Different Versions of Yale Haskell Compared
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There are currently three different platforms running Yale Haskell.
Yale Haskell runs on Lucid Common Lisp, CMU Common Lisp, and AKCL. This
document describes the differences between these systems.
Differences in performance between the different versions of Yale
Haskell reflect the underlying Lisp systems. The better the Lisp
system, the better the Haskell system built on it. However, getting
optimal performance from our Haskell system on top of a Common Lisp
system requires careful attention to the underlying compiler. Small
changes in the optimization settings or the addition of crucial
declarations can make significant differences in performance. We have
been doing most of our work using the Lucid system and have tuned it
more than the others. These comparisons are greatly influenced by the
amount of time we have spent tuning the system: the CMU version has
been tuned only a little and the AKCL version hardly at all.
Methodology
The following timings are only approximate. They were obtained using
the timing functions provided by the Common Lisp system. All timings
were done on an unloaded Sparc 1. No attempt was made to account for
garbage collection, differences in heap size, or similar factors. We
don't intend these benchmark results to be taken as an exhaustive
comparison of the different Lisp implementations involved.
Portability
We have had no trouble moving our system to different hardware
platforms under the same Lisp system. Since the release is in source
form, we expect that users will be able to build on any hardware
platform supported by one the Lisps we have ported to. Probably the
only real constraint on portability is the requirement for a large
virtual memory space.
>From the comp.lang.lisp FAQ:
Lucid Common Lisp runs on a variety of platforms, including PCs (AIX),
Apollo, HP, Sun-3, Sparc, IBM RT, IBM RS/6000, Decstation 3100,
Silicon Graphics, and Vax.
CMU Common Lisp is free, and runs on Sparcs (Mach and SunOs),
DecStation 3100 (Mach), IBM RT (Mach) and requires 16mb RAM, 25mb disk.
Kyoto Common Lisp (KCL) is free, but requires a license. Conforms to CLtL1.
It is available by anonymous ftp from rascal.ics.utexas.edu [128.83.138.20],
cli.com [192.31.85.1], or [133.11.11.11] (a machine in Japan)
in the directory /pub. AKCL is in the file akcl-xxx.tar.Z (take the
highest value of xxx). To obtain KCL, one must first sign and mail a
copy of the license agreement to: Special Interest Group in LISP,
c/o Taiichi Yuasa, Department of Computer Science, Toyohashi
University of Technology, Toyohashi 441, JAPAN. Runs on Sparc,
IBM RT, RS/6000, DecStation 3100, hp300, hp800, Macintosh II (under AUX),
mp386, IBM PS2, Silicon Graphics 4d, Sun3, Sun4, Sequent Symmetry,
IBM 370, NeXT and Vax. A port to DOS is in beta test as
math.utexas.edu:pub/beta2.zip.
We have not yet completed ports of Yale Haskell to any other Lisp
implementations, although we are likely to do so in the future.
System Size
The overall size of the Haskell system depends on the size of the
underlying Lisp system and how much unnecessary Lisp overhead has been
removed for the system. We have removed large Lisp packages (like
CLOS or CLX), but have not attempted to do any tree shaking. The size
of the saved images (including the Lisp system, the Haskell compiler,
and the compiled prelude) is
Image Size:
Lucid 10 meg
CMU 18 meg
AKCL 11 meg
The larger size of the CMU system is probably an artifact of their way
of saving the system.
Compilation Time
There are three possible ways to compile a Haskell program. All
Haskell programs must be translated into Lisp. The generated Lisp can
then be interpreted, using no additional compilation time; compiled
with a `fast' but nonoptimizing Lisp compiler; or compiled with the
`slow' compiler that aggressively attempts to perform as many
optimizations as possible.
To time the `fast', nonoptimizing compiler, we have been using
(PROCLAIM '(OPTIMIZE (SPEED 3) (SAFETY 0) (COMPILATION-SPEED 3)))
and for the `slow', fully optimizing compiler, we have been using
(PROCLAIM '(OPTIMIZE (SPEED 3) (SAFETY 0) (COMPILATION-SPEED 0)))
so that the only difference is in the COMPILATION-SPEED quality.
Lucid does, in fact, provide two completely different compilers that
correspond to these optimize settings. For all three implementations,
it appears that that the effect of a higher compilation speed setting
is primarily in being less aggressive about inlining and making use of
type declarations.
The Haskell system itself (including the Prelude) is normally built
with the fully optimizing compiler.
To show just the Haskell to Lisp compilation time, here are the times
needed to compile the Prelude (about 2500 lines of Haskell code).
This does not include the time in the Lisp compiler or starting up the
system.
Time to compile the Prelude into Lisp: (CPU times)
Lucid 111 sec
CMU 87 sec
AKCL 576 sec
Running the Lisp compiler on the generated code takes far longer than
running the Haskell compiler to produce the Lisp code. For example,
the optimizing Lucid compiler takes 47 minutes to compile the Prelude
(about x20 slower than Haskell -> Lisp). The nonoptimizing compiler
is significantly faster but generates poorer code.
The following times are the Lisp compilation time for the Prolog
interpreter (found in the demo directory of our release):
Lucid - interpreted 8.8 sec Haskell -> Lisp
Lucid - nonopt 20.0 sec Lisp -> Machine code
Lucid - optimizing 320.0 sec Lisp -> Machine code
CMU - interpreted 12.4 sec Haskell -> Lisp
CMU - nonopt 121.0 sec Lisp -> Machine code
CMU - optimizing 152.8 sec Lisp -> Machine code
AKCL - interpreted 47.8 sec Haskell -> Lisp
AKCL - nonopt ~180 sec Lisp -> Machine code
AKCL - optimizing ~360 sec Lisp -> Machine code
The AKCL timings are only approximate, because the Lisp timing
functions do not capture the time spent in the C compiler.
Code Speed
The speed of the Haskell program depends on whether the Lisp code
has been compiled with the optimizing or nonoptimizing compiler, or
is running interpretively.
The first benchmark is nfib, which indicates the basic speed of
function calling and Int arithmetic.
module Main where
nfib :: Int -> Int
nfib 0 = 1
nfib 1 = 1
nfib n = nfib (n-1) + nfib (n-2)
nfib 20 nfib 30
Lucid (Interpreted) 116 sec *
Lucid (nonopt) 0.14 sec 9.4 sec
Lucid (optimizing) 0.08 sec 4.8 sec
CMU (Interpreted) 23.8 sec *
CMU (nonopt) 0.24 sec 6.9 sec
CMU (optimizing) 0.11 sec 7.0 sec
AKCL (Interpreted) 141 sec *
AKCL (nonopt) 0.20 sec 21.3 sec
AKCL (optimizing) 0.15 sec 18.2 sec
* Too slow to benchmark
For other data types, there was no significant difference betwen
optimizing and nonoptimizing compilation in any of the systems.
Changing the signature of nfib to Integer -> Integer:
nfib 20 nfib 30
Lucid (interpreted) 140 sec *
Lucid (compiled) 0.18 sec 10.2 sec
CMU (interpreted) 24.2 sec *
CMU (compiled) 0.16 sec 10.5 sec
AKCL (interpreted) 145 sec *
AKCL (compiled) 1.07 sec 127 sec
Nfib with signature Float -> Float:
nfib 20 nfib 30
Lucid (interpreted) 222 sec *
Lucid (compiled) 16.4 sec 2416 sec
CMU (interpreted) 44.2 sec *
CMU (compiled) 1.61 sec 352 sec
AKCL (interpreted) 161 sec *
AKCL (compiled) 103 sec *
Overloaded functions run considerably slower than nonoverloaded
functions. By allowing nfib to remain overloaded, Num a => a -> a,
and using the Int overloading the same benchmarks run much slower.
Again, there is no real difference between the different compiler
optimization settings.
nfib 15 nfib 20
Lucid (interpreted) 14.2 sec 156 sec
Lucid (compiled) 0.97 sec 9.3 sec
CMU (interpreted) 23.8 sec 155 sec
CMU (compiled) 0.89 sec 15.6 sec
AKCL (interpreted) 30.8 sec 387 sec
AKCL (compiled) 10.3 sec 119 sec
Basic Haskell data structuring operations (pattern matching and
construction) can be tested using another version of nfib which uses
natural numbers:
data Nat = Z | S Nat
The difference betwen CMU and Lucid here is consistent with other
benchmarks that manipulate structures.
nfib 10 nfib 15
Lucid (Interpreted) 1.39 sec 26.7 sec
Lucid (compiled) 0.26 sec 2.28 sec
CMU (interpreted) 3.1 sec <stack overflow>
CMU (compiled) 0.16 sec 0.54 sec
AKCL (Interpreted) 4.25 sec <stack overflow>
AKCL (compiled) 0.21 sec 13.9 sec
A Large Program
For a final benchmark, we use the Prolog interpreter as a way of
getting a feel for general performance of larger programs. This
program is typical of symbolic (as opposed to numeric) computation.
Time to solve append(X,Y,cons(a,cons(b,cons(c,nil)))):
Lucid 12.2 sec
CMU 12.0 sec
AKCL 69.1 sec
My interpretation of this result is that although Lucid is a bit
slower on the previous small benchmarks, it makes up for this is
larger programs where advantages like better instruction scheduling,
register allocation, or memory usage may make a difference. In
general, Lucid and CMU are very similar in performance for larger
programs.
Conclusions
Briefly stated, the pluses and minuses of each system are as follows:
Lucid (4.0.0):
+ Development (nonoptimizing) compiler is very fast
+ Fast Haskell -> Lisp compilation
+ Generates good code
+ Very robust
- Costs money
- Slow floating point code
- Fairly slow interpreter
- The production (optimizing) compiler is extremely slow.
CMU (16e):
+ Free
+ As fast as Lucid for Haskell -> Lisp
+ Good floating point performance
+ Generated code is very fast
+ Fast interpreter
- Slow Lisp -> machine code compilation
- Doesn't run on many systems
AKCL (1.615):
+ Free
+ Widely portable
- Slow (generally 3 - 5 times slower, sometimes much worse)
- Flakey (tends to core dump on errors, choke on large programs, etc.)
Generally, using the fully optimizing compiler seems to be useful only
in code involving Int arithmetic.
The fast compiler for Lucid is a big advantage, delivering by far the
fastest compilation to machine code with relatively little loss in
speed compared to the optimizing compiler.
Yale Haskell Group
September 25, 1992
