The Experts below are selected from a list of 103605 Experts worldwide ranked by ideXlab platform
Andy D Pimentel - One of the best experts on this subject based on the ideXlab platform.
-
A Hybrid Task Mapping Algorithm for Heterogeneous MPSoCs
ACM Transactions on Embedded Computing Systems, 2015Co-Authors: Wei Quan, Andy D PimentelAbstract:The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems, which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at runtime and improve the efficiency of the underlying system architecture, this article presents a hybrid task Mapping Algorithm that combines a static Mapping exploration and a dynamic Mapping optimization to achieve an overall improvement of system efficiency. We evaluate our Algorithm using a heterogeneous MPSoC system with three real applications. Experimental results reveal the effectiveness of our proposed Algorithm by comparing derived solutions to the ones obtained from several other runtime Mapping Algorithms. In test cases with three simultaneously active applications, the Mapping solutions derived by our approach have average performance improvements ranging from 45.9p to 105.9p and average energy savings ranging from 14.6p to 23.5p.
-
a scenario based run time task Mapping Algorithm for mpsocs
Design Automation Conference, 2013Co-Authors: Wei Quan, Andy D PimentelAbstract:The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at run time and improve the efficiency of the underlying system architecture, this paper presents a novel scenario-based run-time task Mapping Algorithm. This Algorithm combines a static Mapping strategy based on workload scenarios and a dynamic Mapping strategy to achieve an overall improvement of system efficiency. We evaluated our Algorithm using a homogeneous MPSoC system with three real applications. From the results, we found that our Algorithm achieves an 11.3% performance improvement and a 13.9% energy saving compared to running the applications without using any run-time Mapping Algorithm. When comparing our Algorithm to three other, well-known run-time Mapping Algorithms, it is superior to these Algorithms in terms of quality of the Mappings found while also reducing the overheads compared to most of these Algorithms.
-
DAC - A scenario-based run-time task Mapping Algorithm for MPSoCs
Proceedings of the 50th Annual Design Automation Conference on - DAC '13, 2013Co-Authors: Wei Quan, Andy D PimentelAbstract:The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at run time and improve the efficiency of the underlying system architecture, this paper presents a novel scenario-based run-time task Mapping Algorithm. This Algorithm combines a static Mapping strategy based on workload scenarios and a dynamic Mapping strategy to achieve an overall improvement of system efficiency. We evaluated our Algorithm using a homogeneous MPSoC system with three real applications. From the results, we found that our Algorithm achieves an 11.3% performance improvement and a 13.9% energy saving compared to running the applications without using any run-time Mapping Algorithm. When comparing our Algorithm to three other, well-known run-time Mapping Algorithms, it is superior to these Algorithms in terms of quality of the Mappings found while also reducing the overheads compared to most of these Algorithms.
Orly Yadid-pecht - One of the best experts on this subject based on the ideXlab platform.
-
An FPGA implementation of a tone Mapping Algorithm with a halo-reducing filter
Journal of Real-Time Image Processing, 2019Co-Authors: Prasoon Ambalathankandy, Alain Hore, Orly Yadid-pechtAbstract:In this paper, we present a real-time hardware implementation of an exponent-based tone Mapping Algorithm of Horé et al., that uses both local and global image information for improving the contrast and increasing the brightness of tone-mapped images. Although there are several tone Mapping Algorithms available in the literature, most of them require manual tuning of their rendering parameters. However, in our implementation, the Algorithm has an embedded automatic key parameter estimation block that controls the brightness of the tone-mapped images. We also present the implementation of a Gaussian-based halo-reducing filter. The hardware implementation is described in Verilog and synthesized for a field programmable gate array device. Experimental results performed on different wide dynamic range images show that we are able to get images which are of good visual quality and have good brightness and contrast. The good performance of our hardware architecture is also confirmed quantitatively with the high peak signal-to-noise ratio and structural similarity index.
-
ISCAS - Hardware implementation of a real-time tone Mapping Algorithm based on a mantissa-exponent representation
2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016Co-Authors: Ulian Shahnovich, Alain Hore, Orly Yadid-pechtAbstract:This paper presents a hardware implementation of a mantissa/exponent-based tone Mapping Algorithm for wide dynamic range (WDR) images. The Algorithm performs tone Mapping by using a global compression model for the pixel intensities combined with a local contrast enhancement model. The pixel intensities of the WDR images used in this paper are represented in a mantissa/exponent format produced by an innovative WDR imager which takes advantage of a multi-reset technique during the capture process. The Algorithm has been implemented on FPGA and designed to be very small, fast, power-efficient and has the potential to be directly integrated into the same chip as the imager. Experimental results performed by using different images show that our implementation is reliable and efficient.
-
Hardware Implementation of an Automatic Rendering Tone Mapping Algorithm for a Wide Dynamic Range Display
Journal of Low Power Electronics and Applications, 2013Co-Authors: Chika Antoinette Ofili, Stanislav Glozman, Orly Yadid-pechtAbstract:Tone Mapping Algorithms are used to adapt captured wide dynamic range (WDR) scenes to the limited dynamic range of available display devices. Although there are several tone Mapping Algorithms available, most of them require manual tuning of their rendering parameters. In addition, the high complexities of some of these Algorithms make it difficult to implement efficient real-time hardware systems. In this work, a real-time hardware implementation of an exponent-based tone Mapping Algorithm is presented. The Algorithm performs a mixture of both global and local compression on colored WDR images. An automatic parameter selector has been proposed for the tone Mapping Algorithm in order to achieve good tone-mapped images without manual reconfiguration of the Algorithm for each WDR image. Both Algorithms are described in Verilog and synthesized for a field programmable gate array (FPGA). The hardware architecture employs a combination of parallelism and system pipelining, so as to achieve a high performance in power consumption, hardware resources usage and processing speed. Results show that the hardware architecture produces images of good visual quality that can be compared to software-based tone Mapping Algorithms. High peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) scores were obtained when the results were compared with output images obtained from software simulations using MATLAB.
Wei Quan - One of the best experts on this subject based on the ideXlab platform.
-
A Hybrid Task Mapping Algorithm for Heterogeneous MPSoCs
ACM Transactions on Embedded Computing Systems, 2015Co-Authors: Wei Quan, Andy D PimentelAbstract:The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems, which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at runtime and improve the efficiency of the underlying system architecture, this article presents a hybrid task Mapping Algorithm that combines a static Mapping exploration and a dynamic Mapping optimization to achieve an overall improvement of system efficiency. We evaluate our Algorithm using a heterogeneous MPSoC system with three real applications. Experimental results reveal the effectiveness of our proposed Algorithm by comparing derived solutions to the ones obtained from several other runtime Mapping Algorithms. In test cases with three simultaneously active applications, the Mapping solutions derived by our approach have average performance improvements ranging from 45.9p to 105.9p and average energy savings ranging from 14.6p to 23.5p.
-
a scenario based run time task Mapping Algorithm for mpsocs
Design Automation Conference, 2013Co-Authors: Wei Quan, Andy D PimentelAbstract:The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at run time and improve the efficiency of the underlying system architecture, this paper presents a novel scenario-based run-time task Mapping Algorithm. This Algorithm combines a static Mapping strategy based on workload scenarios and a dynamic Mapping strategy to achieve an overall improvement of system efficiency. We evaluated our Algorithm using a homogeneous MPSoC system with three real applications. From the results, we found that our Algorithm achieves an 11.3% performance improvement and a 13.9% energy saving compared to running the applications without using any run-time Mapping Algorithm. When comparing our Algorithm to three other, well-known run-time Mapping Algorithms, it is superior to these Algorithms in terms of quality of the Mappings found while also reducing the overheads compared to most of these Algorithms.
-
DAC - A scenario-based run-time task Mapping Algorithm for MPSoCs
Proceedings of the 50th Annual Design Automation Conference on - DAC '13, 2013Co-Authors: Wei Quan, Andy D PimentelAbstract:The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at run time and improve the efficiency of the underlying system architecture, this paper presents a novel scenario-based run-time task Mapping Algorithm. This Algorithm combines a static Mapping strategy based on workload scenarios and a dynamic Mapping strategy to achieve an overall improvement of system efficiency. We evaluated our Algorithm using a homogeneous MPSoC system with three real applications. From the results, we found that our Algorithm achieves an 11.3% performance improvement and a 13.9% energy saving compared to running the applications without using any run-time Mapping Algorithm. When comparing our Algorithm to three other, well-known run-time Mapping Algorithms, it is superior to these Algorithms in terms of quality of the Mappings found while also reducing the overheads compared to most of these Algorithms.
Yanfei Zhong - One of the best experts on this subject based on the ideXlab platform.
-
a new sub pixel Mapping Algorithm based on a bp neural network with an observation model
Neurocomputing, 2008Co-Authors: Liangpei Zhang, Yanfei ZhongAbstract:The mixed pixel is a common problem in remote sensing classification. Even though the composition of these pixels for different classes can be estimated with a pixel un-mixing model, the output provides no indication of how such classes are distributed spatially within these pixels. Sub-pixel Mapping is a technique designed to use the output information with the assumption of spatial dependence to obtain a sharpened image. Pixels are divided into sub-pixels, representing the land cover class fractions. This paper proposes a new Algorithm based on a back-propagation (BP) network combined with an observation model. This method provides an effective method of obtaining the sub-pixel Mapping result and can provide an approximation of the reference classification image. With the upscale factor, the model was tested on both a simple artificial image and a remote sensing image, and the results confirm that the proposed Mapping Algorithm has better performance than the original BPNN model.
Liangpei Zhang - One of the best experts on this subject based on the ideXlab platform.
-
a new sub pixel Mapping Algorithm based on a bp neural network with an observation model
Neurocomputing, 2008Co-Authors: Liangpei Zhang, Yanfei ZhongAbstract:The mixed pixel is a common problem in remote sensing classification. Even though the composition of these pixels for different classes can be estimated with a pixel un-mixing model, the output provides no indication of how such classes are distributed spatially within these pixels. Sub-pixel Mapping is a technique designed to use the output information with the assumption of spatial dependence to obtain a sharpened image. Pixels are divided into sub-pixels, representing the land cover class fractions. This paper proposes a new Algorithm based on a back-propagation (BP) network combined with an observation model. This method provides an effective method of obtaining the sub-pixel Mapping result and can provide an approximation of the reference classification image. With the upscale factor, the model was tested on both a simple artificial image and a remote sensing image, and the results confirm that the proposed Mapping Algorithm has better performance than the original BPNN model.