[TYPES/announce] DAMP 2007: Call for Papers

[Neal Glew]

                        DAMP 2007: Workshop on
             Declarative Aspects of Multicore Programming
                             Nice, France
                            16 January 2007
                      (colocated with POPL 2007)
                      http://www.cs.cmu.edu/~damp

Parallelism is going mainstream. Many chip manufactures are turning to
multicore processor designs rather than scalar-oriented frequency
increases as a way to get performance in their desktop, enterprise,
and mobile processors. This endeavor is not likely to succeed long
term if mainstream applications cannot be parallelized to take
advantage of tens and eventually hundreds of hardware
threads. Parallelizing programs is a difficult problem. User
specification of parallelism is fraught with pitfalls such as race
conditions, non-determinism in thread interactions, a lack of
debugging methods, and poorly understood performance
consequences. Automatic parallelization of existing imperative
languages will not meet the challenge due to dependencies and
aliasing. Multicore architectures will differ in significant ways from
their multisocket predecessors. For example, the communication to
compute bandwidth ratio is likely to be higher, which will positively
impact performance. More generally, multicore architectures introduce
several new dimensions of variability in both performance guarantees
and architectural contracts, such as the memory model, that may not
stabilize for several generations of product.

Programs written in functional or logic programming languages, or even
in other languages with a controlled use of side effects, can greatly
simplify parallel programming. Such declarative programming allows for
a deterministic semantics even when the underlying implementation
might be highly non-deterministic. In addition to simplifying
programming this can simplify debugging and analyzing correctness.

DAMP is a one day workshop seeking to explore ideas in programming
language design that will greatly simplify programming for multicore
architectures, and more generally for tightly coupled parallel
architectures. The emphasis will be on functional and logic
programming, but any programming language ideas that aim to raise the
level of abstraction are welcome. DAMP seeks to gather together
researchers in declarative approaches to parallel programming and to
foster cross fertilization across different approaches.

Specific topics include, but are not limited to: 

* suitability of functional and logic programming languages to
  multicore applications; 
* run-time issues such as garbage collection or thread scheduling; 
* architectural features that may enhance the parallel performance of
  declarative languages;
* type systems for accurately knowing or limiting dependencies,
  aliasing, effects, and nonpure features;
* ways of specifying or hinting at parallelism 
* ways of specifying or hinting at data placement which abstract away
  from any details of the machine; 
* compiler techniques; 
* experiences of and challenges arising from making declarative
  programming practical;
* technology for debugging parallel programs the design and
  implementation of domain-specific declarative languages for
  multi-core;

We are looking for short papers (3-5) pages. These can be in the form
of a position paper, new ideas, initial results, overview of ongoing
research, or even a historical perspective. Submissions are due
November 3; notification of acceptance will be sent by December 1;
final copies will be due January 5.

Programm Chair:

Professor Guy Blelloch
Department of Computer Science
Carnegie Mellon University
blelloch at cs.cmu.edu 

Programme Committee:

Perry Cheng, IBM T. J. Watson Research Center
Gopal Gupta, University of Texas at Dallas
Kevin Hammond, University of St Andrews
Robert Harper, Carnegie Mellon University
Surresh Jagannathan, Purdue University
Charles Leiserson, Massachuetts Institute of Technology
Christian Lengauer, University of Passau
Simon Peyton Jones, Microsoft Research

General Chair:

Neal Glew
Intel Corporation
Santa Clara, CA, USA
neal.glew at intel.com