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An integrated high-level hardware/software partitioning methodology.

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Title: An integrated high-level hardware/software partitioning methodology.
Authors: Abdelhalim, M.1 mbakr@ieee.org, Habib, S.2 seraged@ieee.org
Source: Design Automation for Embedded Systems. Mar2011, Vol. 15 Issue 1, p19-50. 32p.
Subjects: Embedded computer system design & construction, Particle swarm optimization, Field programmable gate arrays, Computer systems, Computer software, Electronic systems
Abstract: Embedded systems are widely used in many sophisticated applications. To speed the time-to-market cycle, the hardware and software co-design has become one of the main methodologies in modern embedded systems. The most important challenge in the embedded system design is partitioning; i.e. deciding which modules of the system should be implemented in hardware and which ones in software. Finding an optimal partition is hard because of the large number and different characteristics of the modules that have to be considered. In this article, we develop a new high-level hardware/software partitioning methodology. Two novel features characterize this methodology. Firstly, the Particle Swarm Optimization (PSO) technique is introduced to the Hardware/Software partitioning field. Secondly, the hardware is modeled using two extreme implementations that bound different hardware scheduling alternatives. Our methodology further partitions the design into hardware and software modules at the early Control-Data Flow Graph (CDFG) level of the design; thanks to improved modeling techniques using intermediate-granularity functional modules. A new restarting technique is applied to PSO to avoid quick convergence. This technique is called Re-Excited PSO. Our numerical results prove the usefulness of the proposed technique. The target technology is Field Programmable Gate Arrays (FPGAs). We developed FPGA-based estimation techniques to evaluate the costs of implementing the design components. These costs are the area, delay, latency, and power consumption for both the hardware and software implementations. Hardware/software communication is also taken into consideration. The aforementioned methodology is embodied in an integrated CAD tool for hardware/software co-design. This tool accepts behavioral, un-timed, algorithmic-level, VHDL, design representation, and outputs a valid hardware/software partition and schedule for the design subject to a set of area/power/delay constraints. This tool is code named CUPSHOP for (Cairo University PSo-based Hardware/sOftware Partitioning tool). Finally, a JPEG-encoder case study is used to validate and contrast our partitioning methodology against the prior-art methodologies. [ABSTRACT FROM AUTHOR]
Copyright of Design Automation for Embedded Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: An integrated high-level hardware/software partitioning methodology.
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  Data: Embedded systems are widely used in many sophisticated applications. To speed the time-to-market cycle, the hardware and software co-design has become one of the main methodologies in modern embedded systems. The most important challenge in the embedded system design is partitioning; i.e. deciding which modules of the system should be implemented in hardware and which ones in software. Finding an optimal partition is hard because of the large number and different characteristics of the modules that have to be considered. In this article, we develop a new high-level hardware/software partitioning methodology. Two novel features characterize this methodology. Firstly, the Particle Swarm Optimization (PSO) technique is introduced to the Hardware/Software partitioning field. Secondly, the hardware is modeled using two extreme implementations that bound different hardware scheduling alternatives. Our methodology further partitions the design into hardware and software modules at the early Control-Data Flow Graph (CDFG) level of the design; thanks to improved modeling techniques using intermediate-granularity functional modules. A new restarting technique is applied to PSO to avoid quick convergence. This technique is called Re-Excited PSO. Our numerical results prove the usefulness of the proposed technique. The target technology is Field Programmable Gate Arrays (FPGAs). We developed FPGA-based estimation techniques to evaluate the costs of implementing the design components. These costs are the area, delay, latency, and power consumption for both the hardware and software implementations. Hardware/software communication is also taken into consideration. The aforementioned methodology is embodied in an integrated CAD tool for hardware/software co-design. This tool accepts behavioral, un-timed, algorithmic-level, VHDL, design representation, and outputs a valid hardware/software partition and schedule for the design subject to a set of area/power/delay constraints. This tool is code named CUPSHOP for (Cairo University PSo-based Hardware/sOftware Partitioning tool). Finally, a JPEG-encoder case study is used to validate and contrast our partitioning methodology against the prior-art methodologies. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Design Automation for Embedded Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Mar2011
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