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SKILL for the Skilled: Part 6, Many Ways to Sum a List

Comments(0)Filed under: SKILL, Team SKILL, programming, LISP, SKILL++, IC615, summing, sum a list, Jim Newton, SKILL for the SkilledIn a previous post I presented sumlist_2b as a function that would sum lists of length 0, 1, or more.
(defun sumlist_2b (numbers)
  (apply plus 0 0 numbers))

Unfortunately sumlist_2b cannot handle extremely long lists. In this posting, I will introduce sumlist_6 which does not suffer from this limitation.

This posting will not introduce any new SKILL++ primitives. Instead, it will use several primitives which have been introduced in the previous several postings to implement an algorithm which you may not have seen before. If any of these are unknown or mysterious to you, please consult previous postings of SKILL for the Skilled or the Virtuoso on-line documentation.

used to call a function indirectly given the function object and a list of arguments.
modify a status variable of the SKILL virtual machine.
makes function calls in tail position be stack-space neutral.
defines local function functions which may be mutually recursive
defines a clean-up procedure which is executed even if an error is triggered.

Very long lists

If you attempt to use sumlist_2b on extremely long lists it will fail. You can generate a very long list as follows:

data = (list 1.1 -2.1 2.3 -.04)
(for i 1 15
  data = (append data data))

This produces a list of length 131072. If you attempt to sum this list with sumlist_2b you get the following error.

*Error* plus: too many arguments (at most 65535 expected, 131074 given) - (0 0 1.1 -2.1 2.3 ... )
<<< Stack Trace >>>
apply(plus 0 0 numbers)

The error message complains about a list of length 131074. This is because data has length 131072, but sumlist_2b prepends two additional 0's to the argument list. 131072 + 2 = 131074.

An esoteric issue?

You may very well consider this an esoteric issue. And you would be right. If you are in charge of generating the data, and you know the number of elements in your list is less than 16K, then there is no need to worry about this corner case. I suspect very few of the readers of this blog have ever, or will ever encounter such a situation. Even with that being the case, I discuss this here in the hopes that some of the techniques may prove useful, even if the exact problem never occurs.

Another reason to present a solution to this particular problem is that in so doing we can combine several other concepts which have been discussed in the previous SKILL for the Skilled blog postings.

The applyReduce function

The following implementation of applyReduce takes advantage of (sstatus optimizeTailCall t) and unwindProtect as seen in a previous post of SKILL for the Skilled.

(defun applyReduce (fun args @key (maxArgs 8192) identity)
  (labels ((apply_head (fun args tail)
             (let ((save (cdr tail)))
               (setcdr tail nil)
                (apply fun args)
                (setcdr tail save))))
           (apply_reduce (args)
             (let ((tail (nthcdr (sub1 maxArgs) args)))
               (if (cdr tail)
                   (apply_reduce (cons (apply_head fun args tail)
                                       (cdr tail)))
                   (apply fun args)))))
      ((cdr args) 
       ;; if args has more the two elements
       (let ((save_optimizeTailCall (status optimizeTailCall)))
         (sstatus optimizeTailCall t)
           (apply_reduce args)
           (sstatus optimizeTailCall save_optimizeTailCall))))
       ;; if args has exactly one element
       (car args))
       ;; if args is nil

How does it work?

The applyReduce function above calls the given function multiple times, but each time with a maximum of maxArgs number of arguments. The maxArgs parameter defaults to 8192 but you may override it to something smaller, especially to understand better how the function works.

(trace plus)
(applyReduce plus '(.1 .2 .3 .4 .5 .6 .7 .8 .9
                    .11 .12 .13 .14 .15 .16 .17 .18 .19) ?maxArgs 5)
(untrace plus)

In the trace output you can see that the plus function is called several times, but never with more than 5 arguments. After the initial call, the first argument to plus is the return value of the previous call.

||||||||||||||(0.1 + 0.2 + 0.3 + 0.4 + 0.5)
||||||||||||||plus --> 1.5
||||||||||||||||(1.5 + 0.6 + 0.7 + 0.8 + 0.9)
||||||||||||||||plus --> 4.5
||||||||||||||||||(4.5 + 0.11 + 0.12 + 0.13 + 0.14)
||||||||||||||||||plus --> 5.0
||||||||||||||||||||(5.0 + 0.15 + 0.16 + 0.17 + 0.18)
||||||||||||||||||||plus --> 5.66
||||||||||||||||||(5.66 + 0.19)
||||||||||||||||||plus --> 5.85

Now we can use applyReduce to create an efficient sumlist_6 function which is able to add up the elements of an arbitrarily long list. We can use sumlist_6 to add up the 131072 elements of the list data created above.

(defun sumlist_6 (numbers)
  (applyReduce plus numbers ?identity 0))

Testing it, we can see that it works and returns the correct result. We need to test sumlist_6 for a very long list, as well as for the nil list and a singleton list.

(sumlist_6 data)
--> 41287.68

(sumlist_6 nil)
--> 0

(sumlist_6 '(42))
--> 42

What about the performance?

Recall the algorithm implemented as sumlist_1a.

(defun sumlist_1a (numbers)
  (let ((sum 0))
    (foreach number numbers
      sum = sum + number)

On the Linux machine which I normally use, evaluating (sumlist_1a data) takes approximately 0.02 seconds, while evaluating (sumlist_6 data) takes about 0.003. I.e., sumlist_6 is about 6 times faster for large lists.


The technique shown in sumlist_2b is very simple, and requires very little code. Nevertheless, it has the caveat that it will fail for arbitrarily long lists. This usually does not matter, and because this corner case is relatively unlikely to occur, the technique is tempting to use, and in fact is a good solution if the data is under your control and you know the length of the list in question is not extremely large.

The technique shown in sumlist_6 is more correct, at the sacrifice of being more complicated code. That being said, because the complication of sumlist_6 is factored into the implementation of the function applyReduce, the actual implementation of sumlist_6 is as simple as sumlist_2b. I would suggest putting a copy of applyReduce in your personal SKILL function library, with the appropriate customer prefix of course.

More to come

In upcoming posts we'll continue to survey the SKILL++ language using the example of summing a list.

Jim Newton

Previous blog posts in this series

SKILL for the Skilled: Many Ways to Sum a List (Part 5)

SKILL for the Skilled: Many Ways to Sum a List (Part 4)

SKILL for the Skilled: Many Ways to Sum a List (Part 3)

SKILL for the Skilled: Many Ways to Sum a List (Part 2)

SKILL for the Skilled: Many Ways to Sum a List (Part 1)


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