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RE: questions about costs of nativeint vs int
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Date: 2001-01-20 (15:18)
From: Dave Berry <dave@k...>
Subject: RE: questions about costs of nativeint vs int
I was assuming a different approach to GC, using a new header format rather
than ssociating static GC descriptors to every call site and heap block.  I
think this should be no slower than normal tagged GC. 

Let me describe the MLWorks tagging scheme, because it's got some ideas that
might be useful to other implementors, even without extending it to support
untagged integers.

Unlike most ML compilers, which use 31-bit integers and assume that heap
objects are word-aligned, MLWorks used 30-bit integers and assumed that heap
objects were double-word-aligned.  The use of 30-bit integers stemmed from
the tagged integer operations on SPARCs (now deprecated).  Combined with
aligning heap objects on double words, this gave 8 run-time tags:

Integers: Even(000), Odd(100)
Headers:  Heap block(010), Unused(110)
Pointers:  Normal(001), Ref(011), Pair(101), Unused(111)

Aligning heap objects on double-words required padding even-length objects
by an extra word.  But using a special pointer for pairs meant that we could
drop header words for pairs completely, which saved more space than was
introduced by padding longer structures.

I would be interested to learn whether any of these ideas are useful to
other compilers.

Given this framework, my idea for supporting untagged integers was to ensure
that all untagged elements of a record were placed at the end of the record.
The unused header tag (110) would mark the beginning of this section, and
would encode the number of untagged words to skip.  So if a record did not
include any untagged elements, the GC cost would be unaffected.

I was also planning to use the unused pointer tag (111) to encode lists of
untagged integers.  A 111 tag would both point to a pair and indicate that
the word immediately after the pointer was untagged.

Both approaches require that the compiler knows the actual layout of every
type, with coercions inserted for some polymorphic operations.  I accept
your point that the complexity and cost of doing this may outweigh the
gains.  Certainly it's complicated if you pursue a full typeful approach to
compilation.  For functors, I would probably go for compiling functors to
lambda code, and only generating machine code at functor application time.
This would have other optimisation advantages (at least, it would have done
for MLWorks, which didn't have any meaningful cross-module optimisation).
But obviously that's a major change to any system.


-----Original Message-----
From: Xavier Leroy [mailto:Xavier.Leroy@inria.fr]
Sent: Sunday, January 14, 2001 11:13
To: Dave Berry
Cc: Norman Ramsey; caml-list@inria.fr
Subject: Re: questions about costs of nativeint vs int

> Do you have any plans to implement unboxed native integers?

Ocaml performs some amount of local (intra-function) unboxing on large
integers (nativeint, int32, int64) as well as on floats.  Version 3.00
missed some opportunities for local unboxing of large integers, but
the next release will improve this, bringing integer unboxing to the
level of float unboxing.  However, large integers as well as
floats remain boxed across functions and inside data structures
(with a few special cases for arrays and big arrays).

But you were probably asking about having native integers unboxed
everywhere in the program.  I did that in my Gallium experimental
compiler in 1993-1994, using the type-based and coercion-based
approach presented in my POPL 92 paper.  Gallium had 32-bit unboxed
integers, 64-bit unboxed floats, and unboxed tuples, in variables as
well as inside data structures.

Later, I gave up on this technology for several reasons:

1- The approach is very hard to extend to structures and functors.
The FLINT and TIL teams later succeeded in making type-based data
representations work in the presence of functors, using run-time type
inspection instead (or in addition to) coercions.  Still, I think this
approach is too complex for its own good, and entails significant
performance hits on polymorphic or functorized code.

2- GC becomes too slow.  It is not hard to write a GC that can handle
mixtures of boxed and unboxed data (without tag bits for the latter):
just associate static GC descriptors to every call site and to every
heap block.  Gallium did it, no big deal.  But the cost of interpreting
these descriptors at every GC is quite high -- much higher than
testing primary/secondary tags on data like the OCaml GC does.

As a consequence, programs that do a lot of symbolic manipulations,
which spend a lot of time in GC, run slower, while they don't benefit
from unboxed integers and floats since they don't use integers and
floats much.  I found this unacceptable: symbolic computation is ML's
bread-and-butter, and should remain as fast as possible.

3- Local unboxing (of the sort I mentioned earlier) achieves
decent performances on floating-point and integer intensive code --
almost as good as Gallium-style unboxing, and without any of the
GC slowdowns.  (See my TIC'97 paper for some measures.)

> I would really have liked to see this happen, because it would have made
> integration with C both easier and more efficient.

Yes, but at so many extra costs (in GC speed and in overall complexity)
that I don't think it's worth it.


- Xavier

PS.  All papers mentioned are available at