Profilingprofilingcost-centre profiling Glasgow Haskell comes with a time and space profiling
system. Its purpose is to help you improve your understanding of
your program's execution behaviour, so you can improve it. Any comments, suggestions and/or improvements you have are
welcome. Recommended “profiling tricks” would be
especially cool! Profiling a program is a three-step process: Re-compile your program for profiling with the
-prof option, and probably one of the
-auto or -auto-all
options. These options are described in more detail in -prof-auto-auto-all Run your program with one of the profiling options, eg.
+RTS -p -RTS. This generates a file of
profiling information.RTS
option Examine the generated profiling information, using one of
GHC's profiling tools. The tool to use will depend on the kind
of profiling information generated.Cost centres and cost-centre stacksGHC's profiling system assigns costs
to cost centres. A cost is simply the time
or space required to evaluate an expression. Cost centres are
program annotations around expressions; all costs incurred by the
annotated expression are assigned to the enclosing cost centre.
Furthermore, GHC will remember the stack of enclosing cost centres
for any given expression at run-time and generate a call-graph of
cost attributions.Let's take a look at an example:
main = print (nfib 25)
nfib n = if n < 2 then 1 else nfib (n-1) + nfib (n-2)
Compile and run this program as follows:
$ ghc -prof -auto-all -o Main Main.hs
$ ./Main +RTS -p
121393
$
When a GHC-compiled program is run with the
RTS option, it generates a file called
<prog>.prof. In this case, the file
will contain something like this:
Fri May 12 14:06 2000 Time and Allocation Profiling Report (Final)
Main +RTS -p -RTS
total time = 0.14 secs (7 ticks @ 20 ms)
total alloc = 8,741,204 bytes (excludes profiling overheads)
COST CENTRE MODULE %time %alloc
nfib Main 100.0 100.0
individual inherited
COST CENTRE MODULE entries %time %alloc %time %alloc
MAIN MAIN 0 0.0 0.0 100.0 100.0
main Main 0 0.0 0.0 0.0 0.0
CAF PrelHandle 3 0.0 0.0 0.0 0.0
CAF PrelAddr 1 0.0 0.0 0.0 0.0
CAF Main 6 0.0 0.0 100.0 100.0
main Main 1 0.0 0.0 100.0 100.0
nfib Main 242785 100.0 100.0 100.0 100.0
The first part of the file gives the program name and
options, and the total time and total memory allocation measured
during the run of the program (note that the total memory
allocation figure isn't the same as the amount of
live memory needed by the program at any one
time; the latter can be determined using heap profiling, which we
will describe shortly).The second part of the file is a break-down by cost centre
of the most costly functions in the program. In this case, there
was only one significant function in the program, namely
nfib, and it was responsible for 100%
of both the time and allocation costs of the program.The third and final section of the file gives a profile
break-down by cost-centre stack. This is roughly a call-graph
profile of the program. In the example above, it is clear that
the costly call to nfib came from
main.The time and allocation incurred by a given part of the
program is displayed in two ways: “individual”, which
are the costs incurred by the code covered by this cost centre
stack alone, and “inherited”, which includes the costs
incurred by all the children of this node.The usefulness of cost-centre stacks is better demonstrated
by modifying the example slightly:
main = print (f 25 + g 25)
f n = nfib n
g n = nfib (n `div` 2)
nfib n = if n < 2 then 1 else nfib (n-1) + nfib (n-2)
Compile and run this program as before, and take a look at
the new profiling results:
COST CENTRE MODULE scc %time %alloc %time %alloc
MAIN MAIN 0 0.0 0.0 100.0 100.0
main Main 0 0.0 0.0 0.0 0.0
CAF PrelHandle 3 0.0 0.0 0.0 0.0
CAF PrelAddr 1 0.0 0.0 0.0 0.0
CAF Main 9 0.0 0.0 100.0 100.0
main Main 1 0.0 0.0 100.0 100.0
g Main 1 0.0 0.0 0.0 0.2
nfib Main 465 0.0 0.2 0.0 0.2
f Main 1 0.0 0.0 100.0 99.8
nfib Main 242785 100.0 99.8 100.0 99.8
Now although we had two calls to nfib
in the program, it is immediately clear that it was the call from
f which took all the time.The actual meaning of the various columns in the output is:entriesThe number of times this particular point in the call
graph was entered.individual %timeThe percentage of the total run time of the program
spent at this point in the call graph.individual %allocThe percentage of the total memory allocations
(excluding profiling overheads) of the program made by this
call.inherited %timeThe percentage of the total run time of the program
spent below this point in the call graph.inherited %allocThe percentage of the total memory allocations
(excluding profiling overheads) of the program made by this
call and all of its sub-calls.In addition you can use the RTS option
to
get the following additional information:ticksThe raw number of time “ticks” which were
attributed to this cost-centre; from this, we get the
%time figure mentioned
above.bytesNumber of bytes allocated in the heap while in this
cost-centre; again, this is the raw number from which we get
the %alloc figure mentioned
above.What about recursive functions, and mutually recursive
groups of functions? Where are the costs attributed? Well,
although GHC does keep information about which groups of functions
called each other recursively, this information isn't displayed in
the basic time and allocation profile, instead the call-graph is
flattened into a tree. The XML profiling tool (described in ) will be able to display real loops in
the call-graph.Inserting cost centres by handCost centres are just program annotations. When you say
to the compiler, it automatically
inserts a cost centre annotation around every top-level function
in your program, but you are entirely free to add the cost
centre annotations yourself.The syntax of a cost centre annotation is
{-# SCC "name" #-} <expression>
where "name" is an aribrary string,
that will become the name of your cost centre as it appears
in the profiling output, and
<expression> is any Haskell
expression. An SCC annotation extends as
far to the right as possible when parsing.Rules for attributing costsThe cost of evaluating any expression in your program is
attributed to a cost-centre stack using the following rules:If the expression is part of the
one-off costs of evaluating the
enclosing top-level definition, then costs are attributed to
the stack of lexically enclosing SCC
annotations on top of the special CAF
cost-centre. Otherwise, costs are attributed to the stack of
lexically-enclosing SCC annotations,
appended to the cost-centre stack in effect at the
call site of the current top-level
definitionThe call-site is just the place
in the source code which mentions the particular function or
variable.. Notice that this is a recursive
definition.Time spent in foreign code (see )
is always attributed to the cost centre in force at the
Haskell call-site of the foreign function.What do we mean by one-off costs? Well, Haskell is a lazy
language, and certain expressions are only ever evaluated once.
For example, if we write:
x = nfib 25
then x will only be evaluated once (if
at all), and subsequent demands for x will
immediately get to see the cached result. The definition
x is called a CAF (Constant Applicative
Form), because it has no arguments.For the purposes of profiling, we say that the expression
nfib 25 belongs to the one-off costs of
evaluating x.Since one-off costs aren't strictly speaking part of the
call-graph of the program, they are attributed to a special
top-level cost centre, CAF. There may be one
CAF cost centre for each module (the
default), or one for each top-level definition with any one-off
costs (this behaviour can be selected by giving GHC the
flag).-caf-allIf you think you have a weird profile, or the call-graph
doesn't look like you expect it to, feel free to send it (and
your program) to us at
glasgow-haskell-bugs@haskell.org.Compiler options for profilingprofilingoptionsoptionsfor profiling: To make use of the profiling system
all modules must be compiled and linked
with the option. Any
SCC annotations you've put in your source
will spring to life. Without a option, your
SCCs are ignored; so you can compile
SCC-laden code without changing
it.There are a few other profiling-related compilation options.
Use them in addition to
. These do not have to be used consistently
for all modules in a program.:cost centresautomatically inserting GHC will automatically add
_scc_ constructs for all
top-level, exported functions.:All top-level functions,
exported or not, will be automatically
_scc_'d.: The costs of all CAFs in a module are usually
attributed to one “big” CAF cost-centre. With
this option, all CAFs get their own cost-centre. An
“if all else fails” option…:Ignore any _scc_
constructs, so a module which already has
_scc_s can be compiled
for profiling with the annotations ignored.Time and allocation profilingTo generate a time and allocation profile, give one of the
following RTS options to the compiled program when you run it (RTS
options should be enclosed between +RTS...-RTS
as usual): or :time profileThe option produces a standard
time profile report. It is written
into the file
program.prof.The option produces a more
detailed report containing the actual time and allocation
data as well. (Not used much.):The option generates profiling
information in the XML format understood by our new
profiling tool, see .RTS
optionThis option makes use of the extra information
maintained by the cost-centre-stack profiler to provide
useful information about the location of runtime errors.
See .Profiling memory usageIn addition to profiling the time and allocation behaviour
of your program, you can also generate a graph of its memory usage
over time. This is useful for detecting the causes of
space leaks, when your program holds on to
more memory at run-time that it needs to. Space leaks lead to
longer run-times due to heavy garbage collector ativity, and may
even cause the program to run out of memory altogether.To generate a heap profile from your program:Compile the program for profiling ().Run it with one of the heap profiling options described
below (eg. for a basic producer profile).
This generates the file
prog.hp.Run hp2ps to produce a Postscript
file,
prog.ps. The
hp2ps utility is described in detail in
.Display the heap profile using a postscript viewer such
as Ghostview, or print it out on a
Postscript-capable printer.RTS options for heap profilingThere are several different kinds of heap profile that can
be generated. All the different profile types yield a graph of
live heap against time, but they differ in how the live heap is
broken down into bands. The following RTS options select which
break-down to use:RTS
optionBreaks down the graph by the cost-centre stack which
produced the data.RTS
optionBreak down the live heap by the module containing
the code which produced the data.RTS
optionBreaks down the graph by closure
description. For actual data, the description
is just the constructor name, for other closures it is a
compiler-generated string identifying the closure.RTS
optionBreaks down the graph by
type. For closures which have
function type or unknown/polymorphic type, the string will
represent an approximation to the actual type.RTS
optionBreak down the graph by retainer
set. Retainer profiling is described in more
detail below ().RTS
optionBreak down the graph by
biography. Biographical profiling
is described in more detail below ().In addition, the profile can be restricted to heap data
which satisfies certain criteria - for example, you might want
to display a profile by type but only for data produced by a
certain module, or a profile by retainer for a certain type of
data. Restrictions are specified as follows:name,...RTS
optionRestrict the profile to closures produced by
cost-centre stacks with one of the specified cost centres
at the top.name,...RTS
optionRestrict the profile to closures produced by
cost-centre stacks with one of the specified cost centres
anywhere in the stack.module,...RTS
optionRestrict the profile to closures produced by the
specified modules.desc,...RTS
optionRestrict the profile to closures with the specified
description strings.type,...RTS
optionRestrict the profile to closures with the specified
types.cc,...RTS
optionRestrict the profile to closures with retainer sets
containing cost-centre stacks with one of the specified
cost centres at the top.bio,...RTS
optionRestrict the profile to closures with one of the
specified biographies, where
bio is one of
lag, drag,
void, or use.For example, the following options will generate a
retainer profile restricted to Branch and
Leaf constructors:prog +RTS -hr -hdBranch,Leaf
There can only be one "break-down" option
(eg. in the example above), but there is no
limit on the number of further restrictions that may be applied.
All the options may be combined, with one exception: GHC doesn't
currently support mixing the and
options.There are two more options which relate to heap
profiling::Set the profiling (sampling) interval to
secs seconds (the default is
0.1 second). Fractions are allowed: for example
will get 5 samples per second.
This only affects heap profiling; time profiles are always
sampled on a 1/50 second frequency.RTS optionInclude the memory occupied by threads in a heap
profile. Each thread takes up a small area for its thread
state in addition to the space allocated for its stack
(stacks normally start small and then grow as
necessary).This includes the main thread, so using
is a good way to see how much stack
space the program is using.Memory occupied by threads and their stacks is
labelled as “TSO” when displaying the profile
by closure description or type description.Retainer ProfilingRetainer profiling is designed to help answer questions
like why is this data being retained?. We start
by defining what we mean by a retainer:
A retainer is either the system stack, or an unevaluated
closure (thunk).
In particular, constructors are not
retainers.An object A is retained by an object B if object A can be
reached by recursively following pointers starting from object
B but not meeting any other retainers on the way. Each object
has one or more retainers, collectively called its
retainer set.When retainer profiling is requested by giving the program
the option, a graph is generated which is
broken down by retainer set. A retainer set is displayed as a
set of cost-centre stacks; because this is usually too large to
fit on the profile graph, each retainer set is numbered and
shown abbreviated on the graph along with its number, and the
full list of retainer sets is dumped into the file
prog.prof.Retainer profiling requires multiple passes over the live
heap in order to discover the full retainer set for each
object, which can be quite slow. So we set a limit on the
maximum size of a retainer set, where all retainer sets larger
than the maximum retainer set size are replaced by the special
set MANY. The maximum set size defaults to 8
and can be altered with the RTS
option:sizeRestrict the number of elements in a retainer set to
size (default 8).Hints for using retainer profilingThe definition of retainers is designed to reflect a
common cause of space leaks: a large structure is retained by
an unevaluated computation, and will be released once the
compuation is forced. A good example is looking up a value in
a finite map, where unless the lookup is forced in a timely
manner the unevaluated lookup will cause the whole mapping to
be retained. These kind of space leaks can often be
eliminated by forcing the relevant computations to be
performed eagerly, using seq or strictness
annotations on data constructor fields.Often a particular data structure is being retained by a
chain of unevaluated closures, only the nearest of which will
be reported by retainer profiling - for example A retains B, B
retains C, and C retains a large structure. There might be a
large number of Bs but only a single A, so A is really the one
we're interested in eliminating. However, retainer profiling
will in this case report B as the retainer of the large
structure. To move further up the chain of retainers, we can
ask for another retainer profile but this time restrict the
profile to B objects, so we get a profile of the retainers of
B:prog +RTS -hr -hcB
This trick isn't foolproof, because there might be other
B closures in the heap which aren't the retainers we are
interested in, but we've found this to be a useful technique
in most cases.Biographical ProfilingA typical heap object may be in one of the following four
states at each point in its lifetime:The lag stage, which is the
time between creation and the first use of the
object,the use stage, which lasts from
the first use until the last use of the object, andThe drag stage, which lasts
from the final use until the last reference to the object
is dropped.An object which is never used is said to be in the
void state for its whole
lifetime.A biographical heap profile displays the portion of the
live heap in each of the four states listed above. Usually the
most interesting states are the void and drag states: live heap
in these states is more likely to be wasted space than heap in
the lag or use states.It is also possible to break down the heap in one or more
of these states by a different criteria, by restricting a
profile by biography. For example, to show the portion of the
heap in the drag or void state by producer: prog +RTS -hc -hbdrag,void
Once you know the producer or the type of the heap in the
drag or void states, the next step is usually to find the
retainer(s):prog +RTS -hr -hccc...
NOTE: this two stage process is required because GHC
cannot currently profile using both biographical and retainer
information simultaneously.Graphical time/allocation profileYou can view the time and allocation profiling graph of your
program graphically, using ghcprof. This is a
new tool with GHC 4.08, and will eventually be the de-facto
standard way of viewing GHC profilesActually this
isn't true any more, we are working on a new tool for
displaying heap profiles using Gtk+HS, so
ghcprof may go away at some point in the future.To run ghcprof, you need
daVinci installed, which can be
obtained from The Graph
Visualisation Tool daVinci. Install one of
the binary
distributionsdaVinci is
sadly not open-source :-(., and set your
DAVINCIHOME environment variable to point to the
installation directory.ghcprof uses an XML-based profiling log
format, and you therefore need to run your program with a
different option: . The file generated is
still called <prog>.prof. To see the
profile, run ghcprof like this:
$ ghcprof <prog>.prof
which should pop up a window showing the call-graph of your
program in glorious detail. More information on using
ghcprof can be found at The
Cost-Centre Stack Profiling Tool for
GHC.<command>hp2ps</command>––heap profile to PostScripthp2psheap profilespostscript, from heap profilesUsage:
hp2ps [flags] [<file>[.hp]]
The program
hp2pshp2ps
program converts a heap profile as produced
by the runtime option into a
PostScript graph of the heap profile. By convention, the file to
be processed by hp2ps has a
.hp extension. The PostScript output is
written to <file>@.ps. If
<file> is omitted entirely, then the
program behaves as a filter.hp2ps is distributed in
ghc/utils/hp2ps in a GHC source
distribution. It was originally developed by Dave Wakeling as part
of the HBC/LML heap profiler.The flags are:In order to make graphs more readable,
hp2ps sorts the shaded bands for each
identifier. The default sort ordering is for the bands with
the largest area to be stacked on top of the smaller ones.
The option causes rougher bands (those
representing series of values with the largest standard
deviations) to be stacked on top of smoother ones.Normally, hp2ps puts the title of
the graph in a small box at the top of the page. However, if
the JOB string is too long to fit in a small box (more than
35 characters), then hp2ps will choose to
use a big box instead. The option
forces hp2ps to use a big box.Generate encapsulated PostScript suitable for
inclusion in LaTeX documents. Usually, the PostScript graph
is drawn in landscape mode in an area 9 inches wide by 6
inches high, and hp2ps arranges for this
area to be approximately centred on a sheet of a4 paper.
This format is convenient of studying the graph in detail,
but it is unsuitable for inclusion in LaTeX documents. The
option causes the graph to be drawn in
portrait mode, with float specifying the width in inches,
millimetres or points (the default). The resulting
PostScript file conforms to the Encapsulated PostScript
(EPS) convention, and it can be included in a LaTeX document
using Rokicki's dvi-to-PostScript converter
dvips.Create output suitable for the gs
PostScript previewer (or similar). In this case the graph is
printed in portrait mode without scaling. The output is
unsuitable for a laser printer.Normally a profile is limited to 20 bands with
additional identifiers being grouped into an
OTHER band. The flag
removes this 20 band and limit, producing as many bands as
necessary. No key is produced as it won't fit!. It is useful
for creation time profiles with many bands.Normally a profile is limited to 20 bands with
additional identifiers being grouped into an
OTHER band. The flag
specifies an alternative band limit (the maximum is
20). requests the band limit to be
removed. As many bands as necessary are produced. However no
key is produced as it won't fit! It is useful for displaying
creation time profiles with many bands.Use previous parameters. By default, the PostScript
graph is automatically scaled both horizontally and
vertically so that it fills the page. However, when
preparing a series of graphs for use in a presentation, it
is often useful to draw a new graph using the same scale,
shading and ordering as a previous one. The
flag causes the graph to be drawn using
the parameters determined by a previous run of
hp2ps on file. These
are extracted from file@.aux.Use a small box for the title.Normally trace elements which sum to a total of less
than 1% of the profile are removed from the
profile. The option allows this
percentage to be modified (maximum 5%). requests no trace elements to be
removed from the profile, ensuring that all the data will be
displayed.Generate colour output.Ignore marks.Print out usage information.Manipulating the hp file(Notes kindly offered by Jan-Willhem Maessen.)
The FOO.hp file produced when you ask for the
heap profile of a program FOO is a text file with a particularly
simple structure. Here's a representative example, with much of the
actual data omitted:
JOB "FOO -hC"
DATE "Thu Dec 26 18:17 2002"
SAMPLE_UNIT "seconds"
VALUE_UNIT "bytes"
BEGIN_SAMPLE 0.00
END_SAMPLE 0.00
BEGIN_SAMPLE 15.07
... sample data ...
END_SAMPLE 15.07
BEGIN_SAMPLE 30.23
... sample data ...
END_SAMPLE 30.23
... etc.
BEGIN_SAMPLE 11695.47
END_SAMPLE 11695.47
The first four lines (JOB, DATE, SAMPLE_UNIT, VALUE_UNIT) form a
header. Each block of lines starting with BEGIN_SAMPLE and ending
with END_SAMPLE forms a single sample (you can think of this as a
vertical slice of your heap profile). The hp2ps utility should accept
any input with a properly-formatted header followed by a series of
*complete* samples.
Zooming in on regions of your profile
You can look at particular regions of your profile simply by loading a
copy of the .hp file into a text editor and deleting the unwanted
samples. The resulting .hp file can be run through hp2ps and viewed
or printed.
Viewing the heap profile of a running program
The .hp file is generated incrementally as your
program runs. In principle, running hp2ps on the incomplete file
should produce a snapshot of your program's heap usage. However, the
last sample in the file may be incomplete, causing hp2ps to fail. If
you are using a machine with UNIX utilities installed, it's not too
hard to work around this problem (though the resulting command line
looks rather Byzantine):
head -`fgrep -n END_SAMPLE FOO.hp | tail -1 | cut -d : -f 1` FOO.hp \
| hp2ps > FOO.ps
The command fgrep -n END_SAMPLE FOO.hp finds the
end of every complete sample in FOO.hp, and labels each sample with
its ending line number. We then select the line number of the last
complete sample using tail and cut. This is used as a
parameter to head; the result is as if we deleted the final
incomplete sample from FOO.hp. This results in a properly-formatted
.hp file which we feed directly to hp2ps.
Viewing a heap profile in real time
The gv and ghostview programs
have a "watch file" option can be used to view an up-to-date heap
profile of your program as it runs. Simply generate an incremental
heap profile as described in the previous section. Run gv on your
profile:
gv -watch -seascape FOO.ps
If you forget the -watch flag you can still select
"Watch file" from the "State" menu. Now each time you generate a new
profile FOO.ps the view will update automatically.
This can all be encapsulated in a little script:
#!/bin/sh
head -`fgrep -n END_SAMPLE FOO.hp | tail -1 | cut -d : -f 1` FOO.hp \
| hp2ps > FOO.ps
gv -watch -seascape FOO.ps &
while [ 1 ] ; do
sleep 10 # We generate a new profile every 10 seconds.
head -`fgrep -n END_SAMPLE FOO.hp | tail -1 | cut -d : -f 1` FOO.hp \
| hp2ps > FOO.ps
done
Occasionally gv will choke as it tries to read an incomplete copy of
FOO.ps (because hp2ps is still running as an update
occurs). A slightly more complicated script works around this
problem, by using the fact that sending a SIGHUP to gv will cause it
to re-read its input file:
#!/bin/sh
head -`fgrep -n END_SAMPLE FOO.hp | tail -1 | cut -d : -f 1` FOO.hp \
| hp2ps > FOO.ps
gv FOO.ps &
gvpsnum=$!
while [ 1 ] ; do
sleep 10
head -`fgrep -n END_SAMPLE FOO.hp | tail -1 | cut -d : -f 1` FOO.hp \
| hp2ps > FOO.ps
kill -HUP $gvpsnum
done
Using “ticky-ticky” profiling (for implementors)ticky-ticky profiling(ToDo: document properly.)It is possible to compile Glasgow Haskell programs so that
they will count lots and lots of interesting things, e.g., number
of updates, number of data constructors entered, etc., etc. We
call this “ticky-ticky”
profiling,ticky-ticky
profilingprofiling,
ticky-ticky because that's the sound a Sun4
makes when it is running up all those counters
(slowly).Ticky-ticky profiling is mainly intended for implementors;
it is quite separate from the main “cost-centre”
profiling system, intended for all users everywhere.To be able to use ticky-ticky profiling, you will need to
have built appropriate libraries and things when you made the
system. See “Customising what libraries to build,” in
the installation guide.To get your compiled program to spit out the ticky-ticky
numbers, use a RTS
option-r RTS option.
See .Compiling your program with the
switch yields an executable that performs these counts. Here is a
sample ticky-ticky statistics file, generated by the invocation
foo +RTS -rfoo.ticky.
foo +RTS -rfoo.ticky
ALLOCATIONS: 3964631 (11330900 words total: 3999476 admin, 6098829 goods, 1232595 slop)
total words: 2 3 4 5 6+
69647 ( 1.8%) function values 50.0 50.0 0.0 0.0 0.0
2382937 ( 60.1%) thunks 0.0 83.9 16.1 0.0 0.0
1477218 ( 37.3%) data values 66.8 33.2 0.0 0.0 0.0
0 ( 0.0%) big tuples
2 ( 0.0%) black holes 0.0 100.0 0.0 0.0 0.0
0 ( 0.0%) prim things
34825 ( 0.9%) partial applications 0.0 0.0 0.0 100.0 0.0
2 ( 0.0%) thread state objects 0.0 0.0 0.0 0.0 100.0
Total storage-manager allocations: 3647137 (11882004 words)
[551104 words lost to speculative heap-checks]
STACK USAGE:
ENTERS: 9400092 of which 2005772 (21.3%) direct to the entry code
[the rest indirected via Node's info ptr]
1860318 ( 19.8%) thunks
3733184 ( 39.7%) data values
3149544 ( 33.5%) function values
[of which 1999880 (63.5%) bypassed arg-satisfaction chk]
348140 ( 3.7%) partial applications
308906 ( 3.3%) normal indirections
0 ( 0.0%) permanent indirections
RETURNS: 5870443
2137257 ( 36.4%) from entering a new constructor
[the rest from entering an existing constructor]
2349219 ( 40.0%) vectored [the rest unvectored]
RET_NEW: 2137257: 32.5% 46.2% 21.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
RET_OLD: 3733184: 2.8% 67.9% 29.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
RET_UNBOXED_TUP: 2: 0.0% 0.0%100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
RET_VEC_RETURN : 2349219: 0.0% 0.0%100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
UPDATE FRAMES: 2241725 (0 omitted from thunks)
SEQ FRAMES: 1
CATCH FRAMES: 1
UPDATES: 2241725
0 ( 0.0%) data values
34827 ( 1.6%) partial applications
[2 in place, 34825 allocated new space]
2206898 ( 98.4%) updates to existing heap objects (46 by squeezing)
UPD_CON_IN_NEW: 0: 0 0 0 0 0 0 0 0 0
UPD_PAP_IN_NEW: 34825: 0 0 0 34825 0 0 0 0 0
NEW GEN UPDATES: 2274700 ( 99.9%)
OLD GEN UPDATES: 1852 ( 0.1%)
Total bytes copied during GC: 190096
**************************************************
3647137 ALLOC_HEAP_ctr
11882004 ALLOC_HEAP_tot
69647 ALLOC_FUN_ctr
69647 ALLOC_FUN_adm
69644 ALLOC_FUN_gds
34819 ALLOC_FUN_slp
34831 ALLOC_FUN_hst_0
34816 ALLOC_FUN_hst_1
0 ALLOC_FUN_hst_2
0 ALLOC_FUN_hst_3
0 ALLOC_FUN_hst_4
2382937 ALLOC_UP_THK_ctr
0 ALLOC_SE_THK_ctr
308906 ENT_IND_ctr
0 E!NT_PERM_IND_ctr requires +RTS -Z
[... lots more info omitted ...]
0 GC_SEL_ABANDONED_ctr
0 GC_SEL_MINOR_ctr
0 GC_SEL_MAJOR_ctr
0 GC_FAILED_PROMOTION_ctr
47524 GC_WORDS_COPIED_ctr
The formatting of the information above the row of asterisks
is subject to change, but hopefully provides a useful
human-readable summary. Below the asterisks all
counters maintained by the ticky-ticky system are
dumped, in a format intended to be machine-readable: zero or more
spaces, an integer, a space, the counter name, and a newline.In fact, not all counters are
necessarily dumped; compile- or run-time flags can render certain
counters invalid. In this case, either the counter will simply
not appear, or it will appear with a modified counter name,
possibly along with an explanation for the omission (notice
ENT_PERM_IND_ctr appears
with an inserted ! above). Software analysing
this output should always check that it has the counters it
expects. Also, beware: some of the counters can have
large values!