Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high performance applications. FPGA has benefited from the shrinking of transistor feature size, which allows more on-chip reconfigurable (e.g., memories and look-up tables) and routing resources available. Unfortunately, the amount of reconfigurable resources in a FPGA is fixed and limited. This paper investigates the mapping scheme of the applications in a FPGA by utilizing sequential processing (e.g., Altera Nios II or Xilinx Microblaze, using C programming language) and task specific hardware (using hardware description language). Genetic Algorithm is used in this study. We found that placing sequential processor cores into FPGA can improve th...
A genetic algorithm (GA) is a robust problem-solving method based on natural selection. Hardware\u27...
Genetic algorithm (GA) is a directed random search technique working on a population of solutions a...
International audienceIn this work, we propose a new approach toward the efficient optimization and ...
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high ...
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high ...
This paper presents static task scheduling using location-aware genetic algorithm techniques to sche...
Genetic algorithms (GAs) are used to solve search and optimization problems in which an optimal solu...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
FPGA '06 : ACM/SIGDA 14th international symposium on Field programmable gate arrays , Feb 22-24, 200...
Summarization: This paper presents the implementation of a Genetic Algorithm on a XUPV2P platform wi...
This paper propose a Virtual-Field Programmable Gate Array (V-FPGA) architecture that allows direct ...
Genetic Algorithms (GAs) are a class of numerical and combinatorial optimisers which are especially ...
FCCM 2006 : 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines , Apr 24-26, ...
Genetic Algorithms (GAs) are used to solve many optimization problems in science and engineering. GA...
Evolvable hardware allows the generation of circuits that are adapted to specific problems by using ...
A genetic algorithm (GA) is a robust problem-solving method based on natural selection. Hardware\u27...
Genetic algorithm (GA) is a directed random search technique working on a population of solutions a...
International audienceIn this work, we propose a new approach toward the efficient optimization and ...
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high ...
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high ...
This paper presents static task scheduling using location-aware genetic algorithm techniques to sche...
Genetic algorithms (GAs) are used to solve search and optimization problems in which an optimal solu...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
FPGA '06 : ACM/SIGDA 14th international symposium on Field programmable gate arrays , Feb 22-24, 200...
Summarization: This paper presents the implementation of a Genetic Algorithm on a XUPV2P platform wi...
This paper propose a Virtual-Field Programmable Gate Array (V-FPGA) architecture that allows direct ...
Genetic Algorithms (GAs) are a class of numerical and combinatorial optimisers which are especially ...
FCCM 2006 : 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines , Apr 24-26, ...
Genetic Algorithms (GAs) are used to solve many optimization problems in science and engineering. GA...
Evolvable hardware allows the generation of circuits that are adapted to specific problems by using ...
A genetic algorithm (GA) is a robust problem-solving method based on natural selection. Hardware\u27...
Genetic algorithm (GA) is a directed random search technique working on a population of solutions a...
International audienceIn this work, we propose a new approach toward the efficient optimization and ...