* [Caml-list] Ocaml optimizer pitfalls & work-arounds @ 2017-01-19 6:51 Mark Hayden 2017-01-19 11:20 ` Nils Becker ` (2 more replies) 0 siblings, 3 replies; 14+ messages in thread From: Mark Hayden @ 2017-01-19 6:51 UTC (permalink / raw) To: caml-list We recently upgraded our Ocaml toolchain from 4.02.3 to Ocaml 4.04.0. We were looking forward to a performance boost from the optimization improvements, especially from flambda. While we generally were able to achieve significant performance improvement, we were somewhat surprised by the effort required to avoid certain pitfalls in Ocaml. This note describes some issues we ran into. We filed several reports on Ocaml Mantis regarding our findings. However it appears the underlying issues we ran into are unlikely to change: Your three reports (0007440, 0007441, 0007442) are manifestations of the same fact: the OCaml compiler performs type-based optimizations first, then erases types, then performs all the other optimizations. This is very unlikely to change in the near future, as it would require a total rewrite of the compiler. [X Leroy, https://caml.inria.fr/mantis/view.php?id=7440] I encourage readers to review the problem reports we submitted, which include more concrete examples. I'm posting this note in case there are others running into similar performance issues with their Ocaml software and who might find it helpful in working around those issues. I'm not aware of them being documented elsewhere and there appears to be little prospect of the issues being addressed in the compiler in the forseeable future. Please chime in if any of this is inaccurate or there is something I missed. As an initial example, consider the following Ocaml code to find the maximum floating point value in an array (that is at least 0.0): [Array.fold_left max 0.0 arr] Now compile this with the latest compiler and maximum optimization. Because of how the Ocaml optimization works, this will run about 10-15x slower (and allocate 2-3 words per array element) than a more carefully written version that uses specialized operations and avoids allocation. See below for one way to achieve this (while still using a functional-programming style). (* Same as Array.fold_left, but with type casting. *) let [@inline] array_fold_leftf f (x:float) (a:float array) = let r = ref x in for i = 0 to Array.length a - 1 do r := f !r (Array.unsafe_get a i) done; !r ;; let [@inline] float_max (v0:float) v1 = if v0 > v1 then v0 else v1 ;; let array_float_max a = array_fold_leftf float_max 0.0 a ;; The assembly for the "inner loop" for the two examples are below. They were compiled with Ocaml 4.05.dev+flambda, "-O3 -unbox-closures", MacOS 12.2, AMD64. Unoptimized example. Note test/branch for array tag. Allocation for boxing (we did not include the calls to trigger a minor gc). There is a call to Ocaml runtime for polymorphic greater-equal. This is probably not what one would expect from an optimizing/inline compiler for a simple case such as this. Note that to create this we used our own definition of Array.fold_left which had an "[@inline]" annotation. L215: movq (%rsp), %rbx .loc 1 38 14 movzbq -8(%rbx), %rax cmpq $254, %rax je L219 .loc 1 38 14 movq -4(%rbx,%rdx,4), %rsi movq %rsi, 24(%rsp) jmp L218 .align 2 L219: .loc 1 38 14 L221: subq $16, %r15 movq _caml_young_limit@GOTPCREL(%rip), %rax cmpq (%rax), %r15 jb L222 leaq 8(%r15), %rsi movq $1277, -8(%rsi) .loc 1 38 14 movsd -4(%rbx,%rdx,4), %xmm0 movsd %xmm0, (%rsi) movq %rsi, 24(%rsp) L218: movq %rdi, 32(%rsp) .file 5 "pervasives.ml" .loc 5 65 17 movq _caml_greaterequal@GOTPCREL(%rip), %rax call _caml_c_call L213: movq _caml_young_ptr@GOTPCREL(%rip), %r11 movq (%r11), %r15 cmpq $1, %rax je L217 movq 32(%rsp), %rdi jmp L216 .align 2 L217: movq 24(%rsp), %rdi L216: movq 8(%rsp), %rdx movq %rdx, %rax addq $2, %rdx movq %rdx, 8(%rsp) movq 16(%rsp), %rbx cmpq %rbx, %rax jne L215 The assembly for the more carefully writting case is below. No allocation. No call to external C code. No test/branch for array tag. This matches what I think most people would like to see. It is compact enough that (maybe) it would benefit from unrolling: l225: .loc 1 46 14 movsd -4(%rax,%rdi,4), %xmm1 comisd %xmm1, %xmm0 jbe l227 jmp l226 .align 2 l227: movapd %xmm1, %xmm0 l226: movq %rdi, %rsi addq $2, %rdi cmpq %rbx, %rsi jne l225 The two main learnings we found were: * Polymorphic primitives ([Array.get], [compare], [>=], [min]) are only specialized if they appear in a context where the types can be determined at their exact call site, otherwise a polymorphic version is used. If the use of the primitive is later inlined in a context where the type is no longer polymorphic, the function will _not_ be specialized by the compiler. * Use of abstract data types prevents specialization. In particular, defining an abstract data type in a module ("type t ;;") will prevent specialization (even after inlining) for any polymorphic primitives (eg, "caml_equal") used with that type. For instance, if the underlying type for [t] is actually [int], other modules will still use polymorphic equality instead of a single machine instruction. You can prevent this behavior with the "private" keyword in order to export the type information, "type t = private int". Alternatively, the module can include its own specialized operations and other modules can be careful to use them. It bears emphasizing that the issues described in this note apply even when all of the code is "fully inlined" and uses highest level of optimization. Specialization in the Ocaml compiler occurs in a stage prior to inlining. If it hasn’t happened before inlining, it won’t happen afterwards. What kind of effect does lack of specialization have on performance? Calling the "caml_compare" Ocaml C runtime function to compare integers can be 10-20x times slower than using a single integer comparison machine instruction. Ditto for floating point values. The unspecialized [Array.get], [Array.set], and (on 32-bit) [Array.length] have to check the tag on the array to determine if the array uses the unboxed floating-point represntation (I wish Ocaml didn't use this!). For instance, the polymorphic [Array.get] checks the tag on the array and (for floating point arrays) reads the value and boxes the floating point value (ie, allocate 2-3 words on the heap). Note that when iterating over an array, the check on the tag will be included in _each_ loop iteration. Other impacts of using non-specialized functions: * Use of polymorphic primitives means floating point values have to be boxed, requiring heap allocation. Through use of specialized specialized primitives, in many cases floats can remain unboxed. * All the extra native code from using polymorphic primitives (checking array tags, conditionally boxing floats, calling out to Ocaml C runtime) can have follow-on effects for further inlining. In other words, when native code can be kept compact, then more code can be inlined and/or loops unrolled and this can in turn allow further optimization. Some suggestions others may find helpful: * Consider using the "private" keyword for any abstract types in your modules. We added over 50 of these to our code base. It is an ugly but effective work-around. * The min/max functions in standard library Pervasives are particularly problematic. They are polymorphic so their comparison will never be specialized. It can be helpful to define specialized functions such as: let [@inline] float_max (v0:float) (v1:float) = if v0 > v1 then v0 else v1 ;; let [@inline] int_max (v0:int) (v1:int) = if v0 > v1 then v0 else v1 ;; These will be compiled to use native machine code and unboxed values. * Any use of polymorphism can negatively affect performance. Be careful about inadvertently introducing polymorphism into your program, such as this helper function: let [@inline] getter v ofs = Array.get v ofs ;; This will result in unspecialized version of [Array.get] being inlined at all call-sites. Note that if your .mli file defines the function as non-polymorphic that will still _not_ affect how [getter] is compiled.: type getter : t -> int -> int ;; (* does not affect optimization *) You must cast the type in the implementation in order for [Array.get] to be specialized: let [@inline] getter (v:int array) ofs = Array.get v ofs ;; * All the iterators in the Array module (eg, [Array.iter]) in the standard library are polymorphic, so will use unspecialized accessors and be affected by the issues described here. Using the following to sum and array of floats may seem elegant: Array.fold_left (+) 0.0 arr However, the resulting code is much slower (and allocates 2 floats per array entry, ie 4-6 words) than a "specialized" version. Note that even if [Array.fold_left] and surrounding code were "fully inlined," it is still a polymorphic function so the above performance penalty for checking the array tag and boxing the float is present. See also the earlier example. * It can be helpful to review the compiled assembly code (using "-S" option for ocamlopt) and look for tell-tale signs of lack of specialization, such as calls to [_caml_greaterequal] or allocation [caml_call_gc] in cases where they are not expected. You can refer to the assembly code for the original implementation, know that that code will not be specialized when inlined. As I said, by examining our hot spots and following the suggestions above, we found the resulting native code could be comparable to what we would expect from C. It is unfortunate these issues were (apparently) designed into the Ocaml compiler architecture, because otherwise it would have seemed this would be a natural area of improvement for the compiler. I would have thought a staticly typed language such as Ocaml would (through its type checker) be well-suited for the simple types of function specialization described in this note. ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 6:51 [Caml-list] Ocaml optimizer pitfalls & work-arounds Mark Hayden @ 2017-01-19 11:20 ` Nils Becker 2017-01-19 11:39 ` Gabriel Scherer 2017-01-19 14:35 ` Alain Frisch 2017-01-19 13:41 ` Yaron Minsky 2017-01-21 14:39 ` [Caml-list] <DKIM> " Pierre Chambart 2 siblings, 2 replies; 14+ messages in thread From: Nils Becker @ 2017-01-19 11:20 UTC (permalink / raw) To: caml-list a while ago there was a proposal for deprecating the specialized treatment of float arrays, which was not accepted iirc. it seems that the slowdown of all Array.get calls is quite a high price to pay. what do we gain from the float array specialization? (honest question - i don't have a good understanding) the min, max issues can be avoided without much trouble by using specialized comparison, as provided in standard library extensions. n. ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 11:20 ` Nils Becker @ 2017-01-19 11:39 ` Gabriel Scherer 2017-01-19 13:26 ` Frédéric Bour 2017-01-19 14:35 ` Alain Frisch 1 sibling, 1 reply; 14+ messages in thread From: Gabriel Scherer @ 2017-01-19 11:39 UTC (permalink / raw) To: Nils Becker; +Cc: caml-list > the min, max issues can be avoided without much trouble by using > specialized comparison, as provided in standard library extensions. Note that min/max are already optimized from generic to specialized when the type information is known at type-checking time. (It used to be the case that only fully applied calls were optimized, this was improved by Frédéric Bour to extend to non-applied primitives in 4.03 (eg. "let eq : int -> int -> _ = (=)"). That does not work when those functions are used inside a functor body at an abstract type (which is when we want inlining and specialization to interact better), but there neither do Float.equal or Int.compare. On Thu, Jan 19, 2017 at 12:20 PM, Nils Becker <nils.becker@bioquant.uni-heidelberg.de> wrote: > a while ago there was a proposal for deprecating the specialized > treatment of float arrays, which was not accepted iirc. it seems that > the slowdown of all Array.get calls is quite a high price to pay. what > do we gain from the float array specialization? (honest question - i > don't have a good understanding) > > the min, max issues can be avoided without much trouble by using > specialized comparison, as provided in standard library extensions. > > n. > > -- > Caml-list mailing list. Subscription management and archives: > https://sympa.inria.fr/sympa/arc/caml-list > Beginner's list: http://groups.yahoo.com/group/ocaml_beginners > Bug reports: http://caml.inria.fr/bin/caml-bugs ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 11:39 ` Gabriel Scherer @ 2017-01-19 13:26 ` Frédéric Bour 0 siblings, 0 replies; 14+ messages in thread From: Frédéric Bour @ 2017-01-19 13:26 UTC (permalink / raw) To: Gabriel Scherer; +Cc: Nils Becker, caml-list [-- Attachment #1: Type: text/plain, Size: 1110 bytes --] Le 19 janv. 2017 à 12:39, Gabriel Scherer <gabriel.scherer@gmail.com> a écrit : > >> the min, max issues can be avoided without much trouble by using >> specialized comparison, as provided in standard library extensions. > > Note that min/max are already optimized from generic to specialized > when the type information is known at type-checking time. (It used to > be the case that only fully applied calls were optimized, this was > improved by Frédéric Bour to extend to non-applied primitives in 4.03 > (eg. "let eq : int -> int -> _ = (=)"). That does not work when those > functions are used inside a functor body at an abstract type (which is > when we want inlining and specialization to interact better), but > there neither do Float.equal or Int.compare. Alas, min/max cannot benefit from this optimisation. In Pervasives, they are defined as: let min x y = if x <= y then x else y let max x y = if x >= y then x else y Specialization only happens for primitives, here it is a plain definition. So no specialization unless the definitions are copied and annotated :(. [-- Attachment #2: Type: text/html, Size: 5410 bytes --] ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 11:20 ` Nils Becker 2017-01-19 11:39 ` Gabriel Scherer @ 2017-01-19 14:35 ` Alain Frisch 2017-01-19 15:35 ` Ivan Gotovchits 2017-01-19 15:41 ` Gerd Stolpmann 1 sibling, 2 replies; 14+ messages in thread From: Alain Frisch @ 2017-01-19 14:35 UTC (permalink / raw) To: Nils Becker, caml-list On 19/01/2017 12:20, Nils Becker wrote: > a while ago there was a proposal for deprecating the specialized > treatment of float arrays, which was not accepted iirc. For future reference, here are some relevant links: https://www.lexifi.com/blog/about-unboxed-float-arrays https://github.com/ocaml/ocaml/pull/163 https://github.com/ocaml/ocaml/pull/616 > it seems that > the slowdown of all Array.get calls is quite a high price to pay. what > do we gain from the float array specialization? (honest question - i > don't have a good understanding) As far as I understand, the main argument for keeping the special current hack is that it helps beginners writing naive numerical code get something not horribly inefficient, while most proponents of removing the hack are advanced users who feel that the current situation gets in the way towards very efficient code. Providing a FloatArray module would address parts of the concerns from these advanced users. At least it would allow better optimization of numerical code, and pave the way for a future deprecation/removal of the special hack. It would not address bad consequences of the special hack on (i) the performance of generic array accesses would remain and (ii) the complexity and corner cases in the compiler and runtime system. (Another argument in favor of the status quo is that writing "FloatArray.get a i" is syntactically heavier than "a.(i)". Interestingly, I don't feel that the ability to write polymorphic code on arrays and apply it to (unboxed) float arrays is considered as a very important property.) -- Alain ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 14:35 ` Alain Frisch @ 2017-01-19 15:35 ` Ivan Gotovchits 2017-01-19 17:02 ` Hezekiah M. Carty 2017-01-19 15:41 ` Gerd Stolpmann 1 sibling, 1 reply; 14+ messages in thread From: Ivan Gotovchits @ 2017-01-19 15:35 UTC (permalink / raw) To: Alain Frisch; +Cc: Nils Becker, caml-list [-- Attachment #1: Type: text/plain, Size: 906 bytes --] On Thu, Jan 19, 2017 at 9:35 AM, Alain Frisch <alain.frisch@lexifi.com> wrote: > > (Another argument in favor of the status quo is that writing > "FloatArray.get a i" is syntactically heavier than "a.(i)". Interestingly, > I don't feel that the ability to write polymorphic code on arrays and apply > it to (unboxed) float arrays is considered as a very important property.) > This is not a big issue, as you can write: module Array = FloatArray a.(i) and it resolve to a call to the FloatArray.get function, as x.(i) is a syntactic sugar for `Array.get x i`. The same is true to bigarrays. This is kind of a non-documented feature, though. > -- Alain > > > -- > Caml-list mailing list. Subscription management and archives: > https://sympa.inria.fr/sympa/arc/caml-list > Beginner's list: http://groups.yahoo.com/group/ocaml_beginners > Bug reports: http://caml.inria.fr/bin/caml-bugs > > [-- Attachment #2: Type: text/html, Size: 1926 bytes --] ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 15:35 ` Ivan Gotovchits @ 2017-01-19 17:02 ` Hezekiah M. Carty 0 siblings, 0 replies; 14+ messages in thread From: Hezekiah M. Carty @ 2017-01-19 17:02 UTC (permalink / raw) To: Ivan Gotovchits, Alain Frisch; +Cc: Nils Becker, caml-list [-- Attachment #1: Type: text/plain, Size: 960 bytes --] On Thu, Jan 19, 2017 at 8:35 AM Ivan Gotovchits <ivg@ieee.org> wrote: > On Thu, Jan 19, 2017 at 9:35 AM, Alain Frisch <alain.frisch@lexifi.com> > wrote: > > (Another argument in favor of the status quo is that writing > "FloatArray.get a i" is syntactically heavier than "a.(i)". Interestingly, > I don't feel that the ability to write polymorphic code on arrays and apply > it to (unboxed) float arrays is considered as a very important property.) > > > This is not a big issue, as you can write: > > module Array = FloatArray > a.(i) > > and it resolve to a call to the FloatArray.get function, as x.(i) is a > syntactic sugar for `Array.get x i`. The same is true to bigarrays. This is > kind of a non-documented feature, though. > > > > -- Alain > > If we get https://github.com/ocaml/ocaml/pull/622 or https://github.com/ocaml/ocaml/pull/616 then it's even simpler since FloatArray could have or define its own specialized element access. Hez [-- Attachment #2: Type: text/html, Size: 2664 bytes --] ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 14:35 ` Alain Frisch 2017-01-19 15:35 ` Ivan Gotovchits @ 2017-01-19 15:41 ` Gerd Stolpmann 1 sibling, 0 replies; 14+ messages in thread From: Gerd Stolpmann @ 2017-01-19 15:41 UTC (permalink / raw) To: Alain Frisch, Nils Becker, caml-list [-- Attachment #1: Type: text/plain, Size: 800 bytes --] Am Donnerstag, den 19.01.2017, 15:35 +0100 schrieb Alain Frisch: > (Another argument in favor of the status quo is that writing > "FloatArray.get a i" is syntactically heavier than "a.(i)". > Interestingly, I don't feel that the ability to write polymorphic > code > on arrays and apply it to (unboxed) float arrays is considered as a > very > important property.) Any chance that we get implicits? Gerd > -- Alain > -- ------------------------------------------------------------ Gerd Stolpmann, Darmstadt, Germany gerd@gerd-stolpmann.de My OCaml site: http://www.camlcity.org Contact details: http://www.camlcity.org/contact.html Company homepage: http://www.gerd-stolpmann.de ------------------------------------------------------------ [-- Attachment #2: This is a digitally signed message part --] [-- Type: application/pgp-signature, Size: 473 bytes --] ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 6:51 [Caml-list] Ocaml optimizer pitfalls & work-arounds Mark Hayden 2017-01-19 11:20 ` Nils Becker @ 2017-01-19 13:41 ` Yaron Minsky 2017-01-19 17:59 ` Mark Hayden 2017-01-21 14:39 ` [Caml-list] <DKIM> " Pierre Chambart 2 siblings, 1 reply; 14+ messages in thread From: Yaron Minsky @ 2017-01-19 13:41 UTC (permalink / raw) To: Mark Hayden; +Cc: caml-list It seems like your primary issues are around lack of specialization around two features: - unboxing in float arrays - optimization of ad-hoc operations (e.g., polymorphic compare) My view on this is that it's best not to rely on float array specialization at all, and I think the best improvement we can make to OCaml is to remove the ad-hoc specialization of float arrays, and instead add a separate, specialized (and unboxed) type for arrays of floats, similar to the Bytes.t type which is effectively a specialized byte array. As you've observed, specialization is brittle, and it's best not to rely on it too much. Beyond that, the existence of float arrays complicate the runtime quite a bit, and make other bugs more likely. There isn't yet consensus that specialization of float array should be removed, but I'm still hopeful that we'll get there. It's probably Jane Street's highest priority ask for the compiler. We also avoid use of polymorphic compare and other ad-hoc operations, preferring to use type-specialized comparators everywhere. This is better for semantic as well as performance reasons, since we've seen a lot of subtle bugs from polymorphic compare doing the wrong thing on specific types. It's hard to deny that using type-specialized comparators is more verbose than polymorphic compare, but hopefully modular implicits will make this problem go away, and we can get the best of both worlds. And we hope that Flambda will be up to the job of inlining away the overhead of the more indirect calling conventions imposed by modular implicits. I think that with the above changes, we can probably get pretty far towards the goal of being able to write OCaml code that is both highly performant and pretty. Being able to delay specialization until later in the compilation pipeline would help more, but I believe we can do pretty well without it. y On Thu, Jan 19, 2017 at 1:51 AM, Mark Hayden <markghayden@yahoo.com> wrote: > We recently upgraded our Ocaml toolchain from 4.02.3 to Ocaml 4.04.0. > We were looking forward to a performance boost from the optimization > improvements, especially from flambda. While we generally were able > to achieve significant performance improvement, we were somewhat > surprised by the effort required to avoid certain pitfalls in Ocaml. > > This note describes some issues we ran into. We filed several > reports on Ocaml Mantis regarding our findings. However it appears > the underlying issues we ran into are unlikely to change: > > Your three reports (0007440, 0007441, 0007442) are manifestations > of the same fact: the OCaml compiler performs type-based > optimizations first, then erases types, then performs all the other > optimizations. This is very unlikely to change in the near future, > as it would require a total rewrite of the compiler. > > [X Leroy, https://caml.inria.fr/mantis/view.php?id=7440] > > I encourage readers to review the problem reports we submitted, which > include more concrete examples. I'm posting this note in case there > are others running into similar performance issues with their Ocaml > software and who might find it helpful in working around those > issues. I'm not aware of them being documented elsewhere and there > appears to be little prospect of the issues being addressed in the > compiler in the forseeable future. Please chime in if any of this is > inaccurate or there is something I missed. > > As an initial example, consider the following Ocaml code to find the > maximum floating point value in an array (that is at least 0.0): > > [Array.fold_left max 0.0 arr] > > Now compile this with the latest compiler and maximum optimization. > Because of how the Ocaml optimization works, this will run about > 10-15x slower (and allocate 2-3 words per array element) than a more > carefully written version that uses specialized operations and avoids > allocation. See below for one way to achieve this (while still using > a functional-programming style). > > (* Same as Array.fold_left, but with type casting. > *) > let [@inline] array_fold_leftf f (x:float) (a:float array) = > let r = ref x in > for i = 0 to Array.length a - 1 do > r := f !r (Array.unsafe_get a i) > done; > !r > ;; > > let [@inline] float_max (v0:float) v1 = > if v0 > v1 then v0 else v1 > ;; > > let array_float_max a = > array_fold_leftf float_max 0.0 a > ;; > > The assembly for the "inner loop" for the two examples are below. > They were compiled with Ocaml 4.05.dev+flambda, "-O3 > -unbox-closures", MacOS 12.2, AMD64. > > Unoptimized example. Note test/branch for array tag. Allocation for > boxing (we did not include the calls to trigger a minor gc). There > is a call to Ocaml runtime for polymorphic greater-equal. This is > probably not what one would expect from an optimizing/inline compiler > for a simple case such as this. Note that to create this we used our > own definition of Array.fold_left which had an "[@inline]" > annotation. > > L215: > movq (%rsp), %rbx > .loc 1 38 14 > movzbq -8(%rbx), %rax > cmpq $254, %rax > je L219 > .loc 1 38 14 > movq -4(%rbx,%rdx,4), %rsi > movq %rsi, 24(%rsp) > jmp L218 > .align 2 > L219: > .loc 1 38 14 > L221: > subq $16, %r15 > movq _caml_young_limit@GOTPCREL(%rip), %rax > cmpq (%rax), %r15 > jb L222 > leaq 8(%r15), %rsi > movq $1277, -8(%rsi) > .loc 1 38 14 > movsd -4(%rbx,%rdx,4), %xmm0 > movsd %xmm0, (%rsi) > movq %rsi, 24(%rsp) > L218: > movq %rdi, 32(%rsp) > .file 5 "pervasives.ml" > .loc 5 65 17 > movq _caml_greaterequal@GOTPCREL(%rip), %rax > call _caml_c_call > L213: > movq _caml_young_ptr@GOTPCREL(%rip), %r11 > movq (%r11), %r15 > cmpq $1, %rax > je L217 > movq 32(%rsp), %rdi > jmp L216 > .align 2 > L217: > movq 24(%rsp), %rdi > L216: > movq 8(%rsp), %rdx > movq %rdx, %rax > addq $2, %rdx > movq %rdx, 8(%rsp) > movq 16(%rsp), %rbx > cmpq %rbx, %rax > jne L215 > > > The assembly for the more carefully writting case is below. No > allocation. No call to external C code. No test/branch for array > tag. This matches what I think most people would like to see. It is > compact enough that (maybe) it would benefit from unrolling: > > l225: > .loc 1 46 14 > movsd -4(%rax,%rdi,4), %xmm1 > comisd %xmm1, %xmm0 > jbe l227 > jmp l226 > .align 2 > l227: > movapd %xmm1, %xmm0 > l226: > movq %rdi, %rsi > addq $2, %rdi > cmpq %rbx, %rsi > jne l225 > > > The two main learnings we found were: > > * Polymorphic primitives ([Array.get], [compare], [>=], [min]) are > only specialized if they appear in a context where the types can be > determined at their exact call site, otherwise a polymorphic > version is used. If the use of the primitive is later inlined in a > context where the type is no longer polymorphic, the function will > _not_ be specialized by the compiler. > > * Use of abstract data types prevents specialization. In particular, > defining an abstract data type in a module ("type t ;;") will > prevent specialization (even after inlining) for any polymorphic > primitives (eg, "caml_equal") used with that type. For instance, > if the underlying type for [t] is actually [int], other modules > will still use polymorphic equality instead of a single machine > instruction. You can prevent this behavior with the "private" > keyword in order to export the type information, "type t = private > int". Alternatively, the module can include its own specialized > operations and other modules can be careful to use them. > > It bears emphasizing that the issues described in this note apply > even when all of the code is "fully inlined" and uses highest level > of optimization. Specialization in the Ocaml compiler occurs in a > stage prior to inlining. If it hasn’t happened before inlining, it > won’t happen afterwards. > > What kind of effect does lack of specialization have on performance? > Calling the "caml_compare" Ocaml C runtime function to compare > integers can be 10-20x times slower than using a single integer > comparison machine instruction. Ditto for floating point values. > The unspecialized [Array.get], [Array.set], and (on 32-bit) > [Array.length] have to check the tag on the array to determine if the > array uses the unboxed floating-point represntation (I wish Ocaml > didn't use this!). For instance, the polymorphic [Array.get] checks > the tag on the array and (for floating point arrays) reads the value > and boxes the floating point value (ie, allocate 2-3 words on the > heap). Note that when iterating over an array, the check on the tag > will be included in _each_ loop iteration. > > Other impacts of using non-specialized functions: > > * Use of polymorphic primitives means floating point values have to > be boxed, requiring heap allocation. Through use of specialized > specialized primitives, in many cases floats can remain unboxed. > > * All the extra native code from using polymorphic primitives > (checking array tags, conditionally boxing floats, calling out to > Ocaml C runtime) can have follow-on effects for further inlining. > In other words, when native code can be kept compact, then more > code can be inlined and/or loops unrolled and this can in turn > allow further optimization. > > Some suggestions others may find helpful: > > * Consider using the "private" keyword for any abstract types in your > modules. We added over 50 of these to our code base. It is an > ugly but effective work-around. > > * The min/max functions in standard library Pervasives are > particularly problematic. They are polymorphic so their comparison > will never be specialized. It can be helpful to define specialized > functions such as: > > let [@inline] float_max (v0:float) (v1:float) = > if v0 > v1 then v0 else v1 > ;; > > let [@inline] int_max (v0:int) (v1:int) = > if v0 > v1 then v0 else v1 > ;; > > These will be compiled to use native machine code and unboxed > values. > > * Any use of polymorphism can negatively affect performance. Be > careful about inadvertently introducing polymorphism into your > program, such as this helper function: > > let [@inline] getter v ofs = Array.get v ofs ;; > > This will result in unspecialized version of [Array.get] being > inlined at all call-sites. Note that if your .mli file defines the > function as non-polymorphic that will still _not_ affect how > [getter] is compiled.: > > type getter : t -> int -> int ;; (* does not affect optimization *) > > You must cast the type in the implementation in order for [Array.get] > to be specialized: > > let [@inline] getter (v:int array) ofs = Array.get v ofs ;; > > * All the iterators in the Array module (eg, [Array.iter]) in the > standard library are polymorphic, so will use unspecialized > accessors and be affected by the issues described here. Using the > following to sum and array of floats may seem elegant: > > Array.fold_left (+) 0.0 arr > > However, the resulting code is much slower (and allocates 2 floats > per array entry, ie 4-6 words) than a "specialized" version. Note > that even if [Array.fold_left] and surrounding code were "fully > inlined," it is still a polymorphic function so the above > performance penalty for checking the array tag and boxing the float > is present. See also the earlier example. > > * It can be helpful to review the compiled assembly code (using "-S" > option for ocamlopt) and look for tell-tale signs of lack of > specialization, such as calls to [_caml_greaterequal] or allocation > [caml_call_gc] in cases where they are not expected. You can refer > to the assembly code for the original implementation, know that > that code will not be specialized when inlined. > > As I said, by examining our hot spots and following the suggestions > above, we found the resulting native code could be comparable to what > we would expect from C. It is unfortunate these issues were > (apparently) designed into the Ocaml compiler architecture, because > otherwise it would have seemed this would be a natural area of > improvement for the compiler. I would have thought a staticly typed > language such as Ocaml would (through its type checker) be > well-suited for the simple types of function specialization described > in this note. > > > -- > Caml-list mailing list. Subscription management and archives: > https://sympa.inria.fr/sympa/arc/caml-list > Beginner's list: http://groups.yahoo.com/group/ocaml_beginners > Bug reports: http://caml.inria.fr/bin/caml-bugs ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 13:41 ` Yaron Minsky @ 2017-01-19 17:59 ` Mark Hayden 2017-01-19 22:30 ` Yaron Minsky 0 siblings, 1 reply; 14+ messages in thread From: Mark Hayden @ 2017-01-19 17:59 UTC (permalink / raw) To: Yaron Minsky; +Cc: caml-list I agree that removal of the current treatment of float array would eliminate the biggest issues and that would avoid some of the bigger issues. However, our issue is not just with how float arrays are handled. Comparisons for integer/char/bool types should always be specialized after inlining. As things stand (and apparently this is unlikely to change), Ocaml programmers who want best performance need to learn to developer their software to carefully tailor use of polymorphism, abstraction, min/max, etc, at least for parts where performance is important. This is too bad... the type checker infers the types but (according to X Leroy) the type information is no longer available by the time inlining occurs. Below is an example taking the maximum (at least 0) of an array of an array of integers. The natural way to implement this is: let array_sum arr = Array.fold_left max 0 arr ;; The inner loop compiles to the code below (again, with Array.fold_left redefined to be annotated with “[@inline]”). Because of how the Ocaml compiler is architected, the array operations and comparison operations will not be specialized, even though the code is inlined and the array type has been inferred to be [int array]. Removing the special “float array” treatment from Ocaml would at least eliminate the "dead code" for checking and boxing for floats, but the call to [_caml_greaterequal] would still be used instead of a single comparison instruction. L258: movq (%rsp), %rbx .loc 1 38 14 movzbq -8(%rbx), %rax cmpq $254, %rax je L262 .loc 1 38 14 movq -4(%rbx,%rdx,4), %rsi movq %rsi, 24(%rsp) jmp L261 .align 2 L262: .loc 1 38 14 L264: subq $16, %r15 movq _caml_young_limit@GOTPCREL(%rip), %rax cmpq (%rax), %r15 jb L265 leaq 8(%r15), %rsi movq $1277, -8(%rsi) .loc 1 38 14 movsd -4(%rbx,%rdx,4), %xmm0 movsd %xmm0, (%rsi) movq %rsi, 24(%rsp) L261: movq %rdi, 32(%rsp) .loc 5 65 17 movq _caml_greaterequal@GOTPCREL(%rip), %rax call _caml_c_call L256: movq _caml_young_ptr@GOTPCREL(%rip), %r11 movq (%r11), %r15 cmpq $1, %rax je L260 movq 32(%rsp), %rdi jmp L259 .align 2 L260: movq 24(%rsp), %rdi L259: movq 8(%rsp), %rdx movq %rdx, %rax addq $2, %rdx movq %rdx, 8(%rsp) movq 16(%rsp), %rbx cmpq %rbx, %rax jne L258 If you write it like this: let [@inline] array_fold_left_i f (x:int) (a:int array) = let r = ref x in for i = 0 to Array.length a - 1 do r := f !r (Array.unsafe_get a i) done; !r ;; let [@inline] int_max (v0:int) v1 = if v0 > v1 then v0 else v1 ;; let array_int_max a = array_fold_left_i int_max 0 a ;; Then the inner loop will compile as follows, which is about 5-15x faster than the code above and I think most developers would be pleased with. L284: .loc 1 54 14 movq -4(%rbx,%rsi,4), %rdx cmpq %rdx, %rdi jle L286 jmp L285 .align 2 L286: movq %rdx, %rdi L285: movq %rsi, %rdx addq $2, %rsi cmpq %rax, %rdx jne L284 > On Jan 19, 2017, at 5:41 AM, Yaron Minsky <yminsky@janestreet.com> wrote: > > It seems like your primary issues are around lack of specialization > around two features: > > - unboxing in float arrays > - optimization of ad-hoc operations (e.g., polymorphic compare) > > My view on this is that it's best not to rely on float array > specialization at all, and I think the best improvement we can make to > OCaml is to remove the ad-hoc specialization of float arrays, and > instead add a separate, specialized (and unboxed) type for arrays of > floats, similar to the Bytes.t type which is effectively a specialized > byte array. > > As you've observed, specialization is brittle, and it's best not to > rely on it too much. Beyond that, the existence of float arrays > complicate the runtime quite a bit, and make other bugs more likely. > > There isn't yet consensus that specialization of float array should be > removed, but I'm still hopeful that we'll get there. It's probably > Jane Street's highest priority ask for the compiler. > > We also avoid use of polymorphic compare and other ad-hoc operations, > preferring to use type-specialized comparators everywhere. This is > better for semantic as well as performance reasons, since we've seen a > lot of subtle bugs from polymorphic compare doing the wrong thing on > specific types. > > It's hard to deny that using type-specialized comparators is more > verbose than polymorphic compare, but hopefully modular implicits will > make this problem go away, and we can get the best of both worlds. And > we hope that Flambda will be up to the job of inlining away the > overhead of the more indirect calling conventions imposed by modular > implicits. > > I think that with the above changes, we can probably get pretty far > towards the goal of being able to write OCaml code that is both highly > performant and pretty. Being able to delay specialization until later > in the compilation pipeline would help more, but I believe we can do > pretty well without it. > > y > > > On Thu, Jan 19, 2017 at 1:51 AM, Mark Hayden <markghayden@yahoo.com> wrote: >> We recently upgraded our Ocaml toolchain from 4.02.3 to Ocaml 4.04.0. >> We were looking forward to a performance boost from the optimization >> improvements, especially from flambda. While we generally were able >> to achieve significant performance improvement, we were somewhat >> surprised by the effort required to avoid certain pitfalls in Ocaml. >> >> This note describes some issues we ran into. We filed several >> reports on Ocaml Mantis regarding our findings. However it appears >> the underlying issues we ran into are unlikely to change: >> >> Your three reports (0007440, 0007441, 0007442) are manifestations >> of the same fact: the OCaml compiler performs type-based >> optimizations first, then erases types, then performs all the other >> optimizations. This is very unlikely to change in the near future, >> as it would require a total rewrite of the compiler. >> >> [X Leroy, https://caml.inria.fr/mantis/view.php?id=7440] >> >> I encourage readers to review the problem reports we submitted, which >> include more concrete examples. I'm posting this note in case there >> are others running into similar performance issues with their Ocaml >> software and who might find it helpful in working around those >> issues. I'm not aware of them being documented elsewhere and there >> appears to be little prospect of the issues being addressed in the >> compiler in the forseeable future. Please chime in if any of this is >> inaccurate or there is something I missed. >> >> As an initial example, consider the following Ocaml code to find the >> maximum floating point value in an array (that is at least 0.0): >> >> [Array.fold_left max 0.0 arr] >> >> Now compile this with the latest compiler and maximum optimization. >> Because of how the Ocaml optimization works, this will run about >> 10-15x slower (and allocate 2-3 words per array element) than a more >> carefully written version that uses specialized operations and avoids >> allocation. See below for one way to achieve this (while still using >> a functional-programming style). >> >> (* Same as Array.fold_left, but with type casting. >> *) >> let [@inline] array_fold_leftf f (x:float) (a:float array) = >> let r = ref x in >> for i = 0 to Array.length a - 1 do >> r := f !r (Array.unsafe_get a i) >> done; >> !r >> ;; >> >> let [@inline] float_max (v0:float) v1 = >> if v0 > v1 then v0 else v1 >> ;; >> >> let array_float_max a = >> array_fold_leftf float_max 0.0 a >> ;; >> >> The assembly for the "inner loop" for the two examples are below. >> They were compiled with Ocaml 4.05.dev+flambda, "-O3 >> -unbox-closures", MacOS 12.2, AMD64. >> >> Unoptimized example. Note test/branch for array tag. Allocation for >> boxing (we did not include the calls to trigger a minor gc). There >> is a call to Ocaml runtime for polymorphic greater-equal. This is >> probably not what one would expect from an optimizing/inline compiler >> for a simple case such as this. Note that to create this we used our >> own definition of Array.fold_left which had an "[@inline]" >> annotation. >> >> L215: >> movq (%rsp), %rbx >> .loc 1 38 14 >> movzbq -8(%rbx), %rax >> cmpq $254, %rax >> je L219 >> .loc 1 38 14 >> movq -4(%rbx,%rdx,4), %rsi >> movq %rsi, 24(%rsp) >> jmp L218 >> .align 2 >> L219: >> .loc 1 38 14 >> L221: >> subq $16, %r15 >> movq _caml_young_limit@GOTPCREL(%rip), %rax >> cmpq (%rax), %r15 >> jb L222 >> leaq 8(%r15), %rsi >> movq $1277, -8(%rsi) >> .loc 1 38 14 >> movsd -4(%rbx,%rdx,4), %xmm0 >> movsd %xmm0, (%rsi) >> movq %rsi, 24(%rsp) >> L218: >> movq %rdi, 32(%rsp) >> .file 5 "pervasives.ml" >> .loc 5 65 17 >> movq _caml_greaterequal@GOTPCREL(%rip), %rax >> call _caml_c_call >> L213: >> movq _caml_young_ptr@GOTPCREL(%rip), %r11 >> movq (%r11), %r15 >> cmpq $1, %rax >> je L217 >> movq 32(%rsp), %rdi >> jmp L216 >> .align 2 >> L217: >> movq 24(%rsp), %rdi >> L216: >> movq 8(%rsp), %rdx >> movq %rdx, %rax >> addq $2, %rdx >> movq %rdx, 8(%rsp) >> movq 16(%rsp), %rbx >> cmpq %rbx, %rax >> jne L215 >> >> >> The assembly for the more carefully writting case is below. No >> allocation. No call to external C code. No test/branch for array >> tag. This matches what I think most people would like to see. It is >> compact enough that (maybe) it would benefit from unrolling: >> >> l225: >> .loc 1 46 14 >> movsd -4(%rax,%rdi,4), %xmm1 >> comisd %xmm1, %xmm0 >> jbe l227 >> jmp l226 >> .align 2 >> l227: >> movapd %xmm1, %xmm0 >> l226: >> movq %rdi, %rsi >> addq $2, %rdi >> cmpq %rbx, %rsi >> jne l225 >> >> >> The two main learnings we found were: >> >> * Polymorphic primitives ([Array.get], [compare], [>=], [min]) are >> only specialized if they appear in a context where the types can be >> determined at their exact call site, otherwise a polymorphic >> version is used. If the use of the primitive is later inlined in a >> context where the type is no longer polymorphic, the function will >> _not_ be specialized by the compiler. >> >> * Use of abstract data types prevents specialization. In particular, >> defining an abstract data type in a module ("type t ;;") will >> prevent specialization (even after inlining) for any polymorphic >> primitives (eg, "caml_equal") used with that type. For instance, >> if the underlying type for [t] is actually [int], other modules >> will still use polymorphic equality instead of a single machine >> instruction. You can prevent this behavior with the "private" >> keyword in order to export the type information, "type t = private >> int". Alternatively, the module can include its own specialized >> operations and other modules can be careful to use them. >> >> It bears emphasizing that the issues described in this note apply >> even when all of the code is "fully inlined" and uses highest level >> of optimization. Specialization in the Ocaml compiler occurs in a >> stage prior to inlining. If it hasn’t happened before inlining, it >> won’t happen afterwards. >> >> What kind of effect does lack of specialization have on performance? >> Calling the "caml_compare" Ocaml C runtime function to compare >> integers can be 10-20x times slower than using a single integer >> comparison machine instruction. Ditto for floating point values. >> The unspecialized [Array.get], [Array.set], and (on 32-bit) >> [Array.length] have to check the tag on the array to determine if the >> array uses the unboxed floating-point represntation (I wish Ocaml >> didn't use this!). For instance, the polymorphic [Array.get] checks >> the tag on the array and (for floating point arrays) reads the value >> and boxes the floating point value (ie, allocate 2-3 words on the >> heap). Note that when iterating over an array, the check on the tag >> will be included in _each_ loop iteration. >> >> Other impacts of using non-specialized functions: >> >> * Use of polymorphic primitives means floating point values have to >> be boxed, requiring heap allocation. Through use of specialized >> specialized primitives, in many cases floats can remain unboxed. >> >> * All the extra native code from using polymorphic primitives >> (checking array tags, conditionally boxing floats, calling out to >> Ocaml C runtime) can have follow-on effects for further inlining. >> In other words, when native code can be kept compact, then more >> code can be inlined and/or loops unrolled and this can in turn >> allow further optimization. >> >> Some suggestions others may find helpful: >> >> * Consider using the "private" keyword for any abstract types in your >> modules. We added over 50 of these to our code base. It is an >> ugly but effective work-around. >> >> * The min/max functions in standard library Pervasives are >> particularly problematic. They are polymorphic so their comparison >> will never be specialized. It can be helpful to define specialized >> functions such as: >> >> let [@inline] float_max (v0:float) (v1:float) = >> if v0 > v1 then v0 else v1 >> ;; >> >> let [@inline] int_max (v0:int) (v1:int) = >> if v0 > v1 then v0 else v1 >> ;; >> >> These will be compiled to use native machine code and unboxed >> values. >> >> * Any use of polymorphism can negatively affect performance. Be >> careful about inadvertently introducing polymorphism into your >> program, such as this helper function: >> >> let [@inline] getter v ofs = Array.get v ofs ;; >> >> This will result in unspecialized version of [Array.get] being >> inlined at all call-sites. Note that if your .mli file defines the >> function as non-polymorphic that will still _not_ affect how >> [getter] is compiled.: >> >> type getter : t -> int -> int ;; (* does not affect optimization *) >> >> You must cast the type in the implementation in order for [Array.get] >> to be specialized: >> >> let [@inline] getter (v:int array) ofs = Array.get v ofs ;; >> >> * All the iterators in the Array module (eg, [Array.iter]) in the >> standard library are polymorphic, so will use unspecialized >> accessors and be affected by the issues described here. Using the >> following to sum and array of floats may seem elegant: >> >> Array.fold_left (+) 0.0 arr >> >> However, the resulting code is much slower (and allocates 2 floats >> per array entry, ie 4-6 words) than a "specialized" version. Note >> that even if [Array.fold_left] and surrounding code were "fully >> inlined," it is still a polymorphic function so the above >> performance penalty for checking the array tag and boxing the float >> is present. See also the earlier example. >> >> * It can be helpful to review the compiled assembly code (using "-S" >> option for ocamlopt) and look for tell-tale signs of lack of >> specialization, such as calls to [_caml_greaterequal] or allocation >> [caml_call_gc] in cases where they are not expected. You can refer >> to the assembly code for the original implementation, know that >> that code will not be specialized when inlined. >> >> As I said, by examining our hot spots and following the suggestions >> above, we found the resulting native code could be comparable to what >> we would expect from C. It is unfortunate these issues were >> (apparently) designed into the Ocaml compiler architecture, because >> otherwise it would have seemed this would be a natural area of >> improvement for the compiler. I would have thought a staticly typed >> language such as Ocaml would (through its type checker) be >> well-suited for the simple types of function specialization described >> in this note. >> >> >> -- >> Caml-list mailing list. Subscription management and archives: >> https://sympa.inria.fr/sympa/arc/caml-list >> Beginner's list: http://groups.yahoo.com/group/ocaml_beginners >> Bug reports: http://caml.inria.fr/bin/caml-bugs ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 17:59 ` Mark Hayden @ 2017-01-19 22:30 ` Yaron Minsky 2017-01-22 20:06 ` Berke Durak 0 siblings, 1 reply; 14+ messages in thread From: Yaron Minsky @ 2017-01-19 22:30 UTC (permalink / raw) To: Mark Hayden; +Cc: caml-list On Thu, Jan 19, 2017 at 12:59 PM, Mark Hayden <markghayden@yahoo.com> wrote: > I agree that removal of the current treatment of float array would > eliminate the biggest issues and that would avoid some of the bigger > issues. However, our issue is not just with how float arrays are > handled. Comparisons for integer/char/bool types should always be > specialized after inlining. I think eliminating polymorphic compare and adding modular implicits would take care of this issue. In that case, you could write: a > 3 and modular implicits could be used to pick the specialized comparison function for this type. This would fix both the performance problem and the semantic problems of polymorphic compare. Modular implicits is a big change, but unlike changes to where type information is available in the compiler, it's one that is actually in progress and seems like it's really going to land. But I agree: for right now, OCaml developers who care about performance need to be careful about exactly the issues you highlight. For what it's worth, Base, which is our not-quite-ready-for-prime-time alternative to the OCaml stdlib, hides polymorphic comparison functions by default. > As things stand (and apparently this is unlikely to change), Ocaml > programmers who want best performance need to learn to developer > their software to carefully tailor use of polymorphism, abstraction, > min/max, etc, at least for parts where performance is important. > This is too bad... the type checker infers the types but (according > to X Leroy) the type information is no longer available by the time > inlining occurs. > > Below is an example taking the maximum (at least 0) of an array of > an array of integers. The natural way to implement this is: > > let array_sum arr = > Array.fold_left max 0 arr > ;; > > The inner loop compiles to the code below (again, with > Array.fold_left redefined to be annotated with “[@inline]”). > Because of how the Ocaml compiler is architected, the array > operations and comparison operations will not be specialized, even > though the code is inlined and the array type has been inferred to > be [int array]. Removing the special “float array” treatment from > Ocaml would at least eliminate the "dead code" for checking and > boxing for floats, but the call to [_caml_greaterequal] would still > be used instead of a single comparison instruction. > > L258: > movq (%rsp), %rbx > .loc 1 38 14 > movzbq -8(%rbx), %rax > cmpq $254, %rax > je L262 > .loc 1 38 14 > movq -4(%rbx,%rdx,4), %rsi > movq %rsi, 24(%rsp) > jmp L261 > .align 2 > L262: > .loc 1 38 14 > L264: > subq $16, %r15 > movq _caml_young_limit@GOTPCREL(%rip), %rax > cmpq (%rax), %r15 > jb L265 > leaq 8(%r15), %rsi > movq $1277, -8(%rsi) > .loc 1 38 14 > movsd -4(%rbx,%rdx,4), %xmm0 > movsd %xmm0, (%rsi) > movq %rsi, 24(%rsp) > L261: > movq %rdi, 32(%rsp) > .loc 5 65 17 > movq _caml_greaterequal@GOTPCREL(%rip), %rax > call _caml_c_call > L256: > movq _caml_young_ptr@GOTPCREL(%rip), %r11 > movq (%r11), %r15 > cmpq $1, %rax > je L260 > movq 32(%rsp), %rdi > jmp L259 > .align 2 > L260: > movq 24(%rsp), %rdi > L259: > movq 8(%rsp), %rdx > movq %rdx, %rax > addq $2, %rdx > movq %rdx, 8(%rsp) > movq 16(%rsp), %rbx > cmpq %rbx, %rax > jne L258 > > If you write it like this: > > let [@inline] array_fold_left_i f (x:int) (a:int array) = > let r = ref x in > for i = 0 to Array.length a - 1 do > r := f !r (Array.unsafe_get a i) > done; > !r > ;; > > let [@inline] int_max (v0:int) v1 = > if v0 > v1 then v0 else v1 > ;; > > let array_int_max a = > array_fold_left_i int_max 0 a > ;; > > Then the inner loop will compile as follows, which is about 5-15x faster than the code above and I think most developers would be pleased with. > > L284: > .loc 1 54 14 > movq -4(%rbx,%rsi,4), %rdx > cmpq %rdx, %rdi > jle L286 > jmp L285 > .align 2 > L286: > movq %rdx, %rdi > L285: > movq %rsi, %rdx > addq $2, %rsi > cmpq %rax, %rdx > jne L284 > > > > > >> On Jan 19, 2017, at 5:41 AM, Yaron Minsky <yminsky@janestreet.com> wrote: >> >> It seems like your primary issues are around lack of specialization >> around two features: >> >> - unboxing in float arrays >> - optimization of ad-hoc operations (e.g., polymorphic compare) >> >> My view on this is that it's best not to rely on float array >> specialization at all, and I think the best improvement we can make to >> OCaml is to remove the ad-hoc specialization of float arrays, and >> instead add a separate, specialized (and unboxed) type for arrays of >> floats, similar to the Bytes.t type which is effectively a specialized >> byte array. >> >> As you've observed, specialization is brittle, and it's best not to >> rely on it too much. Beyond that, the existence of float arrays >> complicate the runtime quite a bit, and make other bugs more likely. >> >> There isn't yet consensus that specialization of float array should be >> removed, but I'm still hopeful that we'll get there. It's probably >> Jane Street's highest priority ask for the compiler. >> >> We also avoid use of polymorphic compare and other ad-hoc operations, >> preferring to use type-specialized comparators everywhere. This is >> better for semantic as well as performance reasons, since we've seen a >> lot of subtle bugs from polymorphic compare doing the wrong thing on >> specific types. >> >> It's hard to deny that using type-specialized comparators is more >> verbose than polymorphic compare, but hopefully modular implicits will >> make this problem go away, and we can get the best of both worlds. And >> we hope that Flambda will be up to the job of inlining away the >> overhead of the more indirect calling conventions imposed by modular >> implicits. >> >> I think that with the above changes, we can probably get pretty far >> towards the goal of being able to write OCaml code that is both highly >> performant and pretty. Being able to delay specialization until later >> in the compilation pipeline would help more, but I believe we can do >> pretty well without it. >> >> y >> >> >> On Thu, Jan 19, 2017 at 1:51 AM, Mark Hayden <markghayden@yahoo.com> wrote: >>> We recently upgraded our Ocaml toolchain from 4.02.3 to Ocaml 4.04.0. >>> We were looking forward to a performance boost from the optimization >>> improvements, especially from flambda. While we generally were able >>> to achieve significant performance improvement, we were somewhat >>> surprised by the effort required to avoid certain pitfalls in Ocaml. >>> >>> This note describes some issues we ran into. We filed several >>> reports on Ocaml Mantis regarding our findings. However it appears >>> the underlying issues we ran into are unlikely to change: >>> >>> Your three reports (0007440, 0007441, 0007442) are manifestations >>> of the same fact: the OCaml compiler performs type-based >>> optimizations first, then erases types, then performs all the other >>> optimizations. This is very unlikely to change in the near future, >>> as it would require a total rewrite of the compiler. >>> >>> [X Leroy, https://caml.inria.fr/mantis/view.php?id=7440] >>> >>> I encourage readers to review the problem reports we submitted, which >>> include more concrete examples. I'm posting this note in case there >>> are others running into similar performance issues with their Ocaml >>> software and who might find it helpful in working around those >>> issues. I'm not aware of them being documented elsewhere and there >>> appears to be little prospect of the issues being addressed in the >>> compiler in the forseeable future. Please chime in if any of this is >>> inaccurate or there is something I missed. >>> >>> As an initial example, consider the following Ocaml code to find the >>> maximum floating point value in an array (that is at least 0.0): >>> >>> [Array.fold_left max 0.0 arr] >>> >>> Now compile this with the latest compiler and maximum optimization. >>> Because of how the Ocaml optimization works, this will run about >>> 10-15x slower (and allocate 2-3 words per array element) than a more >>> carefully written version that uses specialized operations and avoids >>> allocation. See below for one way to achieve this (while still using >>> a functional-programming style). >>> >>> (* Same as Array.fold_left, but with type casting. >>> *) >>> let [@inline] array_fold_leftf f (x:float) (a:float array) = >>> let r = ref x in >>> for i = 0 to Array.length a - 1 do >>> r := f !r (Array.unsafe_get a i) >>> done; >>> !r >>> ;; >>> >>> let [@inline] float_max (v0:float) v1 = >>> if v0 > v1 then v0 else v1 >>> ;; >>> >>> let array_float_max a = >>> array_fold_leftf float_max 0.0 a >>> ;; >>> >>> The assembly for the "inner loop" for the two examples are below. >>> They were compiled with Ocaml 4.05.dev+flambda, "-O3 >>> -unbox-closures", MacOS 12.2, AMD64. >>> >>> Unoptimized example. Note test/branch for array tag. Allocation for >>> boxing (we did not include the calls to trigger a minor gc). There >>> is a call to Ocaml runtime for polymorphic greater-equal. This is >>> probably not what one would expect from an optimizing/inline compiler >>> for a simple case such as this. Note that to create this we used our >>> own definition of Array.fold_left which had an "[@inline]" >>> annotation. >>> >>> L215: >>> movq (%rsp), %rbx >>> .loc 1 38 14 >>> movzbq -8(%rbx), %rax >>> cmpq $254, %rax >>> je L219 >>> .loc 1 38 14 >>> movq -4(%rbx,%rdx,4), %rsi >>> movq %rsi, 24(%rsp) >>> jmp L218 >>> .align 2 >>> L219: >>> .loc 1 38 14 >>> L221: >>> subq $16, %r15 >>> movq _caml_young_limit@GOTPCREL(%rip), %rax >>> cmpq (%rax), %r15 >>> jb L222 >>> leaq 8(%r15), %rsi >>> movq $1277, -8(%rsi) >>> .loc 1 38 14 >>> movsd -4(%rbx,%rdx,4), %xmm0 >>> movsd %xmm0, (%rsi) >>> movq %rsi, 24(%rsp) >>> L218: >>> movq %rdi, 32(%rsp) >>> .file 5 "pervasives.ml" >>> .loc 5 65 17 >>> movq _caml_greaterequal@GOTPCREL(%rip), %rax >>> call _caml_c_call >>> L213: >>> movq _caml_young_ptr@GOTPCREL(%rip), %r11 >>> movq (%r11), %r15 >>> cmpq $1, %rax >>> je L217 >>> movq 32(%rsp), %rdi >>> jmp L216 >>> .align 2 >>> L217: >>> movq 24(%rsp), %rdi >>> L216: >>> movq 8(%rsp), %rdx >>> movq %rdx, %rax >>> addq $2, %rdx >>> movq %rdx, 8(%rsp) >>> movq 16(%rsp), %rbx >>> cmpq %rbx, %rax >>> jne L215 >>> >>> >>> The assembly for the more carefully writting case is below. No >>> allocation. No call to external C code. No test/branch for array >>> tag. This matches what I think most people would like to see. It is >>> compact enough that (maybe) it would benefit from unrolling: >>> >>> l225: >>> .loc 1 46 14 >>> movsd -4(%rax,%rdi,4), %xmm1 >>> comisd %xmm1, %xmm0 >>> jbe l227 >>> jmp l226 >>> .align 2 >>> l227: >>> movapd %xmm1, %xmm0 >>> l226: >>> movq %rdi, %rsi >>> addq $2, %rdi >>> cmpq %rbx, %rsi >>> jne l225 >>> >>> >>> The two main learnings we found were: >>> >>> * Polymorphic primitives ([Array.get], [compare], [>=], [min]) are >>> only specialized if they appear in a context where the types can be >>> determined at their exact call site, otherwise a polymorphic >>> version is used. If the use of the primitive is later inlined in a >>> context where the type is no longer polymorphic, the function will >>> _not_ be specialized by the compiler. >>> >>> * Use of abstract data types prevents specialization. In particular, >>> defining an abstract data type in a module ("type t ;;") will >>> prevent specialization (even after inlining) for any polymorphic >>> primitives (eg, "caml_equal") used with that type. For instance, >>> if the underlying type for [t] is actually [int], other modules >>> will still use polymorphic equality instead of a single machine >>> instruction. You can prevent this behavior with the "private" >>> keyword in order to export the type information, "type t = private >>> int". Alternatively, the module can include its own specialized >>> operations and other modules can be careful to use them. >>> >>> It bears emphasizing that the issues described in this note apply >>> even when all of the code is "fully inlined" and uses highest level >>> of optimization. Specialization in the Ocaml compiler occurs in a >>> stage prior to inlining. If it hasn’t happened before inlining, it >>> won’t happen afterwards. >>> >>> What kind of effect does lack of specialization have on performance? >>> Calling the "caml_compare" Ocaml C runtime function to compare >>> integers can be 10-20x times slower than using a single integer >>> comparison machine instruction. Ditto for floating point values. >>> The unspecialized [Array.get], [Array.set], and (on 32-bit) >>> [Array.length] have to check the tag on the array to determine if the >>> array uses the unboxed floating-point represntation (I wish Ocaml >>> didn't use this!). For instance, the polymorphic [Array.get] checks >>> the tag on the array and (for floating point arrays) reads the value >>> and boxes the floating point value (ie, allocate 2-3 words on the >>> heap). Note that when iterating over an array, the check on the tag >>> will be included in _each_ loop iteration. >>> >>> Other impacts of using non-specialized functions: >>> >>> * Use of polymorphic primitives means floating point values have to >>> be boxed, requiring heap allocation. Through use of specialized >>> specialized primitives, in many cases floats can remain unboxed. >>> >>> * All the extra native code from using polymorphic primitives >>> (checking array tags, conditionally boxing floats, calling out to >>> Ocaml C runtime) can have follow-on effects for further inlining. >>> In other words, when native code can be kept compact, then more >>> code can be inlined and/or loops unrolled and this can in turn >>> allow further optimization. >>> >>> Some suggestions others may find helpful: >>> >>> * Consider using the "private" keyword for any abstract types in your >>> modules. We added over 50 of these to our code base. It is an >>> ugly but effective work-around. >>> >>> * The min/max functions in standard library Pervasives are >>> particularly problematic. They are polymorphic so their comparison >>> will never be specialized. It can be helpful to define specialized >>> functions such as: >>> >>> let [@inline] float_max (v0:float) (v1:float) = >>> if v0 > v1 then v0 else v1 >>> ;; >>> >>> let [@inline] int_max (v0:int) (v1:int) = >>> if v0 > v1 then v0 else v1 >>> ;; >>> >>> These will be compiled to use native machine code and unboxed >>> values. >>> >>> * Any use of polymorphism can negatively affect performance. Be >>> careful about inadvertently introducing polymorphism into your >>> program, such as this helper function: >>> >>> let [@inline] getter v ofs = Array.get v ofs ;; >>> >>> This will result in unspecialized version of [Array.get] being >>> inlined at all call-sites. Note that if your .mli file defines the >>> function as non-polymorphic that will still _not_ affect how >>> [getter] is compiled.: >>> >>> type getter : t -> int -> int ;; (* does not affect optimization *) >>> >>> You must cast the type in the implementation in order for [Array.get] >>> to be specialized: >>> >>> let [@inline] getter (v:int array) ofs = Array.get v ofs ;; >>> >>> * All the iterators in the Array module (eg, [Array.iter]) in the >>> standard library are polymorphic, so will use unspecialized >>> accessors and be affected by the issues described here. Using the >>> following to sum and array of floats may seem elegant: >>> >>> Array.fold_left (+) 0.0 arr >>> >>> However, the resulting code is much slower (and allocates 2 floats >>> per array entry, ie 4-6 words) than a "specialized" version. Note >>> that even if [Array.fold_left] and surrounding code were "fully >>> inlined," it is still a polymorphic function so the above >>> performance penalty for checking the array tag and boxing the float >>> is present. See also the earlier example. >>> >>> * It can be helpful to review the compiled assembly code (using "-S" >>> option for ocamlopt) and look for tell-tale signs of lack of >>> specialization, such as calls to [_caml_greaterequal] or allocation >>> [caml_call_gc] in cases where they are not expected. You can refer >>> to the assembly code for the original implementation, know that >>> that code will not be specialized when inlined. >>> >>> As I said, by examining our hot spots and following the suggestions >>> above, we found the resulting native code could be comparable to what >>> we would expect from C. It is unfortunate these issues were >>> (apparently) designed into the Ocaml compiler architecture, because >>> otherwise it would have seemed this would be a natural area of >>> improvement for the compiler. I would have thought a staticly typed >>> language such as Ocaml would (through its type checker) be >>> well-suited for the simple types of function specialization described >>> in this note. >>> >>> >>> -- >>> Caml-list mailing list. Subscription management and archives: >>> https://sympa.inria.fr/sympa/arc/caml-list >>> Beginner's list: http://groups.yahoo.com/group/ocaml_beginners >>> Bug reports: http://caml.inria.fr/bin/caml-bugs > ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-19 22:30 ` Yaron Minsky @ 2017-01-22 20:06 ` Berke Durak 2017-01-23 16:33 ` David McClain 0 siblings, 1 reply; 14+ messages in thread From: Berke Durak @ 2017-01-22 20:06 UTC (permalink / raw) To: caml-list [-- Attachment #1: Type: text/plain, Size: 9714 bytes --] [Re-sending to list because of size limit] Of course the same kind of issues apply to Bigarray values. A polymorphic getter: let get a i = a.{i} will have pretty bad performance, unless "a" is annotated with the Bigarray kind and layout. Yesterday I rewrote some numerical double-integration inner loop in Fortran. One of the loops looks like this: do ui = 1,n u = real(ui - 1) / real(n - 1) do vi = 1,ui v = real(vi - 1) / real(n - 1) p = p1 + u*p12 + v*p13 r = norm(s - p) if (r > epsilon) then q = qs(1)*(1 - u - v) + qs(2)*u + qs(3)*v z = z + q/r end if end do end do I was half-disappointed, half pleasantly surprised when I noticed that it only got about 3 times faster than the OCaml version (with gfortran 6.3.0 and -O3 -fcheck-bounds -ffast-math). Granted the OCaml code is similar written in a mostly imperative style with Bigarrays and references, but it's using a function passed to a domain iterator instead of having two nested identical loops. This is with 4.05+pr985+flambda. I examined the Fortran assembly code, and while it looks numerically dense, it looks like gfortran ended up calling its internal pack/unpack primitives: mulsd %xmm1, %xmm2 # v, D.4022 movsd %xmm0, 168(%rsp) # D.4022, A.12 movsd 16(%r15), %xmm0 # *s_110(D), *s_110(D) subsd 88(%rsp), %xmm0 # %sfp, D.4022 subsd 32(%rsp), %xmm0 # %sfp, D.4022 subsd %xmm2, %xmm0 # D.4022, D.4022 movsd %xmm0, 176(%rsp) # D.4022, A.12 call _gfortran_internal_pack # movsd (%rax), %xmm2 # MEM[(real(kind=8)[3] *)_117], D.4022 cmpq %r12, %rax # tmp266, D.4025 movsd 8(%rax), %xmm3 # MEM[(real(kind=8)[3] *)_117], D.4022 movq %rax, %rbx #, D.4025 mulsd %xmm2, %xmm2 # D.4022, D.4022 mulsd %xmm3, %xmm3 # D.4022, D.4022 movsd 16(%rax), %xmm0 # MEM[(real(kind=8)[3] *)_117], D.4022 movsd (%rsp), %xmm1 # %sfp, v mulsd %xmm0, %xmm0 # D.4022, D.4022 addsd %xmm3, %xmm2 # D.4022, D.4022 addsd %xmm2, %xmm0 # D.4022, D.4022 sqrtsd %xmm0, %xmm0 # D.4022, D.4022 je .L4 #, leaq 192(%rsp), %rdi #, tmp328 movq %rax, %rsi # D.4025, movsd %xmm0, 8(%rsp) # D.4022, %sfp call _gfortran_internal_unpack # I'm new at using Fortran, so maybe there are a few simple things to make the code faster. I suspect these calls are due to the vector operations, such as the call to norm(u) and the vector substraction, in spite of norm() being defined in the same Fortran module and is inlined. (Note that pack/unpack aren't that expensive.) My point in describing all this is that if some of the pitfalls described are avoided, OCaml is not bad for numerical code if you compare it to "unoptimized" Fortran code. Getting the "magical optimization" from Fortran compilers (auto-vectorization, or auto-parallelization as provided by PGI Fortran) is neither automatic nor easy. Now a lot of scientists are stuck with Matlab, and the newer generation tends to use Python with Numpy. Assuming the required matrix/vector operations are available in OCaml libraries Lacaml, Fftw, etc. we OCaml programmers will find Python + Numpy to be inferior to OCaml because Python is an inferior language. The benefit of Python is that it's easier to "just get started" since "types won't get in the way", but then it's not any better than Matlab (besides the price tag). And yes, Python is a better language than Matlab. (Octave and INRIA's Scilab seem to be slightly better language-wise.) But for writing a non-temporary numerical routine Ocaml is superior since you can produce a type-checked, fast standalone executable efficiently thanks to the high-level programming offered. People dissatisfied with Python's performance often rave about Cython and how wonderful it is. This thing generates C code from type-annotated Python code. Examining the generated C and then assembly code from the heat.pyx examples, the code (with bounds checks disabled) doesn't look glorious. The Cython code looks like this: @cython.boundscheck(False) def solve_heat_buf_nocheck(initial_conditions, double dx, double dt, int iter): cdef numpy.ndarray[double, ndim=2] cur = initial_conditions.copy() cdef numpy.ndarray[double, ndim=2] next = numpy.zeros_like(initial_conditions) cdef int count, i, j, M, N M, N = cur.shape[0], cur.shape[1] cdef double step for count in range(iter): for i in range(1, M-1): for j in range(1, N-1): step = cur[i-1,j] + cur[i+1,j] + cur[i,j-1] + cur[i,j+1] - 4*cur[i,j] next[i,j] = cur[i,j] + dt*step/dx**2 cur, next = next, cur return cur This, with two other Python functions of similar size, generates about 8000 lines of C code. The actual loop is compiled into something that looks like this... if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_pybuffernd_cur.diminfo[0].shape; if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_pybuffernd_cur.diminfo[1].shape; __pyx_v_step = (((((*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_cur.rcbuffer->pybuffer.buf, __pyx_t_15, __pyx_pybuffernd_cur.diminfo[0].strides, __pyx_t_16, __pyx_pybuffernd_cur.diminfo[1].strides)) + (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_cur.rcbuffer->pybuffer.buf, __pyx_t_17, __pyx_pybuffernd_cur.diminfo[0].strides, __pyx_t_18, __pyx_pybuffernd_cur.diminfo[1].strides))) + (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_cur.rcbuffer->pybuffer.buf, __pyx_t_19, __pyx_pybuffernd_cur.diminfo[0].strides, __pyx_t_20, __pyx_pybuffernd_cur.diminfo[1].strides))) + (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_cur.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_cur.diminfo[0].strides, __pyx_t_22, __pyx_pybuffernd_cur.diminfo[1].strides))) - (4.0 * (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_cur.rcbuffer->pybuffer.buf, __pyx_t_23, __pyx_pybuffernd_cur.diminfo[0].strides, __pyx_t_24, __pyx_pybuffernd_cur.diminfo[1].strides)))); ...repeated a hundred times. I pasted the excerpt at https://gist.github.com/anonymous/e54964121b212e5f783fb10c696ed9e2 This comes with an incredible amount of wrapper code for checking types and recursion limits. Regarding the float array issue, I have these two thoughts: 1) Why not just completely drop the float *array* optimization? If you're writing numerical code, use bigarrays. Those are optimized. I rarely use float arrays. 2) However, I often use structures and tuples of floats (e.g. type vec3 = float * float * float or type vec3 = { x : float; y : float; z : float }). Having the floats in structures/tuples be boxed would be very annoying. I'm not sure (1) and (2) interact. 3) What about 63-bit floats? This would be tricky and non-compliant, but someone had already made the suggestion here: http://blog.frama-c.com/index.php?post/2013/05/09/A-63-bit-floating-point-type-for-64-bit-OCaml These could be provided as a separate type. 4) Same thing for single-precision floats (i.e. actual C floats.) On 64-bit machines these would fit with no problems in a 64-bit word. Wasteful, but fast. 5) The really important issue may be float boxing/unboxing when passed to functions. Consider: let accu_over_range i1 i2 f q0 = let rec loop i q = if i > i2 then q else loop (i + 1) (f q i) in loop i1 q0 let _ = Printf.printf "%g\n" (accu_over_range 1 100_000_000 (fun q i -> q +. float i *. float i) 0.0) The inner loop translates into this (with the same 4.05+pr485+flambda) camlFloataccu__loop_133: subq $8, %rsp .L113: movq %rax, %rdi cmpq $200000001, %rdi jle .L112 movq %rbx, %rax addq $8, %rsp ret .L112: .L114: subq $16, %r15 movq caml_young_limit@GOTPCREL(%rip), %rax cmpq (%rax), %r15 jb .L115 leaq 8(%r15), %rsi movq $1277, -8(%rsi) movq %rdi, %rax sarq $1, %rax cvtsi2sdq %rax, %xmm0 movapd %xmm0, %xmm1 mulsd %xmm0, %xmm1 addsd (%rbx), %xmm1 movsd %xmm1, (%rsi) movq %rdi, %rax addq $2, %rax movq %rsi, %rbx jmp .L113 .L115: call caml_call_gc@PLT .L116: jmp .L114 And we see that floats are boxed. Type annotation doesn't help. I did quickly try a few Flambda options such as: ocamlopt -O3 floataccu-anno.ml -unbox-closures -rounds=10 -inline-call-cost=1000 -inlining-report but that didn't change anything. Maybe there is a way? Note that Fortran 2008 currently has "inner functions" which can be defined locally and passed to subroutines. They do capture variables, but the catch is that they are limited to one nesting level. Also some compilers (eg. PGI Fortran) don't support them yet. See: http://www.fortran90.org/src/faq.html#does-fortran-support-closures My point is that efficient calls with float arguments are much more important than this issue. Having to add a few type annotations to avoid polymorphic code is inconvenient, but not being able to use functions efficiently (the fundamental construct!) is a roadblock. 6) For records containing a few floats, there is the Mlton approach of laying out all unboxed fields before boxed ones, however as long as all-float structures are unboxed, this can be worked around by having the used manually place all these fields in a sub-record. -- Berke Durak, VA7OBD (CN88) [-- Attachment #2: Type: text/html, Size: 11256 bytes --] ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] Ocaml optimizer pitfalls & work-arounds 2017-01-22 20:06 ` Berke Durak @ 2017-01-23 16:33 ` David McClain 0 siblings, 0 replies; 14+ messages in thread From: David McClain @ 2017-01-23 16:33 UTC (permalink / raw) To: caml-list [-- Attachment #1: Type: text/plain, Size: 1045 bytes --] > On Jan 22, 2017, at 13:06, Berke Durak <berke.durak@gmail.com <mailto:berke.durak@gmail.com>> wrote: > > > But for writing a non-temporary numerical routine Ocaml is superior since you can produce a type-checked, fast standalone executable efficiently thanks to the high-level programming offered. This was the conclusion I reached almost 16-17 years ago while working on solving for optical train aberrations from point spread images. At that time we were stuck with RSI/IDL (a variant of Matlab, of sorts), and could not get past 5 or 6 degrees of freedom without havoc striking. We needed 150+ DOF. So I sat down and learned about this new world of FPL and developed a tensor based optimization that worked the first time - once I finally got it all to compile. It wasn’t a huge body of code, perhaps 2-3 KLOC. But my experience was so incredible that I wrote a short paper for Phil Wadler in the ACM proceedings. Couldn’t have come at this from a more distant place - astrophysics and missile borne IR sensors. - DM [-- Attachment #2: Type: text/html, Size: 1721 bytes --] ^ permalink raw reply [flat|nested] 14+ messages in thread
* Re: [Caml-list] <DKIM> Ocaml optimizer pitfalls & work-arounds 2017-01-19 6:51 [Caml-list] Ocaml optimizer pitfalls & work-arounds Mark Hayden 2017-01-19 11:20 ` Nils Becker 2017-01-19 13:41 ` Yaron Minsky @ 2017-01-21 14:39 ` Pierre Chambart 2 siblings, 0 replies; 14+ messages in thread From: Pierre Chambart @ 2017-01-21 14:39 UTC (permalink / raw) To: Mark Hayden, caml-list I'm coming a bit late to the discussion to tell you that this is not completely hopeless. Xavier Leroy was right by telling you that the (mid/back)-end of the compiler is untyped and that this hinder this kind of optimization. But it is not completely impossible. I've recently being working on some more aggressive unboxing which requires propagating some more type information. I took the opportunity to specialize a few more primitive in flambda. It appears that not so much more type annotations are required to be propagated through the intermediate representations to be able to improve something like: [Array.fold_left max 0.0 arr] When translating from the typedtree to Lambda, the application arguments can be annotated with the kind of values they carry. Here the important information is that [arr] is a float array. When fold left is inlined that information can be propagated to its uses. I have some tests showing good results on this. Notice that this is still quite limited. Type propagation on later representations can only follow values and flow forward. This is mainly due to GADTs. For instance type 'a t = Float : float t | Int : int t type ('a, 'b) eq = Eq : ('a, 'a) eq let f (type x) (t : x t) (v : x) (a : x array) (cast : x t -> (x, float) eq) = a.(0) <- v; let Eq = cast t in v +. 3.14 (function t/1019 v/1020 a/1021 cast/1022 (seq (array.set a/1021 0 v/1020) (let (match/1028 = (apply cast/1022 t/1019)) (+. v/1020 3.14))))) Here, for instance, the type of the argument v cannot be deduced from the (+.) operation, and specializing the array assignment using it would lead to segfaults. -- Pierre Chambart Le 19/01/2017 à 07:51, Mark Hayden a écrit : > We recently upgraded our Ocaml toolchain from 4.02.3 to Ocaml 4.04.0. > We were looking forward to a performance boost from the optimization > improvements, especially from flambda. While we generally were able > to achieve significant performance improvement, we were somewhat > surprised by the effort required to avoid certain pitfalls in Ocaml. > > This note describes some issues we ran into. We filed several > reports on Ocaml Mantis regarding our findings. However it appears > the underlying issues we ran into are unlikely to change: > > Your three reports (0007440, 0007441, 0007442) are manifestations > of the same fact: the OCaml compiler performs type-based > optimizations first, then erases types, then performs all the other > optimizations. This is very unlikely to change in the near future, > as it would require a total rewrite of the compiler. > > [X Leroy, https://caml.inria.fr/mantis/view.php?id=7440] > > I encourage readers to review the problem reports we submitted, which > include more concrete examples. I'm posting this note in case there > are others running into similar performance issues with their Ocaml > software and who might find it helpful in working around those > issues. I'm not aware of them being documented elsewhere and there > appears to be little prospect of the issues being addressed in the > compiler in the forseeable future. Please chime in if any of this is > inaccurate or there is something I missed. > > As an initial example, consider the following Ocaml code to find the > maximum floating point value in an array (that is at least 0.0): > > [Array.fold_left max 0.0 arr] > > Now compile this with the latest compiler and maximum optimization. > Because of how the Ocaml optimization works, this will run about > 10-15x slower (and allocate 2-3 words per array element) than a more > carefully written version that uses specialized operations and avoids > allocation. See below for one way to achieve this (while still using > a functional-programming style). > > (* Same as Array.fold_left, but with type casting. > *) > let [@inline] array_fold_leftf f (x:float) (a:float array) = > let r = ref x in > for i = 0 to Array.length a - 1 do > r := f !r (Array.unsafe_get a i) > done; > !r > ;; > > let [@inline] float_max (v0:float) v1 = > if v0 > v1 then v0 else v1 > ;; > > let array_float_max a = > array_fold_leftf float_max 0.0 a > ;; > > The assembly for the "inner loop" for the two examples are below. > They were compiled with Ocaml 4.05.dev+flambda, "-O3 > -unbox-closures", MacOS 12.2, AMD64. > > Unoptimized example. Note test/branch for array tag. Allocation for > boxing (we did not include the calls to trigger a minor gc). There > is a call to Ocaml runtime for polymorphic greater-equal. This is > probably not what one would expect from an optimizing/inline compiler > for a simple case such as this. Note that to create this we used our > own definition of Array.fold_left which had an "[@inline]" > annotation. > > L215: > movq (%rsp), %rbx > .loc 1 38 14 > movzbq -8(%rbx), %rax > cmpq $254, %rax > je L219 > .loc 1 38 14 > movq -4(%rbx,%rdx,4), %rsi > movq %rsi, 24(%rsp) > jmp L218 > .align 2 > L219: > .loc 1 38 14 > L221: > subq $16, %r15 > movq _caml_young_limit@GOTPCREL(%rip), %rax > cmpq (%rax), %r15 > jb L222 > leaq 8(%r15), %rsi > movq $1277, -8(%rsi) > .loc 1 38 14 > movsd -4(%rbx,%rdx,4), %xmm0 > movsd %xmm0, (%rsi) > movq %rsi, 24(%rsp) > L218: > movq %rdi, 32(%rsp) > .file 5 "pervasives.ml" > .loc 5 65 17 > movq _caml_greaterequal@GOTPCREL(%rip), %rax > call _caml_c_call > L213: > movq _caml_young_ptr@GOTPCREL(%rip), %r11 > movq (%r11), %r15 > cmpq $1, %rax > je L217 > movq 32(%rsp), %rdi > jmp L216 > .align 2 > L217: > movq 24(%rsp), %rdi > L216: > movq 8(%rsp), %rdx > movq %rdx, %rax > addq $2, %rdx > movq %rdx, 8(%rsp) > movq 16(%rsp), %rbx > cmpq %rbx, %rax > jne L215 > > > The assembly for the more carefully writting case is below. No > allocation. No call to external C code. No test/branch for array > tag. This matches what I think most people would like to see. It is > compact enough that (maybe) it would benefit from unrolling: > > l225: > .loc 1 46 14 > movsd -4(%rax,%rdi,4), %xmm1 > comisd %xmm1, %xmm0 > jbe l227 > jmp l226 > .align 2 > l227: > movapd %xmm1, %xmm0 > l226: > movq %rdi, %rsi > addq $2, %rdi > cmpq %rbx, %rsi > jne l225 > > > The two main learnings we found were: > > * Polymorphic primitives ([Array.get], [compare], [>=], [min]) are > only specialized if they appear in a context where the types can be > determined at their exact call site, otherwise a polymorphic > version is used. If the use of the primitive is later inlined in a > context where the type is no longer polymorphic, the function will > _not_ be specialized by the compiler. > > * Use of abstract data types prevents specialization. In particular, > defining an abstract data type in a module ("type t ;;") will > prevent specialization (even after inlining) for any polymorphic > primitives (eg, "caml_equal") used with that type. For instance, > if the underlying type for [t] is actually [int], other modules > will still use polymorphic equality instead of a single machine > instruction. You can prevent this behavior with the "private" > keyword in order to export the type information, "type t = private > int". Alternatively, the module can include its own specialized > operations and other modules can be careful to use them. > > It bears emphasizing that the issues described in this note apply > even when all of the code is "fully inlined" and uses highest level > of optimization. Specialization in the Ocaml compiler occurs in a > stage prior to inlining. If it hasn’t happened before inlining, it > won’t happen afterwards. > > What kind of effect does lack of specialization have on performance? > Calling the "caml_compare" Ocaml C runtime function to compare > integers can be 10-20x times slower than using a single integer > comparison machine instruction. Ditto for floating point values. > The unspecialized [Array.get], [Array.set], and (on 32-bit) > [Array.length] have to check the tag on the array to determine if the > array uses the unboxed floating-point represntation (I wish Ocaml > didn't use this!). For instance, the polymorphic [Array.get] checks > the tag on the array and (for floating point arrays) reads the value > and boxes the floating point value (ie, allocate 2-3 words on the > heap). Note that when iterating over an array, the check on the tag > will be included in _each_ loop iteration. > > Other impacts of using non-specialized functions: > > * Use of polymorphic primitives means floating point values have to > be boxed, requiring heap allocation. Through use of specialized > specialized primitives, in many cases floats can remain unboxed. > > * All the extra native code from using polymorphic primitives > (checking array tags, conditionally boxing floats, calling out to > Ocaml C runtime) can have follow-on effects for further inlining. > In other words, when native code can be kept compact, then more > code can be inlined and/or loops unrolled and this can in turn > allow further optimization. > > Some suggestions others may find helpful: > > * Consider using the "private" keyword for any abstract types in your > modules. We added over 50 of these to our code base. It is an > ugly but effective work-around. > > * The min/max functions in standard library Pervasives are > particularly problematic. They are polymorphic so their comparison > will never be specialized. It can be helpful to define specialized > functions such as: > > let [@inline] float_max (v0:float) (v1:float) = > if v0 > v1 then v0 else v1 > ;; > > let [@inline] int_max (v0:int) (v1:int) = > if v0 > v1 then v0 else v1 > ;; > > These will be compiled to use native machine code and unboxed > values. > > * Any use of polymorphism can negatively affect performance. Be > careful about inadvertently introducing polymorphism into your > program, such as this helper function: > > let [@inline] getter v ofs = Array.get v ofs ;; > > This will result in unspecialized version of [Array.get] being > inlined at all call-sites. Note that if your .mli file defines the > function as non-polymorphic that will still _not_ affect how > [getter] is compiled.: > > type getter : t -> int -> int ;; (* does not affect optimization *) > > You must cast the type in the implementation in order for [Array.get] > to be specialized: > > let [@inline] getter (v:int array) ofs = Array.get v ofs ;; > > * All the iterators in the Array module (eg, [Array.iter]) in the > standard library are polymorphic, so will use unspecialized > accessors and be affected by the issues described here. Using the > following to sum and array of floats may seem elegant: > > Array.fold_left (+) 0.0 arr > > However, the resulting code is much slower (and allocates 2 floats > per array entry, ie 4-6 words) than a "specialized" version. Note > that even if [Array.fold_left] and surrounding code were "fully > inlined," it is still a polymorphic function so the above > performance penalty for checking the array tag and boxing the float > is present. See also the earlier example. > > * It can be helpful to review the compiled assembly code (using "-S" > option for ocamlopt) and look for tell-tale signs of lack of > specialization, such as calls to [_caml_greaterequal] or allocation > [caml_call_gc] in cases where they are not expected. You can refer > to the assembly code for the original implementation, know that > that code will not be specialized when inlined. > > As I said, by examining our hot spots and following the suggestions > above, we found the resulting native code could be comparable to what > we would expect from C. It is unfortunate these issues were > (apparently) designed into the Ocaml compiler architecture, because > otherwise it would have seemed this would be a natural area of > improvement for the compiler. I would have thought a staticly typed > language such as Ocaml would (through its type checker) be > well-suited for the simple types of function specialization described > in this note. > > ^ permalink raw reply [flat|nested] 14+ messages in thread
end of thread, other threads:[~2017-01-23 16:34 UTC | newest] Thread overview: 14+ messages (download: mbox.gz / follow: Atom feed) -- links below jump to the message on this page -- 2017-01-19 6:51 [Caml-list] Ocaml optimizer pitfalls & work-arounds Mark Hayden 2017-01-19 11:20 ` Nils Becker 2017-01-19 11:39 ` Gabriel Scherer 2017-01-19 13:26 ` Frédéric Bour 2017-01-19 14:35 ` Alain Frisch 2017-01-19 15:35 ` Ivan Gotovchits 2017-01-19 17:02 ` Hezekiah M. Carty 2017-01-19 15:41 ` Gerd Stolpmann 2017-01-19 13:41 ` Yaron Minsky 2017-01-19 17:59 ` Mark Hayden 2017-01-19 22:30 ` Yaron Minsky 2017-01-22 20:06 ` Berke Durak 2017-01-23 16:33 ` David McClain 2017-01-21 14:39 ` [Caml-list] <DKIM> " Pierre Chambart
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