Difference between revisions of "Performance/Strictness"
Beerdude26 (talk  contribs) m (→Explicit strictness: Added reference to Performance/Data_types) 
(Change <prehaskell> and <codehaskell> markup to <haskell> and <hask>, respectively. Thanks to Rory Green for pointing this out.) 

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== Strictness analysis == 
== Strictness analysis == 

−  Optimising compilers like GHC try to reduce the cost of laziness using ''strictness analysis'', which attempts to determine which function arguments are always evaluated by the function, and hence can be evaluated by the caller instead. Sometimes this leads to bigger gains; a strict < 
+  Optimising compilers like GHC try to reduce the cost of laziness using ''strictness analysis'', which attempts to determine which function arguments are always evaluated by the function, and hence can be evaluated by the caller instead. Sometimes this leads to bigger gains; a strict <hask>Int</hask> can be passed as an unboxed value, for example. Strictness analysis sometimes does wonderful things; for example it is very good at optimising <hask>fac</hask>: 
−  < 
+  <haskell> 
fac :: Int > Int 
fac :: Int > Int 

fac n = if n <= 1 then 1 else n * fac (n1) 
fac n = if n <= 1 then 1 else n * fac (n1) 

−  </ 
+  </haskell> 
−  Strictness analysis can spot the fact that the argument < 
+  Strictness analysis can spot the fact that the argument <hask>n</hask> is strict, and can be represented unboxed. The resulting function won't use any heap while it is running, as you'd expect. 
The common case of misunderstanding of strictness analysis is when [[Foldfolding]] (reducing) lists. If this program 
The common case of misunderstanding of strictness analysis is when [[Foldfolding]] (reducing) lists. If this program 

−  < 
+  <haskell> 
main = print (foldl (+) 0 [1..1000000]) 
main = print (foldl (+) 0 [1..1000000]) 

−  </ 
+  </haskell> 
−  is compiled in GHC without "O" flag, it uses a lot of heap and stack. A programmer knows that the long list (< 
+  is compiled in GHC without "O" flag, it uses a lot of heap and stack. A programmer knows that the long list (<hask>[1..1000000]</hask>) is stored as a thunk, not fully, because the programmer read about [[nonstrict semantics]] and [[lazy vs. nonstrict]]. The programmer explicitly wrote <hask>sum</hask> as [[Tail recursiontail recursive]], so the program should use a small amount of stack, because the programmer knows about [[stack overflow]]. So behavior of the program looks mysterious to the programmer. 
The programmer concludes that the program somehow decides to store the long list fully in the heap, or garbage collector is not able to remove dead prefix of the long list. Wrong. The long list is fine. 
The programmer concludes that the program somehow decides to store the long list fully in the heap, or garbage collector is not able to remove dead prefix of the long list. Wrong. The long list is fine. 

Look at the definition from the standard library. 
Look at the definition from the standard library. 

−  < 
+  <haskell> 
foldl :: (a > b > a) > a > [b] > a 
foldl :: (a > b > a) > a > [b] > a 

foldl f z0 xs0 = lgo z0 xs0 
foldl f z0 xs0 = lgo z0 xs0 

Line 30:  Line 30:  
lgo z [] = z 
lgo z [] = z 

lgo z (x:xs) = lgo (f z x) xs 
lgo z (x:xs) = lgo (f z x) xs 

−  </ 
+  </haskell> 
−  < 
+  <hask>lgo</hask>, instead of adding elements of the long list, creates '''a thunk''' for <hask>(f z x)</hask>. <hask>z</hask> is stored within that thunk, and <hask>z</hask> is a thunk also, created during the previous call to <hask>lgo</hask>. The program creates the long chain of thunks. Stack is bloated when evaluating that chain. 
−  With "O" flag GHC performs strictness analysis, 
+  With "O" flag GHC performs strictness analysis, then it knows that <hask>lgo</hask> is strict in <hask>z</hask> argument, therefore thunks are not needed and are not created. 
== Limitations of strictness analysis == 
== Limitations of strictness analysis == 

It's easy to accidentally write functions that aren't strict, though. Often a lazy function can be sitting around eating up your performance, when making it strict wouldn't change the meaning of the program. For example: 
It's easy to accidentally write functions that aren't strict, though. Often a lazy function can be sitting around eating up your performance, when making it strict wouldn't change the meaning of the program. For example: 

−  < 
+  <haskell> 
suminit :: [Int] > Int > Int > (Int,[Int]) 
suminit :: [Int] > Int > Int > (Int,[Int]) 

suminit xs len acc = case len == 0 of 
suminit xs len acc = case len == 0 of 

Line 47:  Line 47:  
x:xs > suminit xs (len1) (acc+x) 
x:xs > suminit xs (len1) (acc+x) 

main = print (fst (suminit [1..] 1000000 0)) 
main = print (fst (suminit [1..] 1000000 0)) 

−  </ 
+  </haskell> 
−  this function sums the first len elements of a list, returning the sum and the remaining list. We've already tried to improve performance by using an [[Performance/Accumulating parameteraccumulating parameter]]. However, the parameter < 
+  this function sums the first len elements of a list, returning the sum and the remaining list. We've already tried to improve performance by using an [[Performance/Accumulating parameteraccumulating parameter]]. However, the parameter <hask>acc</hask> isn't strict, because there's no guarantee that the caller will evaluate it. The compiler will use a fully boxed <hask>Int</hask> to represent <hask>acc</hask>, although it will probably use an unboxed <hask>Int</hask> to represent <hask>len</hask>. The expression <hask>(acc+x)</hask> will be saved as a suspension, rather than evaluated on the spot. (Incidentally, this is a common pattern we see crop up time and again in small recursive functions with a few parameters). 
== Explicit strictness == 
== Explicit strictness == 

Line 54:  Line 54:  
We can make an argument strict explicitly. 
We can make an argument strict explicitly. 

−  In the < 
+  In the <hask>foldl</hask> example, replace <hask>foldl</hask> with <hask>foldl'</hask>. 
−  For < 
+  For <hask>suminit</hask>, we need to make <hask>acc</hask> strict. The way to do this is using <hask>seq</hask>: 
−  < 
+  <haskell> 
suminit :: [Int] > Int > Int > (Int,[Int]) 
suminit :: [Int] > Int > Int > (Int,[Int]) 

suminit xs len acc = acc `seq` case len == 0 of 
suminit xs len acc = acc `seq` case len == 0 of 

Line 64:  Line 64:  
[] > (acc,[]) 
[] > (acc,[]) 

x:xs > suminit xs (len1) (acc+x) 
x:xs > suminit xs (len1) (acc+x) 

−  </ 
+  </haskell> 
Some other languages (eg. Clean) have strictness annotations on types, which is a less ugly way to express this, but for now there are no Haskell compilers that support this. 
Some other languages (eg. Clean) have strictness annotations on types, which is a less ugly way to express this, but for now there are no Haskell compilers that support this. 

Line 72:  Line 72:  
{{NoteFor strict data structures, see [[Performance/Data_types]].}} 
{{NoteFor strict data structures, see [[Performance/Data_types]].}} 

−  < 
+  <haskell> 
suminit xs !len !acc = … 
suminit xs !len !acc = … 

−  </ 
+  </haskell> 
Incidentally, GHC will also eliminate the tuple returned by this function if the caller immediately deconstructs it. 
Incidentally, GHC will also eliminate the tuple returned by this function if the caller immediately deconstructs it. 

Line 80:  Line 80:  
== Evaluating expressions strictly == 
== Evaluating expressions strictly == 

−  There's a useful variant of the infix application operator < 
+  There's a useful variant of the infix application operator <hask>($)</hask> that evaluates its argument strictly: <hask>($!)</hask>. This can often be used to great effect in eliminating unnecessary suspensions that the compiler hasn't spotted. eg. in a function application 
−  < 
+  <haskell> 
f (g x) 
f (g x) 

−  </ 
+  </haskell> 
writing instead 
writing instead 

−  < 
+  <haskell> 
f $! (g x) 
f $! (g x) 

−  </ 
+  </haskell> 
−  will be more efficient if (a) you were going to evaluate < 
+  will be more efficient if (a) you were going to evaluate <hask>(g x)</hask> anyway, and (b) <hask>f</hask> isn't visibly strict, or inlined. If <hask>f</hask> is strict or inlined, then the chances are that <hask>($!)</hask> is unnecessary cruft here. 
A good example is the monadic return. If you find yourself writing 
A good example is the monadic return. If you find yourself writing 

−  < 
+  <haskell> 
do … 
do … 

… 
… 

return (fn x) 
return (fn x) 

−  </ 
+  </haskell> 
then consider instead writing 
then consider instead writing 

−  < 
+  <haskell> 
do … 
do … 

… 
… 

return $! fn x 
return $! fn x 

−  </ 
+  </haskell> 
it is very rare to actually need laziness in the argument of return here. 
it is very rare to actually need laziness in the argument of return here. 

Line 111:  Line 111:  
A rule of thumb for when strictness annotation might be needed: 
A rule of thumb for when strictness annotation might be needed: 

−  When a function < 
+  When a function <hask>f</hask> with argument <hask>x</hask> satisfies both conditions: 
−  * < 
+  * <hask>f</hask> calls a function on a function of <hask>x</hask>: <hask>(h (g x))</hask> 
−  * is not already strict in < 
+  * is not already strict in <hask>x</hask> (does not inspect <hask>x</hask>'s value), 
then it can be helpful to force evaluation: 
then it can be helpful to force evaluation: 

Example: 
Example: 

−  < 
+  <haskell> 
 Force Strict: Make g's argument smaller. 
 Force Strict: Make g's argument smaller. 

f x = g $! (h x) 
f x = g $! (h x) 

Line 127:  Line 127:  
f x = case x of 
f x = case x of 

0 > (h (g x)) 
0 > (h (g x)) 

−  </ 
+  </haskell> 
Latest revision as of 16:59, 23 March 2019
Haskell Performance Resource
Constructs: Techniques: 
Haskell is a nonstrict language, and most implementations use a strategy called laziness to run your program. Basically laziness == nonstrictness + sharing.
Laziness can be a useful tool for improving performance, but more often than not it reduces performance by adding a constant overhead to everything. Because of laziness, the compiler can't evaluate a function argument and pass the value to the function, it has to record the expression in the heap in a suspension (or thunk) in case it is evaluated later. Storing and evaluating suspensions is costly, and unnecessary if the expression was going to be evaluated anyway.
Contents
Strictness analysis
Optimising compilers like GHC try to reduce the cost of laziness using strictness analysis, which attempts to determine which function arguments are always evaluated by the function, and hence can be evaluated by the caller instead. Sometimes this leads to bigger gains; a strict Int
can be passed as an unboxed value, for example. Strictness analysis sometimes does wonderful things; for example it is very good at optimising fac
:
fac :: Int > Int
fac n = if n <= 1 then 1 else n * fac (n1)
Strictness analysis can spot the fact that the argument n
is strict, and can be represented unboxed. The resulting function won't use any heap while it is running, as you'd expect.
The common case of misunderstanding of strictness analysis is when folding (reducing) lists. If this program
main = print (foldl (+) 0 [1..1000000])
is compiled in GHC without "O" flag, it uses a lot of heap and stack. A programmer knows that the long list ([1..1000000]
) is stored as a thunk, not fully, because the programmer read about nonstrict semantics and lazy vs. nonstrict. The programmer explicitly wrote sum
as tail recursive, so the program should use a small amount of stack, because the programmer knows about stack overflow. So behavior of the program looks mysterious to the programmer.
The programmer concludes that the program somehow decides to store the long list fully in the heap, or garbage collector is not able to remove dead prefix of the long list. Wrong. The long list is fine.
Look at the definition from the standard library.
foldl :: (a > b > a) > a > [b] > a
foldl f z0 xs0 = lgo z0 xs0
where
lgo z [] = z
lgo z (x:xs) = lgo (f z x) xs
lgo
, instead of adding elements of the long list, creates a thunk for (f z x)
. z
is stored within that thunk, and z
is a thunk also, created during the previous call to lgo
. The program creates the long chain of thunks. Stack is bloated when evaluating that chain.
With "O" flag GHC performs strictness analysis, then it knows that lgo
is strict in z
argument, therefore thunks are not needed and are not created.
Limitations of strictness analysis
It's easy to accidentally write functions that aren't strict, though. Often a lazy function can be sitting around eating up your performance, when making it strict wouldn't change the meaning of the program. For example:
suminit :: [Int] > Int > Int > (Int,[Int])
suminit xs len acc = case len == 0 of
True > (acc,xs)
False > case xs of
[] > (acc,[])
x:xs > suminit xs (len1) (acc+x)
main = print (fst (suminit [1..] 1000000 0))
this function sums the first len elements of a list, returning the sum and the remaining list. We've already tried to improve performance by using an accumulating parameter. However, the parameter acc
isn't strict, because there's no guarantee that the caller will evaluate it. The compiler will use a fully boxed Int
to represent acc
, although it will probably use an unboxed Int
to represent len
. The expression (acc+x)
will be saved as a suspension, rather than evaluated on the spot. (Incidentally, this is a common pattern we see crop up time and again in small recursive functions with a few parameters).
Explicit strictness
We can make an argument strict explicitly.
In the foldl
example, replace foldl
with foldl'
.
For suminit
, we need to make acc
strict. The way to do this is using seq
:
suminit :: [Int] > Int > Int > (Int,[Int])
suminit xs len acc = acc `seq` case len == 0 of
True > (acc,xs)
False > case xs of
[] > (acc,[])
x:xs > suminit xs (len1) (acc+x)
Some other languages (eg. Clean) have strictness annotations on types, which is a less ugly way to express this, but for now there are no Haskell compilers that support this.
With the BangPatterns GHC extension enabled, the above can be written as
∗ For strict data structures, see Performance/Data_types.
suminit xs !len !acc = …
Incidentally, GHC will also eliminate the tuple returned by this function if the caller immediately deconstructs it.
Evaluating expressions strictly
There's a useful variant of the infix application operator ($)
that evaluates its argument strictly: ($!)
. This can often be used to great effect in eliminating unnecessary suspensions that the compiler hasn't spotted. eg. in a function application
f (g x)
writing instead
f $! (g x)
will be more efficient if (a) you were going to evaluate (g x)
anyway, and (b) f
isn't visibly strict, or inlined. If f
is strict or inlined, then the chances are that ($!)
is unnecessary cruft here.
A good example is the monadic return. If you find yourself writing
do …
…
return (fn x)
then consider instead writing
do …
…
return $! fn x
it is very rare to actually need laziness in the argument of return here.
Warning: Using any kind of strictness annotations as above can have unexpected impact on program semantics, in particular when certain optimizations are performed by the compiler. See correctness of short cut fusion.
Rule of Thumb for Strictness Annotation
A rule of thumb for when strictness annotation might be needed:
When a function f
with argument x
satisfies both conditions:

f
calls a function on a function ofx
:(h (g x))
 is not already strict in
x
(does not inspectx
's value),
then it can be helpful to force evaluation:
Example:
 Force Strict: Make g's argument smaller.
f x = g $! (h x)
 Don't force: f isn't building on x, so just let g deal with it.
f x = g x
 Don't force: f is already strict in x
f x = case x of
0 > (h (g x))