Add to ORKGThis paper presents a Genetic Algorithm (GA) based approach for Hardware/Software partitioning targeting an architecture composed of a processor and a dynamically reconfigurable datapath (FPGA). From an acyclic task graph and a set of Area-Time implementation trade offs points for each task, our GA performs HW/SW partitioning and scheduling such that the global application execution time is minimized. The efficiency of our GA is established through its application to a AC-3 decoder function and its performance is compared with a greedy algorithm. 1
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
Reconfigurable computing allows field programmable gate arrays (FPGA) to form a platform for develop...
Hardware/Software partitioning is one of the most important issues of codesign of embedded systems, ...
In this project, HW-SW Partitioning is used as a process to map each task of image processing applic...
Genetic Algorithms (GAs) are robust techniques based on natural selection that can be used to solve ...
In this article, we propose a novel partitioning method for hardware-software codesign based on a ge...
During the last decade, the complexity and size of circuits have been rapidly increasing, placing a ...
This paper presents static task scheduling using location-aware genetic algorithm techniques to sche...
This study discusses hardware-software partitioning, which is useful for system-on-chip (SoC) applic...
Abstract: It has been proved that the hardware/software partitioning problem is NP-hard. Currently w...
In this paper, a genetic algorithm (GA) for scheduling tasks onto dynamically reconfigurable devices...
Several embedded application domains for reconfigurable systems tend to combine frequent changes wit...
Summarization: Genetic algorithms (GA) are search algorithms based on the mechanism of natural selec...
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high ...
A genetic algorithm (GA) is a robust problem-solving method based on natural selection. Hardware\u27...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
Reconfigurable computing allows field programmable gate arrays (FPGA) to form a platform for develop...
Hardware/Software partitioning is one of the most important issues of codesign of embedded systems, ...
In this project, HW-SW Partitioning is used as a process to map each task of image processing applic...
Genetic Algorithms (GAs) are robust techniques based on natural selection that can be used to solve ...
In this article, we propose a novel partitioning method for hardware-software codesign based on a ge...
During the last decade, the complexity and size of circuits have been rapidly increasing, placing a ...
This paper presents static task scheduling using location-aware genetic algorithm techniques to sche...
This study discusses hardware-software partitioning, which is useful for system-on-chip (SoC) applic...
Abstract: It has been proved that the hardware/software partitioning problem is NP-hard. Currently w...
In this paper, a genetic algorithm (GA) for scheduling tasks onto dynamically reconfigurable devices...
Several embedded application domains for reconfigurable systems tend to combine frequent changes wit...
Summarization: Genetic algorithms (GA) are search algorithms based on the mechanism of natural selec...
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high ...
A genetic algorithm (GA) is a robust problem-solving method based on natural selection. Hardware\u27...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
Reconfigurable computing allows field programmable gate arrays (FPGA) to form a platform for develop...
Hardware/Software partitioning is one of the most important issues of codesign of embedded systems, ...