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[Caml-list] @, List.append, and tail recursion
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 Date: 2003-01-31 (17:04) From: Brian Hurt Subject: Re: [Caml-list] @, List.append, and tail recursion
```On Thu, 30 Jan 2003, james woodyatt wrote:

> everyone--
>
> Earlier in this thread, I suggested using a queue if you are spending
> too much time in List.append.  Lack of optimized tail recursion is not
> really a factor compared to the waste of cycles involved in
> constructing a whole new list just to append a single element on the
> end.
>
> Apparently, nobody seemed to notice what I was talking about.  So I'm
> going to try to make my point again.  Sorry if you got it the first
> time.

I did get it the first time.  I'm just using List.append to illustrate a
problem I'm having.

The problem is *constructing* lists.  If you can construct your list
backwards, fine- but if you can't, you end up either not being tail
recursive (and blowing up for long lists) or allocating the list twice.

Here's an example I have run across.  I'm working with sparse vectors, and
basically storing them as (int * float) lists.  Now, let's write the
vector add function.  The naive implementation would be:

let rec add x y = (* return x + y *)
match (x, y) with
([], _) -> y
| (_, []) -> x
| (((xidx, xval) as xhead) :: xtail,
((yidx, yval) as yhead) :: ytail)
->
if (xidx == yidx) then
(xidx, xval +. yval) :: (add xtail ytail)
else if (xidx < yidx) then
else
;;

It's simple, and obvious in both what it does and how it does it.  Except
opps, this isn't tail recursive.  If your sparse vectors might be 65536
elements long, this will blow up.  So we rewrite to be tail recursive:

let add x y = (* return x + y *)
let add_int x y accum =
match (x, y) with
([], _) -> (List.rev_append accum y)
| (_, []) -> (List.rev_append accum x)
| (((xidx, xval) as xhead) :: xtail,
((yidx, yval) as yhead) :: ytail)
->
if (xidx == yidx) then
add_int xtail ytail ((xidx, xval +. yval) :: accum)
else if (xidx < yidx) then
else
;;

This makes the function truely tail recursive, except now it's allocating
most of the returned vector twice (once as accum, and once in
List.rev_append) and it's signifigantly uglier IMHO.  Rewritting the code
to use set_cdr is the best performaner, but the ugliest yet.

And the add function is truely simple.  It can handle minor increases in
ugliness without losing much.  But now consider something rather more
complicated- say matrix transposition or matrix multiplication with
matricies defined as:

type vector_t = (int * float) list ;; (* index * value list *)
type matrix_t = (int * vector_t) list ;; (* row index * row vector list *)

Now minor uglification becomes major uglification.  It'd be nicer just to
be able to be able to construct lists forwards instead of backwards.

List.append is just an obvious example to be talking about, but the
problem is signifigantly more general.

Brian

>
> On Thursday, Jan 30, 2003, at 13:57 US/Pacific, Brian Hurt wrote:
> > On Thu, 30 Jan 2003, Olivier Andrieu wrote:
> >
> >>> list1: 1.462s
> >>> list2: 1.757s
> >>> list3: 1.824s
> >>
> >> There's an assert in setcdr : it's important because the first
> >> argument mustn't be an empty list. It's never the case here, so you
> >> can safely compile with -noassert.
> >
> > Doh!  OK- now, compiling with -noassert drops the time to 1.457 seconds
> > (same machine, same environment)- to slightly better than the recursive
> > version.
>
> For grins, I wrote an equivalent test program.  It uses a functional
> deque instead of a list.  (I have written one.  It's a component of my
> Cf library, which remains unreleased at the moment.  Markus Mottl has
> translated several of Chris Okasaki's functional queue implementations
> into Ocaml, and you can find them on the Hump.)
>
> To get started, I timed the 'benchmarks' by running them on my iBook
> (the 700 MHz G3 model) so I could get a baseline.  My little iBook is
> nowhere near as fast as your cool 1.6GHz P4, but I'm not complaining.
>
> The results of my tests were:
>
> 	\$ time ./list1
> 	3.690u 0.070s 0:04.14 90.8%     0+0k 0+0io 0pf+0w
>
> 	\$ time ./list2
> 	4.180u 0.020s 0:05.01 83.8%     0+0k 0+0io 0pf+0w
>
> 	\$ time ./list3
> 	3.700u 0.000s 0:04.49 82.4%     0+0k 0+0io 0pf+0w
>
> Not real fast, but fast enough that I don't mind waiting for results.
> So, what difference does my functional deque implementation make?  Glad
>
> My Cf_deque module matches the following signature:
>
> 	(* begin cf_deque.mli *)
> 	type 'a t
>
> 	val nil: 'a t
>
> 	module type Direction_T = sig
> 	    val pop: 'a t -> ('a * 'a t) option
> 	    val push: 'a -> 'a t -> 'a t
> 	end
>
> 	module A: Direction_T
> 	module B: Direction_T
>
> 	val cat: 'a t -> 'a t -> 'a t
> 	(* end file *)
>
> (Actually, this isn't the complete interface.  I've written a variety
> of ancillary functions that make it convenient to work with the objects
> in a deque without having to translate them into lists, e.g. fold,
> iterate, etc.)
>
> All the functions above are purely functional, and they perform with
> O(1) average complexity.  (Or at least, that's my untrained analysis.
> I'd like to provide proof of that assertion, and I'm working on getting
> some help in that effort-- but, I'll have more news on that when I have
> it.)
>
> Here's a variant of the list1.ml test above, which uses my Cf_deque
>
> 	(* begin t-opt.deque.ml *)
> 	open Cf_deque
>
> 	let rec makelist_aux c accum =
> 	  let accum = B.push c accum in
> 	  if c > 0 then makelist_aux (pred c) accum else accum
>
> 	let makelist c = makelist_aux c nil
>
> 	;;
> 	let _ = makelist 5000;;
> 	(* end file *)
>
> Here are the timing results on that same iBook:
>
> 	\$ time ./t-opt.deque
> 	0.010u 0.010s 0:00.02 100.0%    0+0k 0+0io 0pf+0w
>
> In other words, it's done before enough time passes even to measure it
> properly.
>
> > And for the record, I just tested with appending to a list of 500,000
> > elements, and it worked OK.
>
> Here is the result of running my version of the test with 500,000
> elements:
>
> 	\$ time ./t-opt.deque
> 	0.450u 0.080s 0:00.75 70.6%     0+0k 0+0io 0pf+0w
>
> It took under a second of wall-clock time.  On the other hand, when I
> modified list3.ml for 500,000 elements, it took *forever* in wall-clock
> time.  I gave up after almost an hour and a half.  Ultimately, I killed
> it with SIGINT before it finished.  I have no idea how far it got.
>
> Clearly, I need to push a lot more elements into my deque before I will
> get a timing result that I can measure in heartbeats.  Here is the
> result for 5,000,000 elements:
>
> 	\$ time ./t-opt.deque
> 	5.160u 0.510s 0:06.69 84.7%     0+0k 0+0io 0pf+0w
>
> At this stage, I noticed my little iBook was just starting to thrash
> when the program finished.    So, I bumped it up to 50,000,000
> elements, because I like punishing my computer from time to time-- just
> to teach it respect.
>
> At around 15 seconds into the run, the program turned into the
> psychedelic pizza delivery service: the pager went into fear and
> loathing mode, and the pretty Aqua GUI started acting like it was
> sniffing glue.  If I had let it run to completion, it probably would
> have wedged the machine.  (Mac OS X is pretty stable, but it hates
> resource bombs as much as any other operating system.)
>
> None of the listN.ml files were able to bring down the machine like
> that, no matter how long I let them run-- which should make sense,
> right?  The APPEND function is O(N) for lists.  Once N gets beyond a
> few hundred, the program spends almost all its cycles just copying list
> cells inside its innermost loop, only occasionally reaching the end of
> a list and tacking a new cell onto the end before starting over again.
>
> The problem is not the language, or the compiler.  The problem is the
> design of the program.  The moral of this story: you really should
> consider using a queue if you find your programs are spending a lot of
> cycles appending things to very long lists.
>
>
>

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