Temat: embedded design - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: GP-based methodology for HW/SW co-synthesis of multiprocessor embedded systems with increasing number of individuals obtained by mutation
Autorzy:: Górski, Adam
Ogorzałek, Maciej
Wydawca:: SciTePress
Opis:: In this work, a genetic programming methodology for co-synthesis of multiprocessor systems is presented. Genotype is a tree which nodes include system construction procedures. Thus the design methodology is evolving. Next generations are obtained using genetic operators: mutation, reproduction and crossover. Unlike other algorithms in presented methodology number of individuals obtained by mutation operator is not const. Therefore number of individuals in each population is increasing. The size of final generation is found by the algorithm.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

Inne

Skocz do pozycji: 2.

Tytuł:: Iterative improvement methodology for hardware/software co-synthesis of embedded systems using genetic programming
Autorzy:: Górski, Adam
Ogorzałek, Maciej
Wydawca:: Institute of Electrical and Electronics Engineers (IEEE)
Opis:: In this paper we present a novel developmental genetic programming methodology for co-synthesis of distributed embedded systems. This methodology is based on iterative improvement algorithms. Genotype is represented by a tree. Unlike existing genetic programming approaches, our methodology starts from the fastest architecture. Every node in the tree is a chromosome and describes system refinement option. Thus the co-synthesis process is evolving. Using genetic operators: crossover, mutation and selection new systems are created.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

Inne

Skocz do pozycji: 3.

Tytuł:: Adaptive GP-based algorithm for hardware/software co-design of distributed embedded systems
Autorzy:: Górski, Adam
Ogorzałek, Maciej
Wydawca:: SciTePress
Opis:: In this work, a novel adaptive approach to co-design of embedded systems is presented. The approach is based on developmental genetic programming. Unlike most of existing algorithms, presented methodology involves evolving co-synthesis process, not the system architecture directly. Genotype is a tree which nodes include system construction options. The system can adapt to the environment by increasing chromosomes which give better results in each situations. Half of the next populations is created using genetic operators (crossover, mutation, reproduction). Second half is obtained by generating additional solutions but with different probability of the options.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

Inne

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