Please advise us of other ``helpful hints'' that should go here!
-O
or (especially) -O2
:By using them, you are telling GHC that you are willing to suffer longer compilation times for better-quality code.
GHC is surprisingly zippy for normal compilations without -O
!
Within reason, more memory for heap space means less garbage
collection for GHC, which means less compilation time. If you use
the -Rgc-stats
option, you'll get a garbage-collector report.
(Again, you can use the cheap-and-nasty -optCrts-Sstderr
option to
send the GC stats straight to standard error.)
If it says you're using more than 20% of total time in garbage collecting, then more memory would help.
If the heap size is approaching the maximum (64M by default), and you
have lots of memory, try increasing the maximum with the
-M<size>
option, e.g.: ghc -c -O
-M16m Foo.hs
.
Increasing the default allocation area size used by the compiler's RTS
might also help: use the -A<size>
option.
If GHC persists in being a bad memory citizen, please report it as a bug.
As soon as GHC plus its ``fellow citizens'' (other processes on your
machine) start using more than the real memory on your
machine, and the machine starts ``thrashing,'' the party is
over. Compile times will be worse than terrible! Use something
like the csh-builtin time
command to get a report on how many page
faults you're getting.
If you don't know what virtual memory, thrashing, and page faults are, or you don't know the memory configuration of your machine, don't try to be clever about memory use: you'll just make your life a misery (and for other people, too, probably).
Because Haskell objects and libraries tend to be large, it can take many real seconds to slurp the bits to/from a remote filesystem.
It would be quite sensible to compile on a fast machine using remotely-mounted disks; then link on a slow machine that had your disks directly mounted.
Read
unnecessarily:It's ugly and slow.
Deeply-nested list comprehensions seem to be one such; in the past, very large constant tables were bad, too.
We'd rather you reported such behaviour as a bug, so that we can try to correct it.
The parts of the compiler that seem most prone to wandering off for a
long time are the abstract interpreters (strictness and update
analysers). You can turn these off individually with
-fno-strictness
and
-fno-update-analysis
.
To figure out which part of the compiler is badly behaved, the
-dshow-passes
option is your
friend.
If your module has big wads of constant data, GHC may produce a huge
basic block that will cause the native-code generator's register
allocator to founder. Bring on -fvia-C
(not that GCC will be that quick about it, either).
Use -no-link-chk
; saves effort. This is
probably safe in a I-only-compile-things-one-way setup.
import
declarations:Instead of saying import Foo
, say import Foo (...stuff I want...)
.
Truthfully, the reduction on compilation time will be very small.
However, judicious use of import
declarations can make a
program easier to understand, so it may be a good idea anyway.
The key tool to use in making your Haskell program run faster are GHC's profiling facilities, described separately in Section Profiling. There is no substitute for finding where your program's time/space is really going, as opposed to where you imagine it is going.
Another point to bear in mind: By far the best way to improve a program's performance dramatically is to use better algorithms. Once profiling has thrown the spotlight on the guilty time-consumer(s), it may be better to re-think your program than to try all the tweaks listed below.
Another extremely efficient way to make your program snappy is to use
library code that has been Seriously Tuned By Someone Else. You
might be able to write a better quicksort than the one in the
HBC library, but it will take you much longer than typing import
QSort
. (Incidentally, it doesn't hurt if the Someone Else is Lennart
Augustsson.)
Please report any overly-slow GHC-compiled programs. The current definition of ``overly-slow'' is ``the HBC-compiled version ran faster''...
-O
or -O2
:This is the most basic way
to make your program go faster. Compilation time will be slower,
especially with -O2
.
At present, -O2
is nearly indistinguishable from -O
.
Even with -O
, GHC tries to
use a native-code generator, if available. But the native
code-generator is designed to be quick, not mind-bogglingly clever.
Better to let GCC have a go, as it tries much harder on register
allocation, etc.
So, when we want very fast code, we use: -O -fvia-C -O2-for-C
.
Haskell's overloading (using type classes) is elegant, neat, etc., etc., but it is death to performance if left to linger in an inner loop. How can you squash it?
Signatures are the basic trick; putting them on exported, top-level
functions is good software-engineering practice, anyway. (Tip: using
-fwarn-missing-signatures
can help enforce good signature-practice).
The automatic specialisation of overloaded functions (with -O
)
should take care of overloaded local and/or unexported functions.
SPECIALIZE
pragmas:
Specialize the overloading on key functions in your program. See Sections SPECIALIZE pragmas and SPECIALIZE instance pragmas
A low-tech way: grep (search) your interface files for overloaded type signatures; e.g.,:
% egrep '^[a-z].*::.*=>' *.hi
and, among other things, lazy pattern-matching is your enemy.
(If you don't know what a ``strict function'' is, please consult a functional-programming textbook. A sentence or two of explanation here probably would not do much good.)
Consider these two code fragments:
f (Wibble x y) = ... # strict
f arg = let { (Wibble x y) = arg } in ... # lazy
The former will result in far better code.
A less contrived example shows the use of cases
instead
of lets
to get stricter code (a good thing):
f (Wibble x y) # beautiful but slow
= let
(a1, b1, c1) = unpackFoo x
(a2, b2, c2) = unpackFoo y
in ...
f (Wibble x y) # ugly, and proud of it
= case (unpackFoo x) of { (a1, b1, c1) ->
case (unpackFoo y) of { (a2, b2, c2) ->
...
}}
It's all the better if a function is strict in a single-constructor type (a type with only one data-constructor; for example, tuples are single-constructor types).
If your datatype has a single constructor with a single field, use a
newtype
declaration instead of a data
declaration. The newtype
will be optimised away in most cases.
Don't guess---look it up.
Look for your function in the interface file, then for the third field
in the pragma; it should say _S_ <string>
. The <string>
gives the strictness of the function's arguments. L
is lazy
(bad), S
and E
are strict (good), P
is ``primitive'' (good),
U(...)
is strict and
``unpackable'' (very good), and A
is absent (very good).
For an ``unpackable'' U(...)
argument, the info inside
tells the strictness of its components. So, if the argument is a
pair, and it says U(AU(LSS))
, that means ``the first component of the
pair isn't used; the second component is itself unpackable, with three
components (lazy in the first, strict in the second \& third).''
If the function isn't exported, just compile with the extra flag -ddump-simpl
;
next to the signature for any binder, it will print the self-same
pragmatic information as would be put in an interface file.
(Besides, Core syntax is fun to look at!)
INLINE
d (esp. monads):Placing INLINE
pragmas on certain functions that are used a lot can
have a dramatic effect. See Section
INLINE pragmas.
export
list:If you do not have an explicit export list in a module, GHC must assume that everything in that module will be exported. This has various pessimising effects. For example, if a bit of code is actually unused (perhaps because of unfolding effects), GHC will not be able to throw it away, because it is exported and some other module may be relying on its existence.
GHC can be quite a bit more aggressive with pieces of code if it knows they are not exported.
(The form in which GHC manipulates your code.) Just run your
compilation with -ddump-simpl
(don't forget the -O
).
If profiling has pointed the finger at particular functions, look at
their Core code. lets
are bad, cases
are good, dictionaries
(d.<Class>.<Unique>
) [or anything overloading-ish] are bad,
nested lambdas are bad, explicit data constructors are good, primitive
operations (e.g., eqInt#
) are good, ...
When you are really desperate for speed, and you want to get right down to the ``raw bits.'' Please see Section Unboxed types for some information about using unboxed types.
_ccall_s
(a GHC extension) to plug into fast libraries:This may take real work, but... There exist piles of massively-tuned library code, and the best thing is not to compete with it, but link with it.
Section Calling~C directly from Haskell says a little about how to use C calls.
Float
s:We don't provide specialisations of Prelude functions for Float
(but we do for Double
). If you end up executing overloaded
code, you will lose on performance, perhaps badly.
Floats
(probably 32-bits) are almost always a bad idea, anyway,
unless you Really Know What You Are Doing. Use Doubles. There's
rarely a speed disadvantage---modern machines will use the same
floating-point unit for both. With Doubles
, you are much less
likely to hang yourself with numerical errors.
One time when Float
might be a good idea is if you have a
lot of them, say a giant array of Float
s. They take up
half the space in the heap compared to Doubles
. However, this isn't
true on a 64-bit machine.
If your program's GC stats (-S
RTS option)
indicate that it's doing lots of garbage-collection (say, more than
20% of execution time), more memory might help---with the
-M<size>
or
-A<size>
RTS options (see
Section
RTS options to control the garbage-collector).
Decrease the ``go-for-it'' threshold for unfolding smallish
expressions. Give a
-funfolding-use-threshold0
option for the extreme case. (``Only unfoldings with
zero cost should proceed.'') Warning: except in certain specialiised
cases (like Happy parsers) this is likely to actually
increase the size of your program, because unfolding
generally enables extra simplifying optimisations to be performed.
Avoid Read
.
Use strip
on your executables.
``I think I have a space leak...'' Re-run your program with
+RTS -Sstderr
,
and remove all doubt!
(You'll see the heap usage get bigger and bigger...) [Hmmm... this
might be even easier with the -F2s
RTS
option; so... ./a.out +RTS -Sstderr -F2s
...]
Once again, the profiling facilities (Section Profiling) are the basic tool for demystifying the space behaviour of your program.
Strict functions are good for space usage, as they are for time, as discussed in the previous section. Strict functions get right down to business, rather than filling up the heap with closures (the system's notes to itself about how to evaluate something, should it eventually be required).