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Genetic Algorithms, Parallelism, and Reconfigurable Hardware
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Several international Projects and Collaborations have emerged in the last years due to the increasing demand for Grid resources. One important aspect of these initiatives deals with the gridification of computing intensive scientific applications otherwise difficult to run efficiently. The EELA Project (E-Infrastructure shared between Europe and Latin America) is a collaboration of Latin America and Europe Institutions whose aim is to create human and scientific networks. It has developed a performance e-Infrastructure for e-Science applications in the fields of Biomedicine, High Energy Physics, e-Learning and Climate. Nowadays many groups have already ported their applications on the EELA Grid and are obtaining first results. This paper describes the first year of EELA and the progress achieved so far.
Field programmable gate arrays (FPGAs) are becoming increasingly important implementation platforms for digital circuits. One of the necessary requirements to effectively utilize the FPGA's fixed resources is an efficient placement and routing mechanism. This paper presents particle swarm optimization (PSO) for FPGA placement and routing. Preliminary results for the implementation of an arithmetic logic unit on a Xilinx FPGA show that PSO is a potential technique for solving the placement and routing problem.
This paper presents a performance-oriented placement and routing tool for field-programmable
gate arrays. Using recursive geometric partitioning for simultaneous
placement and global routing, and a graph-based strategy for detailed routing, our tool
optimizes source-sink pathlengths, channel width and total wirelength. Our results
compare favorably with other FPGA layout tools, as measured by the maximum
channel width required to place and route several benchmarks.
We present results on the application of a new methodology based on Parallel and Distributed Genetic Programming (PADGP).
The aim for the methodology we present is to automatically perform the placement and routing of circuits on reconfigurable
hardware. The system has been successfully applied to some benchmark problems. For each of the problems we have dealt with,
the methodology is capable of finding several solutions. The results show the methodology’s feasibility for addressing the
problem of placement and routing on FPGAs.
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.
As computers and software have become more powerful, it seems
almost human nature to want the biggest and fastest toy you can afford.
But how do you know if your toy is tops? Even if your application never
does any I/O, it's not just the speed of the CPU that dictates
performance. Cache, main memory, and compilers also play a role.
Software applications also have differing performance requirements. So
whom do you trust to provide this information? The Standard Performance
Evaluation Corporation (SPEC) is a nonprofit consortium whose members
include hardware vendors, software vendors, universities, customers, and
consultants. SPEC's mission is to develop technically credible and
objective component- and system-level benchmarks for multiple operating
systems and environments, including high-performance numeric computing,
Web servers, and graphical subsystems. On 30 June 2000, SPEC retired the
CPU95 benchmark suite. Its replacement is CPU2000, a new CPU benchmark
suite with 19 applications that have never before been in a SPEC CPU
suite. The article discusses how SPEC developed this benchmark suite and
what the benchmarks do
The GridWay framework for adaptative scheduling execution on grids
- Huedo E.
Placement and routing of Boolean functions in constrained FPGAs using a distributed genetic algorithm and local search
- M Rubio
- J Sanchez
- J Gomez
- Vega
Using genetic algorithms for delay minimization in the FPGAs routing. InProceedings of the First International NAISO Congress on Neuro Fuzzy Technologies(NF'02)
- J Altunaandw
- Falcon
Genetic algorithms for solving the placement and routing problem of an FPGA with area constraints
- M Rubio
- J Sanchez
- J Gomez
- Vega