| |
 Programme
Overview
Detailed
Programme
| High Performance
and Parallel Computing Tools (HPPCT) |
CHAIR: ANDREJ DOBNIKAR
Tuesday, March 22nd, 11h00-12h40
| HPPCT-1 |
| |
| Title: |
|
|
Datamining in Grid Environment |
| Author(s): |
M.Ciglaric,
M.Pancur,
B.Šter,
A.Dobnikar |
| Abstract: |
The paper deals with assessing performance improvements
and some implementation issues of two well-known data mining
algorithms, Apriori and FP-growth, in Alchemi grid environment.
We compare execution times and speed-up of two parallel implementations:
pure Apriori and hybrid FP-growth - Apriori version on grid
with one to six processors. As expected, the latter shows
superior performances. We also discuss the effects of database
characteristics on overall performance, and give directions
for proper choice of execution parameters and suitable number
of executors. |
 |
| HPPCT-2 |
| |
| Title: |
|
|
Parallel Placement Procedure based
on Distributed Genetic Algorithms |
| Author(s): |
Masaya Yoshikawa,
Takeshi Fujino,
Hidekazu Terai |
| Abstract: |
This paper discusses a novel performance driven
placement technique based on distributed Genetic Algorithms,
and focuses particularly on the following points:(1) The algorithm
has two-level hierarchical structure consisting of outline
placement and detail placement. (2) For selection control,
which is one of the genetic operations, new multi-objective
functions are introduced. (3) In order to reduce the computation
time, a parallel processing is introduced. Results show improvement
of 22.5% for worst path delay, 11.7% for power consumption,
15.9% for wire congestion and 10.7% for chip area. |
|
| HPPCT-3 |
| |
| Title: |
|
|
Massive parallelization of the
compact genetic algorithm |
| Author(s): |
Fernando G. Lobo,
Claudio F. Lima,
Hugo Martires |
| Abstract: |
This paper presents an architecture which is suitable for
a massive parallelization of the compact genetic algorithm.
The resulting scheme has three major advantages. First, it
has low synchronization costs. Second, it is fault tolerant,
and third, it is scalable. The paper argues that the benefits
that can be obtained with the proposed approach is potentially
higher than those obtained with traditional parallel genetic
algorithms. |
|
| HPPCT-4 |
| |
| Title: |
|
|
Parallel implementations of feed-forward
neural network using MPI and C# on .NET platform |
| Author(s): |
U. Lotric,
A. Dobnikar |
| Abstract: |
The parallelization of gradient descent training
algorithm with momentum and the Levenberg-Marquardt algorithm
is implemented using C# and Message Passing Interface (MPI)
on .NET platform. The turnaround times of both algorithms
are analyzed on cluster of equal computers. It is shown that
the optimal number of cluster nodes is a compromise between
the decrease of computational time due to parallelization
and corresponding increase of time needed for communication. |
|
| HPPCT-5 |
| |
| Title: |
|
|
HeuristicLab: A Generic and Extensible
Optimization Environment |
| Author(s): |
S. Wagner,
M. Affenzeller |
| Abstract: |
Today numerous variants of heuristic optimization
algorithms are used to solve different kinds of optimization
problems. This huge variety makes it very difficult to reuse
already implemented algorithms or problems. In this paper
the authors describe a generic, extensible, and paradigm-independent
optimization environment that strongly abstracts the process
of heuristic optimization. By providing a well organized and
strictly separated class structure and by introducing a generic
operator concept for the interaction between algorithms and
problems, HeuristicLab makes it possible to reuse an algorithm
implementation for the attacking of lots of different kinds
of problems and vice versa. Consequently HeuristicLab is very
well suited for rapid prototyping of new algorithms and is
also useful for educational support due to its state-of-the-art
user interface, its self-explanatory API and the use of modern
programming concepts. |
|
| HPPCT-6 |
| |
| Title: |
|
|
THE SATELLITE LIST: A Reversible
Doubly-Linked List |
| Author(s): |
C. Osterman,
C. Rego,
D. Gamboa |
| Abstract: |
Subpath reversals are common operations in graph-based
structures arising in a wide range of applications in
combinatorial optimization. We describe the satellite list,
a variation on the doubly-linked list that is symmetric, efficient,
and can be reversed or reverse subsections in constant time. |
|