thesis available for ftp

[urs@cs.stanford.edu (Urs Hoelzle)]

Dear self-interesters,

My thesis is now available via ftp and Mosaic (see below).  Yes, I
have graduated!  Though many things will change, I'm planning to keep
on working on Self at UCSB; my new e-mail address is urs@cs.ucsb.edu.
However, I am no longer maintaining the self-interest list, for
questions/requests please contact self-request@self rather than
writing directly to me.

-Urs

---------------

Urs Hoelzle. "Adaptive Optimization for Self: Reconciling High
Performance with Exploratory Programming." Ph.D. thesis, Computer
Science Department, Stanford University, August 1994.

The report is available in PostScript form via ftp from
self.stanford.edu:/pub/papers/hoelzle-thesis.ps.Z or via Mosaic from
http://self.stanford.edu.  In a few weeks, it should be available in
printed form as a Stanford CSD technical report and as a Sun
Microsystems Laboratories technical report.

Abstract: Crossing abstraction boundaries often incurs a substantial
run-time overhead in the form of frequent procedure calls.  Thus,
pervasive use of abstraction, while desirable from a design
standpoint, may lead to very inefficient programs.  Aggressively
optimizing compilers can reduce this overhead but conflict with
interactive programming environments because they introduce long
compilation pauses and often preclude source-level debugging. Thus,
programmers are caught on the horns of two dilemmas: they have to
choose between abstraction and efficiency, and between respon sive
programming environments and efficiency. This dissertation shows how
to reconcile these seemingly contradic tory goals by performing
optimizations lazily.

Four new techniques work together to achieve this:

- Type feedback achieves high performance by allowing the compiler to
inline message sends based on information extracted from the runtime
system. On average, programs run 1.5 times faster than the previous
SELF system; compared to a commercial Smalltalk implementation, two
medium-sized benchmarks run about three times faster.  This level of
performance is obtained with a compiler that is both simpler and
faster than previous SELF compilers.

- Adaptive optimization achieves high responsiveness without sacrificing
performance by using a fast compiler to generate initial code while
automatically recompiling heavily used program parts with an
optimizing compiler. On a previous-generation workstation like the
SPARCstation-2, fewer than 200 pauses exceeded 200 ms during a 50-
minute interaction, and 21 pauses exceeded one second. On a
current-generation workstation, only 13 pauses exceed 400 ms.

- Dynamic deoptimization shields the programmer from the complexity of
debugging optimized code by transparently recreating non-optimized
code as needed. No matter whether a program is optimized or not, it
can always be stopped, inspected, and single-stepped. Compared to
previous approaches, deoptimization allows more debugging while
placing fewer restrictions on the optimizations allowed.

- Polymorphic inline caching generates type-case sequences on-the-fly to
speed up messages sent from the same call site to several different
types of objects. More significantly, they collect concrete type
information for the compiler.

With better performance yet good interactive behavior, these
techniques reconcile exploratory programming, ubiqui tous abstraction,
and high performance.