Modern C++ and Lisp Programming Style
chriskohlhepp.wordpress.com
chriskohlhepp.wordpress.com
auto addone = [](auto x) { return x+1; };
That monstrosity at the top of the article is needlessly complex because C++11 didn't support generic lamdbas. addone1(x) = x+1
Completely generic with type inference, and compiles to optimal machine code. But it also suffers from the "latent type errors deferred to the user" that the article discusses. Calling it with a type that does not support adding 1 will raise an error for a non-existing "+" method: addone1("0")
ERROR: MethodError: no method matching +(::String, ::Int64)
This is pretty understandable in this case, but we may prefer annotating the addone function so that it can only be called with types that support adding 1. Using the (very conservative) notion that only numbers can have 1 added to them, we could use Julia's type hierarchy to restrict the types for which addone may be called: addone2(x::T) where T<:Number = x+1
Calling it with an incompatible type now properly points to the outer level: addone2("0")
ERROR: MethodError: no method matching addone2(::String)
But this type of dispatch restrictions rely on a type hierarchy, causing similar problems as class hierarchies in OO languages. For example, the user might have defined their own type that supports addition but not multiplication. Using addone on this type makes sense, but the type shouldn't be a subtype of Number. Such more flexible dispatch scenarios can be achieved with traits. Although Julia currently doesn't have direct language support for traits, they can be implemented inside the language, with macros for syntactic sugar. With traits, the previous example becomes: using SimpleTraits
@traitdef CanAddOne{T}
@traitimpl CanAddOne{T} <- issubtype(T,Number)
@traitfn addone3{T; CanAddOne{T}}(x::T) = x+1
Still relatively straight-forward to write and read, and the trait-restricted addone has the same performance as the original one. For incompatible types, the error message still points to the outer level: addone3("0")
ERROR: MethodError: no method matching addone3(::Type{SimpleTraits.Not{CanAddOne{String}}}, ::String)
Importantly, the user can extend the CanAddOne trait (with additional @traitimpl lines) to cover their own type, without being forced to make it a subtype of Number. add1 = (+1)
> add1 23
24
> add1 2.01
3.01
> add1 "0"
No instance found...
But that error is at compile time.add1 =: >:
add1 1r3
4r3
add1 0 1My Haskell is very rusty, but IIRC it will deduce that the argument to add1 must be Num, because of the type constraint on (+):
(+) :: Num a => a -> a -> a
So if I'm not mistaken, your add1 is equivalent to my addone2, i.e. incorporating a type constraint based on the type hierarchy. I'm curious: what's the equivalent of my addone3 in Haskell? How would you define add1 so that it also works on a type T later defined by the user, with T just supporting addition but T not subtype of Num? Do you need to define your own addition function (acting as a proxy for (+) for Num types)?Haskell also provides a ton of options for generic programming that provide similar power (still statically typed). GADTs (Generalized Algebraic Data Types) might be of use here. There are also existential types and type classes.
What you probably really want though is a dependently typed language like Idris or Agda. If you're not familiar, here's the one liner: Java generics are types that depend on types (like a List of Bools). Dependent types are types that can depend on values (like a List of exactly 3 Bools). So in theory you should be able to define the type you're looking for here, but I don't know what the concrete syntax would be.
The problem with dependently typed languages right now is that the surface languages and concepts tend to be hard for people to grok. Personally I think meta-programming facilities and DSLs will help with this. Ther are lots of languages heading in that direction.
Working code poured out almost as fast as I can type.
If I had to think about some propeller-head academic dependent type nonsense, I'd still be writing it come March 2018.
> The problem with dependently typed languages right now is that the surface languages and concepts tend to be hard for people to grok.
Anything hard to grok is a regression in tooling.
Why would I want to grok something difficult, when I'm finding programming easy and don't have any issues with getting the desired behavior out of the machine.
All I want to be grokking is how the bits of the run-time representation in the machine are coming together to solve whatever is being solved.
If you're programming a single computer the existing languages and tooling are good. What I'm interested in is distributed compute and compute over heterogenous architectures (CPUs, GPUs, FPGAs, microcontrollers, etc).
For simplicity, let's limit ourselves to the simple case of HTTP-based service-oriented systems (or microservices). The state of the art has us spending a lot of time considering serialization, protocols, communication failures, managing identities, making authorization decisions, routing, etc. Things that should be completely orthogonal to the problem we're trying to solve end up being tightly coupled with our business logic. This becomes exponentially harder to manage as you add languages to your stack.
There is a lot of research around solving these problems. Unfortunately, all of it starts with a formal system that is "declarative" (or at least "algebraic") and doesn't mesh well with existing popular languages and tooling. Personally, I think we need to come up with a solution that lets us keep the existing tools that are good for programming a single component, and use some of this newer technology to build a smarter platform / underlay. The bridge between the existing languages and this underlay would be DSLs. Or, more precisely, "abstract languages" that can be implemented as DSLs in a variety of programming languages and may or may not have their own concrete syntax (think SQL+ORMs).
Sort of vague, I know, but hopefully that kind of makes sense?
My Lisp-fu isn't as strong as my C++-fu so someone correct me if I'm wrong but isn't the GC an intrinsic part of Lisp? Do more modern Lisps allow you to mark value types so you can control memory access patterns(which is where the true speed of C/C++ comes from).
Edit: looks like I misread what you were saying. Yeah, if you want to pack two things next to each other in memory, that might be tricky in the language defined in the ansi standard. Although I think some implementations give you control over this sort of thing.
https://www.pvk.ca/Blog/2014/03/15/sbcl-the-ultimate-assembl...
A really cool example of SB-ALIEN in action is jiyunomegami's native type extensions for the Vacietis C-to-CL transpiler: https://github.com/jiyunomegami/Vacietis/commits/master (commits 5504079d63eb2745f6b8ef7ec1cf9bb3151994eb onward)
This is LispWorks 64bit from http://lispworks.com . It uses a generational GC, and each generation has several memory segments. You can tell LispWorks how much generations it should use, how large these segments should be and in which generation/segment to allocate.
CL-USER 12 > (room t)
> Generation 7: 33904936 (0x2055928)
Cons 4774352 (0x48D9D0)
Non-Pointer 3213752 (0x3109B8)
Other 8048192 (0x7ACE40)
Symbol 2881680 (0x2BF890)
Function 14569120 (0xDE4EA0)
Non-Pointer-Static 5528 (0x1598)
Mixed-Static 411600 (0x647D0)
Weak 712 (0x2C8)
-- Segments:
Cons 40C0038800 - 40C04C9000
Non-Pointer 40D0000800 - 40D0314000
Other 40E0038800 - 40E07E8000
Symbol 40F0038800 - 40F02FB000
Function 4100038800 - 4100E20000
Non-Pointer-Static 40B0000800 - 40B000D000
Mixed-Static 400004E800 - 40000C8000
Weak 4110038800 - 4110039000
================================
> Generation 6: 0 (0x0)
> Generation 5: 0 (0x0)
> Generation 4: 0 (0x0)
> Generation 3: 206544 (0x326D0)
Non-Pointer 69648 (0x11010)
Other 5040 (0x13B0)
Symbol 131856 (0x20310)
-- Segments:
Non-Pointer 4070000800 - 4071001000
Other 4170018800 - 4171019000
Symbol 4080018800 - 4080819000
================================
> Generation 2: 8768024 (0x85CA18)
Cons 1960288 (0x1DE960)
Non-Pointer 2531584 (0x26A100)
Other 2720024 (0x298118)
Symbol 5088 (0x13E0)
Function 700184 (0xAAF18)
Non-Pointer-Static 850152 (0xCF8E8)
Mixed-Static 64 (0x40)
Weak 640 (0x280)
-- Segments:
Cons 41B0010800 - 41B1011000
Non-Pointer 4180000800 - 4181001000
Other 41C0010800 - 41C1011000
Symbol 41D0010800 - 41D0811000
Function 41E0010800 - 41E0811000
Non-Pointer-Static 4040000800 - 4040136000
Mixed-Static 4090010800 - 4090013000
Weak 41F0010800 - 41F0051000
================================
> Generation 1: 732480 (0xB2D40)
Cons 160240 (0x271F0)
Non-Pointer 170344 (0x29968)
Other 398200 (0x61378)
Function 3248 (0xCB0)
Weak 448 (0x1C0)
-- Segments:
Cons 4200008800 - 4200301000
Non-Pointer 4210000800 - 4210411000
Other 4220008800 - 42203F1000
Symbol 4230008800 - 423001B000
Function 4240008800 - 424003B000
Weak 4250008800 - 4250009000
================================
> Generation 0: 1956832 (0x1DDBE0)
Cons 630224 (0x99DD0)
Non-Pointer 361232 (0x58310)
Other 923816 (0xE18A8)
Function 41560 (0xA258)
-- Segments:
Cons 4010000800 - 401040B000
Non-Pointer 4030000800 - 403041B000
Other 4020000800 - 402040B000
Symbol 4150000800 - 4150101000
Function 4060000800 - 4060101000
Weak 4190000800 - 4190041000
================================
Total allocated 45568816 (0x2B75330), total size 178085888 (0xA9D6000)
NILArrays are also available, including specialized versions that hold value types.
https://www.cs.cmu.edu/Groups/AI/html/cltl/clm/node15.html
You can also stack allocate if required, via dynamic-extent, http://clhs.lisp.se/Body/d_dynami.htm
Also not all Lisps have a tracing GC, some variants had a RC with tracing GC for collecting cycles.
RAII like patterns can be achieved via the with-.... functions, or macros.
I don't know the actual performance of commercial Lisps like Allegro Common Lisp and LispWorks, but I imagine it is quite good, given that they stay in business.
On the other had, given the amount of money spent in C and C++ optimizers vs the lack of industry wide adoption of Lisp, probably still not as good as current leading C++ compilers.
It might be good or just OK on modern hardware. I imagine they stayed in business for their IDE's, libraries, commercial support, and decent compilers. Batteries included. Some success stories make me think performance is really good, though.
http://www.lispworks.com/success-stories/netfonds-primetrade...
http://www.lispworks.com/success-stories/ral-siglab.html
I found those while looking for one about a real-time implementation for telecom or something. Franz's success stories are mostly about doing complicated stuff easier. There was one that looked performance-critical:
http://franz.com/success/customer_apps/finance/ravenpack.lht...
In TXR Lisp, RAII is supported thusly:
This is GC finalization of a struct:
This is the TXR Lisp interactive listener of TXR 172.
Use the :quit command or type Ctrl-D on empty line to exit.
1> (defstruct animal nil
(:fini (me) (put-line `@me says good-bye`)))
#<struct-type animal>
2> (progn (new animal) nil) ;; make animal without referencing from REPL
nil
3> (+ 2 2)
4
4> (sys:gc)
#S(animal) says good-bye
t
OK, now with-objects macro: 5> (with-objects ((a (new animal)))
(prinl a))
#S(animal)
#S(animal) says good-bye
#S(animal)
with-objects invokes finalizers explicitly, before objects become unreachable.Also, what if a constructor throws? Let's derive animal to dog which bails at `new` time:
6> (defstruct dog animal
(:fini (me) (put-line `@me: woof woof`))
(:postinit (me) (error "refuse to construct")))
#<struct-type dog>
7> (new dog)
#S(dog): woof woof
#S(dog) says good-bye
** refuse to construct
** during evaluation at expr-6:3 of form (error "refuse to construct")
The object instantiation logic catches exceptions and invokes finalizers on a partially constructed object (in the proper order as you can see: derived, then base).Neither the gc-based nor with-* based solutions handle that.
Somewhere in the whole workflow there must be a class allocated in the stack.
You can have destructor like behavior in Lisp as well, just register a file handle cleanup action by giving a cleanup lambda when creating the map instance.
The function that removes entries from the map will call the provided lambda.
Of course instances of classes (not "classes", as you say, classes are an entirely compile-time construct in C++) must be allocated, but I mean... there's still heap storage. You know, shared_ptr<T> and all that...
What am I missing?
> You can have destructor like behavior in Lisp as well, just register a file handle cleanup action by giving a cleanup lambda when creating the map instance.
Well, except you don't know exactly when the map is going to get cleaned up...? And it could get reused across various sections of the program... Do you see what I'm talking about?
EDIT: That, and if the map exists for the entire duration of the program, but it's really important that entries have prompt cleanup when removed... what then?
(Btw, I do understand that in the general case with weak_ptr, shared_ptr, unique_ptr, etc. that things get decidedly less deterministic[1], but RAII is pretty well defined by scope or referenced-to-scope.)
[1] Basically almost as unpredictable as a general purpose GC. I can't recall the paper title, but I'm sure there is a paper out there detailing this.
This is the TXR Lisp interactive listener of TXR 173.
Use the :quit command or type Ctrl-D on empty line to exit.
1> (defstruct map nil
(hash (hash :equal-based))
(:method lambda (me key) (gethash me.hash key))
(:method lambda-set (me key new-val)
(let ((old-val (shift (gethash me.hash key) new-val)))
(call-finalizers old-val)
new-val))
(:fini (me)
(dohash (key val me.hash)
(call-finalizers key)
(call-finalizers val))))
#<struct-type map>
2> (defstruct widget nil
id
(:static counter 0)
(:init (me) (set me.id (inc me.counter)))
(:fini (me) (put-line `widget @{me.id} says bye`)))
#<struct-type widget>
3> (defvar map (new map))
map
4> (set [map "a"] (new widget))
#S(widget id 1)
5> (set [map "a"] (new widget))
widget 1 says bye
#S(widget id 2)
6> (set [map "a"] (new widget))
widget 2 says bye
#S(widget id 3)
7> (set [map "b"] (new widget))
#S(widget id 4)
8> (set [map "c"] (new widget))
#S(widget id 5)
9> (call-finalizers map)
widget 3 says bye
widget 4 says bye
widget 5 says bye
10> (with-objects ((m (new map)))
(set [m "x"] (new widget))
(set [m "y"] (new widget)))
widget 6 says bye
widget 7 says bye
#S(widget id 7)Secondly, doing RAII into and out of a map container is largely a poor idea, and C++ programmers expend energy fighting it.
The assignment operation and constructors and destructors of the map element all have lexical scopes somewhere.
Please explain your example further then, because I don't see it.
> Secondly, doing RAII into and out of a map container is largely a poor idea, and C++ programmers expend energy fighting it.
Again, explain, please. Why is it a "poor idea"? Any links, at least? "Fighting it"... how, exactly?
(It's been a while since I was a professional C++ programmer, but I don't really recognize this characterization.)
> The assignment operation and constructors and destructors of the map element all have lexical scopes somewhere.
Well, yes, but what about the MAP itself? It could easily be heap allocated.
I'm sorry, I just don't see what you're on about.
{
map<whatever> *ptr = new map<whatever> ;
// forgotten delete
}
If you don't want the heap allocated map to leak, and you want that management to be automated, you need some smart pointer type to reference it; map itself doesn't help.All RAII-driven management of heap resources is tied to some scope somewhere. Anything not tied to scoping has to be treated explicitly: try to calculate the lifetime and explicitly dispose of the resource.
Performance is not one easy number. Applications have different performance requirements. In many benchmarks for typed or type inferred code SBCL tends to be slightly faster with less programming effort.
Fast can mean for example:
* fastest possible execution of optimized code
Then one might not care about code size, code safety, robustness, threading capability, interrupts, .
* fast execution of non-optimized robust, flexible, reflective, debuggable code.
Allegro CL and LispWorks integrate a lot of features. These features are provided over some amount of platforms, with only few restrictions. They provide relatively good performance of a native code compiler. Some robustness is needed for commercial applications, thus I would expect an advantage there.
On the other hand, the default in Lisp is always to let the compiler handle memory, but Common Lisp in particular gives the programmer a lot of flexibility and control over types, memory management, and other optimizations. It's been fighting the "Lisp is slow" stereotype for a long time, so there's been a lot of work done to optimize it and give the programmer optimization options.
For your specific question about memory access patterns, Common Lisp does allow some control over that via the "dynamic-extent" declaration: (declare (dynamic-extent variable-name)). It tells the compiler (or interpreter) that a variable in an inner scope (of a loop, for example) can be allocated once and the space reused each iteration instead of allocating fresh memory each time. It's not full blown C style control of memory, but it's similar and can have a big impact in some situations. The book "Common Lisp Recipes" has a section on it, and so does the hyperspec: http://www.lispworks.com/documentation/HyperSpec/Body/d_dyna...
The recently published "Common Lisp Recipes" is a great book that covers a ton of topics in this area. I think a lot of people would be surprised just how much control and flexibility is available in Common Lisp.
I wouldn't say Common Lisp is faster than C++ in general, and certainly not by default, but with a bit of work it's possible to get pretty close. Importantly, the optimized code will still look and feel like more or less idiomatic Lisp.
However, the set of problems I can tackle is going to be bounded by the escape-hatches that are available to me. Much like Rust has `unsafe {}`, being able to drop down to the bare metal is an important tool to be used at the appropriate time.
Is hoax a placeholder for "hype" or am I missing something?
Data structures and allocators, surely yes.
One writes ordinary generic functions, and then optimized typed methods in lisp like this:
(defgeneric xplusone (x) (1+ x))
(defmethod xplusone ((x integer)) (1+ x))
(defmethod xplusone ((x double-float)) (1+ x))
The sbcl compiler (called python) even creates the typed methods by itself, so mostly the defgeneric line is enough.
The type hints for args and return types are purely optional, as the compiler figures it out by itself.He is right that algorithms, methods, trump data structures, objects. You always write methods with specializations on objects. Not the other way round, classes with specific methods.
> The sbcl compiler (called python) even creates the typed methods by itself, so mostly the defgeneric line is enough.
Is this some new SBCL extension you are talking about? That `defgeneric` line is an error in CLOS.
Think of defgeneric as the function signature and defmethod as the template specialization. Not sure why you say this is an error in CLOS. Looks fine to me.
That said, most implementations try to auto-infer the generic function metaobject when you use defmethod without defgeneric. SBCL raises a warning.
Good reads on the topic:
http://www.gigamonkeys.com/book/object-reorientation-generic...
(defgeneric xplusone (x)
(:method (x) (+ 1 x)))
Also, generic functions are slower than regular functions (due to dynamic dispatch), so using them for type optimization would be rather counterproductive.http://www.softwarepreservation.org/projects/LISP/parallel
Often parallel computers had also a Lisp implementation. Much more than listed above.
Parallel Computation and Computers for Artificial Intelligence http://link.springer.com/book/10.1007/978-1-4613-1989-4
Parallel Lisp: Languages and Systems http://link.springer.com/book/10.1007/BFb0024148
Parallel Symbolic Computing: Languages, Systems, and Applications http://link.springer.com/book/10.1007/BFb0018643/page/1
template<typename Scalar, typename Functor>
auto
DoSomething(Scalar value, std::size_t k) -> decltype(Functor(Scalar(0))
{
...
Functor(value / Scalar(k));
...
}
Even though it will probably only be used once. Simply because I don't know what types I am going to need yet... but I know it might need a few operators `+`, `-`, `*`, `/`. Once I figure that out, the code is ready to go and is as fast as anything hand written.If somebody could ever write a great 'Haskell for C++ MetaProgrammers' book describing how you are supposed to understand binary layout, IO, and wtf those hundreds of operators mean... you would probably have a bunch of programmers saying "Oh, I guess I know Haskell".
It's also no surprise that a bunch of the STL algorithms structures were easily made parallel in C++17. A lot of developers using the STL correctly could basically change a few lines of code and switch their program from sequential to parallel.
That may be a bug, not a feature. The Boost crowd won the battle, making extremely complex templates an essential part of the language. But they may have lost the war, as C++ loses market share.
LISP backed into typing, and it shows. Both typed variables and objects are painful in LISP. By the time LISP got both, the era of LISP was over. LISP is really dead now; there hasn't been a release of GNU Common LISP ("clisp") in 7 years.
Allegro CL 10.0 released on 2015-10-05
ABCL 1.4.0 released on 2016-10-08
CCL 1.11 released on 2015-11-06
ECL 16.1.3 released on 2016-12-19
Lispworks 7.0 released on 2015-05-05
MKCL 1.1.10 released on 2017-01-18
SBCL 1.3.15 released 2017-02-28a) Grateful for the extensive access to algorithms, lambdas, type inference;
b) Astounded at the complexity of template meta programming.
I imagine I'll get better at it with practice. But I'm operating at about 15% of the time efficiency of, say, Scala.
Generally that is not required even in performance sensitive code. Perhaps a few conditionals a'la enable_if or direct use of SFINAE... but most everything else, not really.
Edit: Clarification, I am not actually having myself to do original metaprogramming, but in order to diagnose problems implementing the custom iterators, I have needed to delve into, and understand, the meaning of the Thrust library code.
It sounds tongue in cheek, but I am serious. In the std library, boost and other sophisticated libraries there are tons of template shenanigans and there is little to be gain for most application developers. The single thing complex template meta-programs buy you is compile time evaluation for things in the middle of algorithms and classes.
Which is useful, but usually for things like deciding how many object should be allocated at once or how big a working set is to keep everything in cache. These are usually the performance optimizations you care about after all the algorithmic ones have been dealt with and often save only a constant number of instructions. When this seemingly insane level of optimization makes sense the author of a library will often accept the needed data as a parameter.
With constexpr things like lookup tables can easily be computed at compile with much more sane code.
(When it breaks, then you have to.)
In practice when the tools we rely on break, we have other alternatives. We tend to start with web searches and asking questions on SO. We can try different versions or libraries. Most problems have workarounds that may or may not be applicable.
Sometimes deep knowledge helps and I will tend to advocate for it. In the case of template metaprogramming, deep knowledge gains you very little and a common breakage will add 2 extra instructions to your runtime execution. If that matters you are already watching for it. As soon as you use COM, RPC, a web API or any scripting language you have already done something that would blow this cost away for an abstraction.
Knowing enough to fix a problem doesn't always mean a deep understanding of every library and tool even in C and C++ land. There is simply too much for any 1 person or any dedicated team to know, we must rely on division of labor. That is why we find abstractions like COM, RPC, web APIs and scripting languages worthwhile, they allow someone else to handle some part of our cognitive load at the cost of runtime performance.
Lisp might be dead, but this sentence is a non sequitur.
GNU Common Lisp : https://www.gnu.org/software/gcl/
GNU CLISP : http://clisp.org
CLISP hasn't had a release in a few years, but the repository has a lot of activity these days:
https://sourceforge.net/p/clisp/clisp/ci/e4aba2ecdcf71968053...
> there hasn't been a release of GNU Common LISP ("clisp") in 7 years.
CLISP had a beta release a few days ago.
Just installed it on my Mac: this is GNU CLISP 2.49.50 from 2017-03-19.
$ clisp
i i i i i i i ooooo o ooooooo ooooo ooooo
I I I I I I I 8 8 8 8 8 o 8 8
I \ `+' / I 8 8 8 8 8 8
\ `-+-' / 8 8 8 ooooo 8oooo
`-__|__-' 8 8 8 8 8
| 8 o 8 8 o 8 8
------+------ ooooo 8oooooo ooo8ooo ooooo 8
Welcome to GNU CLISP 2.49.50 (2017-03-19) <http://clisp.org/>
Copyright (c) Bruno Haible, Michael Stoll 1992, 1993
Copyright (c) Bruno Haible, Marcus Daniels 1994-1997
Copyright (c) Bruno Haible, Pierpaolo Bernardi, Sam Steingold 1998
Copyright (c) Bruno Haible, Sam Steingold 1999-2000
Copyright (c) Sam Steingold, Bruno Haible 2001-2010
Type :h and hit Enter for context help.
[1]> (lisp-implementation-version)
"2.49.50 (2017-03-19) (built 3699208367) (memory 3699208818)"
Doesn't look dead to me...GNU Common Lisp is currently a bit less active: http://git.savannah.gnu.org/cgit/gcl.git/log/
Other 'free/open source' implementations are currently more interesting, especially ECL, Clozure CL and SBCL.
I have on my 32bit ARM under Linux the following implementations: GCL, ECL, LispWorks, SBCL, CCL, ABCL. LispWorks, CCL and SBCL are native compilers. I'd say that's enough choice.
> LISP is really dead now
Not more than usual.
Current version: 2.49 (2010-07-07).
Two people are still making source checkins, but there hasn't been a new release since 2010. It's nice to know that someone is still working on it, but they're not making it to a release version.
There is a beta version.
https://sourceforge.net/p/clisp/mailman/clisp-devel/thread/l...
> Two people are still making source checkins
source checkins = CLISP gets updates
Bruno Haible is one of the original authors. Sam Steingold joined 1999.
If CLISP is important to you, why not help them with testing the new beta release?
I've been toiling all alone since mid 2009 on a great language called TXR which includes a fantastic new Lisp dialect with many original features and ideas.
$ git log --oneline | wc
3643 45798 313606
Over 3600 commits since switching to git late October 2009, after version 18.