=`pwd`:$LD_LIBRARY_PATH
Then, we’ll install the digest
and digest-pure
libraries, which we
need for the benchmark:
$ ghc --version
The Glorious Glasgow Haskell Compilation System, version 7.11.20150411
$ cabal get digest
Unpacking to digest-0.0.1.2/
$ cd digest-0.0.1.2/
$ cabal install --disable-library-stripping --ghc-options="-g -rtsopts"
$ cd ..
$ cabal get digest-pure
$ cd digest-pure-0.0.3/
$ cabal install --disable-library-stripping --ghc-options="-g -rtsopts"
Note how we’re getting the packages using cabal get
, so that the
Haskell sources will be preserved in the locations where the objects
were built from.
We’ll also install mwc-random
without bothering to keep the sources,
since we won’t need to inspect its functions (we use it to generate
random data to run our benchmark on):
$ cabal install --disable-library-stripping --ghc-options="-g -rtsopts" mwc-random
We’re going to use a simple benchmark to compare the Haskell and C function.
$ wget https://gist.github.com/bitonic/781ff80e6eb65eebf14a/raw/7cee087dbe12c6cf813667eccb0a00d721ecb9a6/crc32.hs
$ ghc -g -O2 crc32.hs
crc32.hs
let us compare two functions with an identical interface,
computing the CRC32 for a given ByteString
:
crc32 :: ByteString -> Word32
digest
implements this function by calling a foreign crc32
routine
provided by zlib
, while digest-pure
implements it natively in
Haskell.
Now we’re ready to compare the two versions, one using the pure CRC32, and one using zlib. First we generate some random data to work on
$ ./crc32 generate
This will write a data
file to disk, which we can use in all
subsequent tests. Then we time each version:
$ time ./crc32 hask # Using digest-pure
./crc32 hask 34,55s user 0,01s system 99% cpu 34,599 total
$ time ./crc32 c # Using digest
./crc32 c 10,42s user 0,00s system 99% cpu 10,444 total
The Haskell version is more than 3 times slower than the C one. Let’s try to find out why.
The first thing we’ll do is understand where time is spent. We expect some CRC32 function to make up for most of the running time, but we’d like to verify this. Moreover, we’d like to know what exactly is taking time in the CRC32 function itself.
Let’s run the two versions again, but this time using perf record
:
$ perf record -o perf-hask.data ./crc32 hask
[ perf record: Woken up 2 times to write data ]
[ perf record: Captured and wrote 0.346 MB perf-hask.data (~15126 samples) ]
$ perf record -o perf-c.data ./crc32 c
[ perf record: Woken up 1 times to write data ]
[ perf record: Captured and wrote 0.110 MB perf-c.data (~4789 samples) ]
perf record
will sample the execution with the aid of the
perf_event_open
linux syscall. Using perf report -i perf-hask.data
we can inspect the result of the Haskell version. The main screen shows
a breakdown of where time is spent in the executable:
Samples: 8K of event 'cpu-clock', Event count (approx.): 2233500000
99,75% crc32 crc32 [.] s4Tw_info
0,10% crc32 crc32 [.] c5gn_info
0,03% crc32 crc32 [.] c5g3_info
0,02% crc32 crc32 [.] c2k_info
0,02% crc32 crc32 [.] c7F_info
0,01% crc32 [kernel.kallsyms] [k] __do_softirq
0,01% crc32 crc32 [.] allocatePinned
0,01% crc32 crc32 [.] c6le_info
0,01% crc32 crc32 [.] chg3_info
0,01% crc32 crc32 [.] 0x000000000041ca88
0,01% crc32 libc-2.19.so [.] _dl_addr
Symbols like c5gn_info
are generated by the GHC code generator. As we
can see, almost all the time is spent in a single symbol, s4Tw_info
.
We can drill down into s4Tw_info
, and “annotate” it, to get a precise
breakdown of where time is spent in s4Tw_alone
:
s4Tw_info /home/francesco/crc32/crc32
│ Disassembly of section .text:
│
│ 000000000063a738 <s4Tw_info>:
│ crc = flipAll prevCRC
│ flipAll = xor 0xffffffff
│
│ -- | Unsafe array access.
│ (!!!) :: (IArray a e, Ix i, Integral i) => a i e -> i -> e
│ arr !!! i = unsafeAt arr $ fromIntegral i
0,79 │ 0:┌─→add $0x10,%r12
10,33 │ │ cmp 0x358(%r13),%r12
│ │↓ ja 27
0,04 │ │ cmp %rdi,%rsi
0,01 │ │↓ jne 36
│ │ movq $0xa737a0,-0x8(%r12)
│ │ mov %r14,(%r12)
│ │ lea -0x7(%r12),%rbx
│ │↓ jmpq ffffffffff9c58c8
│27:│ movq $0x10,0x388(%r13)
│ │↓ jmpq ffffffffff9c58c8
│ │ flipAll (tblEntry `xor` (crc `shiftR` 8))
│ │ where
│ │ -- Note: unsafe access is ok here, we guarantee that the value is within
│ │ -- (0..255), crc32Table covers that range.
│ │ tblEntry = crc32Table !!! ((crc `xor` (fromIntegral c)) .&. 0xff)
│ │ crc = flipAll prevCRC
0,76 │36:│ add $0xfffffffffffffff0,%r12
0,02 │ │ mov $0xffffffff,%eax
10,01 │ │ xor %rax,%r14
0,03 │ │ mov $0xffffffff,%eax
1,07 │ │ mov %r14,%rcx
│ │ shr $0x8,%rcx
10,55 │ │ xor %rax,%rcx
0,10 │ │ mov 0x4(%rbx),%rax
1,03 │ │ movzbl (%rsi),%edx
0,16 │ │ xor %rdx,%r14
9,69 │ │ and $0xff,%r14d
0,75 │ │ mov 0x10(%rax,%r14,4),%eax
44,32 │ │ xor %rcx,%rax
10,31 │ │ inc %rsi
0,01 │ │ mov %rax,%r14
│ └──jmp 0
What this breakdown tells us is that a whopping 75% of the time is spent
in xor
and and
instructions alone. Another 20% of the time is spent
in looping code: a cmp
at the beginning, and an inc
at the end –
which keep track of an index in the ByteString
we’re digesting to find
out when we’re done traversing it. Moreover, we get the Haskell source
code interleaved with the assembly deriving from it, which lets us
understand what Haskell code parts of s4Tw_info
correspond to. In
this case, the part that eats almost all of the time is
the section of the code corresponding to the main section of the CRC32 algorithm,
which is what we expected. What the code does is get a value out of pre
computed table, and then use it together with the current CRC to get the
new value.
To get more information about the symbol, we can also use objdump
on
the binary to get more information about the “compile unit” s4Tw_info
comes from:
$ objdump -Wi crc32
[...]
Compilation Unit @ offset 0xdbd68:
Length: 0x629 (32-bit)
Version: 3
Abbrev Offset: 0x6cb
Pointer Size: 8
<0><dbd73>: Abbrev Number: 1 (DW_TAG_compile_unit)
<dbd74> DW_AT_name : src/Data/Digest/Pure/CRC32.hs
<dbd92> DW_AT_producer : The Glorious Glasgow Haskell Compilation System 7.11.20150411
<dbdd0> DW_AT_language : 0x18 (Unknown: 18)
<dbdd4> DW_AT_comp_dir : /tmp/digest-pure-0.0.3/
<dbdec> DW_AT_use_UTF8 : 255
<dbded> DW_AT_stmt_list : 0x32790
[...]
<1><dbf83>: Abbrev Number: 2 (DW_TAG_subprogram)
<dbf84> DW_AT_name : !!!
<dbf88> DW_AT_MIPS_linkage_name: s4Tw_info
<dbf92> DW_AT_external : 0
<dbf93> DW_AT_low_pc : 0x63afc8
<dbf9b> DW_AT_high_pc : 0x63b03a
<dbfa3> DW_AT_frame_base : 1 byte block: 9c (DW_OP_call_frame_cfa)
[...]
Which tells us the exact file the symbol comes from. The DWARF
information also takes a stab at pairing the symbol with a name,
although it is often difficult to do so: in this case it picked the
inlined !!!
function, which is misleading.
Check out this screencast for a taste
of what interacting with perf
on this data set looks like.
Now let’s do the same with the C version, using perf report -i perf-c.data
:
In this case almost all the time is spent in libz.so
crc32
function,
which is again what we expect. However when drilling into the crc32
function, we get a much bigger disassemble output. While confusing at
first, it is quite clear that all the time is spent in the mysterious
DOLIT32
, a rather long section of the code:
│ DOLIT32;
0,04 │ 70: xor (%r8),%edi
1,29 │ mov %rdi,%rax
│ mov %edi,%r11d
│ movzbl %ah,%ebx
2,31 │ movzbl %dil,%eax
0,04 │ shr $0x18,%edi
│ mov 0xc00(%rcx,%rax,4),%eax
3,33 │ xor (%rcx,%rdi,4),%eax
2,76 │ shr $0x10,%r11d
[...omitted code...]
│ shr $0x18,%edi
1,17 │ shr $0x10,%r11d
0,08 │ movzbl %ah,%eax
1,06 │ mov (%rcx,%rdi,4),%edi
4,20 │ xor 0xc00(%rcx,%rbx,4),%edi
2,38 │ movzbl %r11b,%r11d
│ xor 0x800(%rcx,%rax,4),%edi
1,14 │ xor 0x400(%rcx,%r11,4),%edi
In fact, summing up the small percentages in DOLIT32
we find out that
around 85% of the time is spent there. To find out what DOLIT32
does
we need to consult the
zlib
source code.
DOLIT32
is a macro repeating DOLIT4
8 times. DOLIT4
is a macro
which computes the CRC32 4 bytes at a time, assuming little endianness.
Equivalent macros for big endian architecture are present.
The fact that zlib
computes the CRC32 4 bytes at a time, and that it
unrolls the main loop makes the code per byte needed to compute the
CRC32 much smaller. The loop (from cmp
to jmp
) with DOLIT32
as a
body uses around 110 instructions to compute the CRC32 for 32 bytes
(≈3.5 instructions per byte), while the loop generated from the pure
Haskell version uses 25 instructions for just one byte. This should
amount to a seven fold increase in the instructions executed by the
Haskell program.
We can easily verify this fact using perf
. In this case we’ll use
perf stat
, which gives us global statistics, since we know that one
symbol is taking up all the time. Otherwise we could use perf record -e
to record the events we’re interested and get figures for the
specific symbols.
$ perf stat ./crc32 hask
Performance counter stats for './crc32 hask':
35623,015084 task-clock (msec) # 0,995 CPUs utilized
4.982 context-switches # 0,140 K/sec
207 cpu-migrations # 0,006 K/sec
3.318 page-faults # 0,093 K/sec
94.594.036.631 cycles # 2,655 GHz
44.565.899.687 stalled-cycles-frontend # 47,11% frontend cycles idle
<not supported> stalled-cycles-backend
210.111.081.169 instructions # 2,22 insns per cycle
# 0,21 stalled cycles per insn
30.020.583.035 branches # 842,730 M/sec
1.138.765 branch-misses # 0,00% of all branches
35,788883623 seconds time elapsed
$ perf stat ./crc32 c
Performance counter stats for './crc32 c':
10690,308263 task-clock (msec) # 0,995 CPUs utilized
1.754 context-switches # 0,164 K/sec
63 cpu-migrations # 0,006 K/sec
3.314 page-faults # 0,310 K/sec
28.453.816.903 cycles # 2,662 GHz
18.427.339.226 stalled-cycles-frontend # 64,76% frontend cycles idle
<not supported> stalled-cycles-backend
31.027.193.409 instructions # 1,09 insns per cycle
# 0,59 stalled cycles per insn
330.594.059 branches # 30,925 M/sec
670.612 branch-misses # 0,20% of all branches
10,743639214 seconds time elapsed
The first thing to notice is the difference in the number of instructions. The Haskell program uses 201 billions, versus the 31 billions of the C program. A 6.5 difference, which is a factor close to our rough estimate of 7.
Note that the 6.5 difference in instructions does not translate to a 6.5
performance increase in the C program. This can be due to a variety
of reasons, but the perf stat
output already shows a factor: the C
version spends more time stalled, as evident from the
stalled-cycles-frontend
hardware counter. This is most likely since
the C code spends less time in the loop code, and more time fetching
bytes from the input buffer and from the static tables used to compute
the CRC32. In fact, the overall productivity is lower: 1 instruction
per cycle in C versus more than 2 in Haskell. Thus, we only get a 3x
speedup in C , as we have seen.
Now that we know the main reason for the Haskell version being slower, we can make the Haskell version more similar to the C one. The first measure we adopted is to implement the CRC32 algorithm so that it consumes 4 bytes at a time. We choose to do this before loop unrolling because it has more possibilities to impact performance. For instance it makes the algorithm less sequential and increases the chances for pipelining, since we don’t have to wait for each byte to continue.
To do so, we will split the input ByteString
in three sections: an
aligned vector of Word32
s, and the remaining unaligned leading and
trailing bytes. For example, for a ByteString
of length 26 starting
at address 9, we will have 3 leading bytes (up to address 12), 6 aligned
words (up to address 38), and 2 trailing bytes. This will give us a
memory-aligned section to perform the CRC32 word-by-word instead of
byte-by-byte. The type signature for the function splitting the
ByteString
will be
getWord32Vector
:: BS.ByteString
-> (BS.ByteString -> V.Vector Word32 -> BS.ByteString -> IO a)
-> IO a
We use a continuation-passing style since we need to manipulate the
pointer underlying the ByteString
to know where the aligned section of
the memory starts, and the functions that let us do this use CPS
themselves.
Once we have this function, the ugly part is over: we can very easily
port the algorithm present in zlib
to Haskell, but in a more
functional style:
{-# NOINLINE crc32UpdateLittle #-}
crc32UpdateLittle
:: Word32
-- ^ The previous CRC
-> BS.ByteString
-- ^ The input to digest
-> Word32
-- ^ Resulting CRC
crc32UpdateLittle prevC bs =
unsafePerformIO $ getWord32Vector bs $ \leading aligned trailing -> do
let c0 = complement prevC
let c1 = BS.foldl' word8Step c0 leading -- Perform CRC32 on the leading bytes...
let c2 = V.foldl' word32Step c1 aligned -- ...on the aligned words...
let c3 = BS.foldl' word8Step c2 trailing -- ...and on the trailing bytes.
return $ complement c3
where
{-# INLINE word32Step #-}
word32Step :: Word32 -> Word32 -> Word32
word32Step c0 word =
(crc32Table_3 !!! (c .&. 0xff)) `xor`
(crc32Table_2 !!! ((c `unsafeShiftR` 8) .&. 0xff)) `xor`
(crc32Table_1 !!! ((c `unsafeShiftR` 16) .&. 0xff)) `xor`
(crc32Table_0 !!! (c `unsafeShiftR` 24))
where
c = c0 `xor` word
{-# INLINE word8Step #-}
word8Step :: Word32 -> Word8 -> Word32
word8Step c byte =
(crc32Table_0 !!! ((c `xor` fromIntegral byte) .&. 0xff)) `xor` (c `unsafeShiftR` 8)
The various crc32Table_n
are various pre-computed tables needed to
perform the algorithm, and !!!
is an unsafe indexing operator (we know
we’re going to be within the bounds). The Little
is to indicate that
this is the algorithm for little-endian architectures. A matching
crc32UpdateBig
has to be defined for big-endian architectures.
You can find the full source in my fork of digest-pure
.
After we recompile digest-pure
again with the changes above, and
recompile our crc32.hs
benchmark, we can run it again using the
Haskell version:
$ time ./crc32 hask
./crc32 hask 12,87s user 0,02s system 99% cpu 12,903 total
With the new algorithm we get a three fold speedup, and we’re only 20% slower than the C version.
$ perf stat ./crc32 hask
Performance counter stats for './crc32 hask':
13025,715282 task-clock (msec) # 0,993 CPUs utilized
1.668 context-switches # 0,128 K/sec
61 cpu-migrations # 0,005 K/sec
3.340 page-faults # 0,256 K/sec
35.174.753.255 cycles # 2,700 GHz
15.093.419.773 stalled-cycles-frontend # 42,91% frontend cycles idle
<not supported> stalled-cycles-backend
77.735.375.354 instructions # 2,21 insns per cycle
# 0,19 stalled cycles per insn
2.541.638.382 branches # 195,125 M/sec
956.494 branch-misses # 0,04% of all branches
13,121155788 seconds time elapsed
The number of instructions is reduced by almost three times, while the productivity stays the same – which explains the threefold increase in performance. Note that we’re still using more than twice the instructions as the C program, due to loop unrolling. However, loop unrolling seems to push the program towards being memory-bound and thus does not result in a great performance increase. We have not pursued this road further.
However, when analyzing the program through perf report
, we get
somewhat surprising results:
│ crc32UpdateLittle :: Word32 -> BS.ByteString -> Word32
│ crc32UpdateLittle prevC bs =
│ unsafePerformIO $ getWord32Vector bs $ \leading aligned trailing -> do
│ let c0 = complement prevC
│ let c1 = BS.foldl' word8Step c0 leading
│ let c2 = V.foldl' word32Step c1 aligned
0,05 │ 9: mov 0xe(%rbx),%rax
0,03 │ mov 0x16(%rbx),%rax
7,21 │ mov 0x1e(%rbx),%rax
0,01 │ mov 0x26(%rbx),%rax
0,06 │ mov 0x3e(%rbx),%rax
0,02 │ mov 0x46(%rbx),%rcx
7,27 │ mov 0x4e(%rbx),%rdx
0,02 │ mov 0x56(%rbx),%rdi
0,08 │ mov 0x36(%rbx),%r8
0,03 │ mov (%r8,%rsi,4),%r8d
7,34 │ xor %r8,%r14
0,07 │ mov %r14,%r8
0,06 │ and $0xff,%r8d
0,09 │ mov (%rax,%r8,4),%eax
29,32 │ mov %r14,%r8
0,01 │ shr $0x8,%r8
0,02 │ and $0xff,%r8d
│ mov (%rcx,%r8,4),%ecx
10,83 │ mov %r14,%r8
0,00 │ shr $0x10,%r8
0,02 │ and $0xff,%r8d
0,01 │ mov (%rdx,%r8,4),%edx
8,89 │ shr $0x18,%r14
0,00 │ mov (%rdi,%r14,4),%edi
1,18 │ inc %rsi
0,00 │ xor %rdi,%rdx
13,49 │ xor %rdx,%rcx
6,75 │ xor %rcx,%rax
7,15 │ mov %rax,%r14
mov
instructions from register to register make up for more than 60%
of the time spent in the critical section of the code, while we would
expect most of the time to be spent xor
ing and and
ing. I have not
investigated why this is the case, ideas welcome!
Thanks to Peter Wortmann and to Arash Rouhani for the very informative discussions on the status of DWARF in GHC. Also thanks to Niklas Hambüchen for reviewing a draft of this blogpost.