The key tool to use in making your Haskell program run faster are GHC's profiling facilities, described separately in Chapter 6, 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 Data.List
, but it
will take you much longer than typing import
Data.List
.
Please report any overly-slow GHC-compiled programs. Since GHC doesn't have any credible competition in the performance department these days it's hard to say what overly-slow means, so just use your judgement! Of course, if a GHC compiled program runs slower than the same program compiled with NHC or Hugs, then it's definitely a bug.
-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
.
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
.
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 Section 8.12.8, “SPECIALIZE pragma” and Section 8.12.9, “SPECIALIZE instance pragma ”.
A low-tech way: grep (search) your interface
files for overloaded type signatures. You can view
interface files using the
--show-iface
option (see Section 5.6.7, “Other options related to interface files”).
% ghc --show-iface Foo.hi | egrep '^[a-z].*::.*=>'
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 8.12.5.1, “INLINE pragma”.
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,…
Putting a strictness annotation ('!') on a constructor field helps in two ways: it adds strictness to the program, which gives the strictness analyser more to work with, and it might help to reduce space leaks.
It can also help in a third way: when used with
-funbox-strict-fields
(see Section 5.9.2, “-f*
: platform-independent flags”), a strict field can be unpacked or
unboxed in the constructor, and one or more levels of
indirection may be removed. Unpacking only happens for
single-constructor datatypes (Int
is a
good candidate, for example).
Using -funbox-strict-fields
is only
really a good idea in conjunction with -O
,
because otherwise the extra packing and unpacking won't be
optimised away. In fact, it is possible that
-funbox-strict-fields
may worsen
performance even with
-O
, but this is unlikely (let us know if it
happens to you).
When you are really desperate for speed, and you want to get right down to the “raw bits.” Please see Section 8.2.1, “Unboxed types ” for some information about using unboxed types.
Before resorting to explicit unboxed types, try using
strict constructor fields and
-funbox-strict-fields
first (see above).
That way, your code stays portable.
foreign import
(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.
Chapter 9, Foreign function interface (FFI) describes the foreign function interface.
Float
s:If you're using Complex
, definitely
use Complex Double
rather than
Complex Float
(the former is specialised
heavily, but the latter isn't).
Floats
(probably 32-bits) are
almost always a bad idea, anyway, unless you Really Know
What You Are Doing. Use Double
s.
There's rarely a speed disadvantage—modern machines
will use the same floating-point unit for both. With
Double
s, 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.
UArray
)GHC supports arrays of unboxed elements, for several
basic arithmetic element types including
Int
and Char
: see the
Data.Array.Unboxed
library for details.
These arrays are likely to be much faster than using
standard Haskell 98 arrays from the
Data.Array
library.
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 5.14.3, “RTS options to control the garbage collector”).