The Experts below are selected from a list of 74616 Experts worldwide ranked by ideXlab platform
Christophe Calvin - One of the best experts on this subject based on the ideXlab platform.
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competing energy lookup algorithms in monte carlo neutron transport calculations and their optimization on cpu and intel mic architectures
Journal of Computational Science, 2017Co-Authors: Yunsong Wang, Emeric Brun, Fausto Malvagi, Christophe CalvinAbstract:Abstract The Monte Carlo method is a common and accurate way to model neutron transport with minimal approximations. However, such method is rather time-consuming due to its slow convergence rate. More specifically, the energy lookup process for cross sections can take up to 80% of overall computing time and therefore becomes an important performance hot-spot. Several optimization solutions have been already proposed: unionized grid, hashing and fractional cascading methods. In this paper we revisit those algorithms for both CPU and Many Integrated Core (MIC) architectures and introduce Vectorized versions. Tests are performed with the PATMOS Monte Carlo prototype, and algorithms are evaluated and compared in terms of time performance and memory usage. Results show that significant speedup can be achieved over the conventional binary search on both CPU and MIC. Using Vectorization instructions has been proved efficient on manycore architecture due to its 512-bit Vector Processing Unit (VPU); on CPU this improvement is limited by the smaller VPU width. Further optimization like memory reduction turns out to be very important since it largely improves computing performance.
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competing energy lookup algorithms in monte carlo neutron transport calculations and their optimization on cpu and intel mic architectures
International Conference on Conceptual Structures, 2016Co-Authors: Yunsong Wang, Emeric Brun, Fausto Malvagi, Christophe CalvinAbstract:Abstract The Monte Carlo method is a common and accurate way to model neutron transport with minimal approximations. However, such method is rather time-consuming due to its slow convergence rate. More specifically, the energy lookup process for cross sections can take up to 80% of overall computing time and therefore becomes an important performance hotspot. Several optimization solutions have been already proposed: unionized grid, hashing and fractional cascading methods. In this paper we revisit those algorithms for both CPU and manycore (Intel MIC) architectures and introduce Vectorized versions. Tests are performed with the PATMOS Monte Carlo prototype, and algorithms are evaluated and compared in terms of time performance and memory usage. Results show that significant speedup can be achieved over the conventional binary search on both CPU and Intel MIC. Further optimization with Vectorization instructions has been proved very efficient on Intel MIC architecture due to its 512-bit Vector Processing Unit (VPU); on CPU this improvement is limited by the smaller VPU width.
T Q Nguyen - One of the best experts on this subject based on the ideXlab platform.
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correlation based motion Vector Processing with adaptive interpolation scheme for motion compensated frame interpolation
IEEE Transactions on Image Processing, 2009Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, we address the problems of unreliable motion Vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion Vector Processing method is proposed to detect and correct those unreliable motion Vectors by explicitly considering motion Vector correlation in the motion Vector reliability classification, motion Vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion Vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.
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motion Vector Processing using bidirectional frame difference in motion compensated frame interpolation
World of Wireless Mobile and Multimedia Networks, 2008Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, we address the potential issues in bidirectional motion compensated frame interpolation when the received motion Vector field is directly used. Based on this motion Vector analysis, we therefore propose using bidirectional motion Vector Processing method to eliminate the ghost artifacts around the moving objects. The artifacts caused by large motion Vector magnitude can be effectively removed by correcting motion Vectors bidirectionally. Moreover, since the proposed motion Vector selection process chooses the best motion Vector from adjacent motion Vectors, the computational complexity can be greatly reduced comparing to motion estimation. We also demonstrate how to obtain clearer object edges by allowing displacement adjustment during the bidirectional motion Vector Processing. Experimental results show that the proposed algorithm outperforms other methods in terms of visual quality.
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A Multistage Motion Vector Processing Method for Motion-Compensated Frame Interpolation
IEEE Transactions on Image Processing, 2008Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, a novel, low-complexity motion Vector Processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion Vectors on different block sizes. Our method explicitly considers the reliability of each received motion Vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion Vectors. The motion Vector reliability information is also used as a prior knowledge in motion Vector refinement using a constrained Vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.
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a novel multi stage motion Vector Processing method for motion compensated frame interpolation
International Conference on Image Processing, 2007Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, a novel multi-stage motion Vector Processing algorithm at the decoder is proposed for motion compensated frame interpolation. We address the problems of discontinuous edges and deformed structures in an interpolated frame by explicitly considering reliability of each received motion Vector. By hierarchically refining motion Vectors with different block sizes, the proposed method is capable of preserving structure information. Experimental results show that the proposed scheme outperforms other methods in terms of visual quality and PSNR, and it is also robust when video sequences have complex scenes and fast motion.
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motion Vector Processing for frame rate up conversion
International Conference on Acoustics Speech and Signal Processing, 2004Co-Authors: G Dane, T Q NguyenAbstract:In this paper, the effect of motion Vector accuracy on the efficiency of motion compensated frame rate up conversion (MC-FRUC) is studied. The motion Vector Processing problem is formulated and analyzed via motion Vector modelling. A Processing scheme is proposed to improve the interpolated frame quality at the decoder. The practical application of integrating the motion Vector Processing algorithm in a standard H.263 decoder for MC-FRUC is also discussed. Experimental results show that a 0.4-0.6 dB gain in the H.263 codec, and a 0.5-2 dB gain in off-line frame rate conversion can be obtained by the proposed algorithm.
Yunsong Wang - One of the best experts on this subject based on the ideXlab platform.
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competing energy lookup algorithms in monte carlo neutron transport calculations and their optimization on cpu and intel mic architectures
Journal of Computational Science, 2017Co-Authors: Yunsong Wang, Emeric Brun, Fausto Malvagi, Christophe CalvinAbstract:Abstract The Monte Carlo method is a common and accurate way to model neutron transport with minimal approximations. However, such method is rather time-consuming due to its slow convergence rate. More specifically, the energy lookup process for cross sections can take up to 80% of overall computing time and therefore becomes an important performance hot-spot. Several optimization solutions have been already proposed: unionized grid, hashing and fractional cascading methods. In this paper we revisit those algorithms for both CPU and Many Integrated Core (MIC) architectures and introduce Vectorized versions. Tests are performed with the PATMOS Monte Carlo prototype, and algorithms are evaluated and compared in terms of time performance and memory usage. Results show that significant speedup can be achieved over the conventional binary search on both CPU and MIC. Using Vectorization instructions has been proved efficient on manycore architecture due to its 512-bit Vector Processing Unit (VPU); on CPU this improvement is limited by the smaller VPU width. Further optimization like memory reduction turns out to be very important since it largely improves computing performance.
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competing energy lookup algorithms in monte carlo neutron transport calculations and their optimization on cpu and intel mic architectures
International Conference on Conceptual Structures, 2016Co-Authors: Yunsong Wang, Emeric Brun, Fausto Malvagi, Christophe CalvinAbstract:Abstract The Monte Carlo method is a common and accurate way to model neutron transport with minimal approximations. However, such method is rather time-consuming due to its slow convergence rate. More specifically, the energy lookup process for cross sections can take up to 80% of overall computing time and therefore becomes an important performance hotspot. Several optimization solutions have been already proposed: unionized grid, hashing and fractional cascading methods. In this paper we revisit those algorithms for both CPU and manycore (Intel MIC) architectures and introduce Vectorized versions. Tests are performed with the PATMOS Monte Carlo prototype, and algorithms are evaluated and compared in terms of time performance and memory usage. Results show that significant speedup can be achieved over the conventional binary search on both CPU and Intel MIC. Further optimization with Vectorization instructions has been proved very efficient on Intel MIC architecture due to its 512-bit Vector Processing Unit (VPU); on CPU this improvement is limited by the smaller VPU width.
Ai-mei Huang - One of the best experts on this subject based on the ideXlab platform.
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correlation based motion Vector Processing with adaptive interpolation scheme for motion compensated frame interpolation
IEEE Transactions on Image Processing, 2009Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, we address the problems of unreliable motion Vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion Vector Processing method is proposed to detect and correct those unreliable motion Vectors by explicitly considering motion Vector correlation in the motion Vector reliability classification, motion Vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion Vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.
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motion Vector Processing using bidirectional frame difference in motion compensated frame interpolation
World of Wireless Mobile and Multimedia Networks, 2008Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, we address the potential issues in bidirectional motion compensated frame interpolation when the received motion Vector field is directly used. Based on this motion Vector analysis, we therefore propose using bidirectional motion Vector Processing method to eliminate the ghost artifacts around the moving objects. The artifacts caused by large motion Vector magnitude can be effectively removed by correcting motion Vectors bidirectionally. Moreover, since the proposed motion Vector selection process chooses the best motion Vector from adjacent motion Vectors, the computational complexity can be greatly reduced comparing to motion estimation. We also demonstrate how to obtain clearer object edges by allowing displacement adjustment during the bidirectional motion Vector Processing. Experimental results show that the proposed algorithm outperforms other methods in terms of visual quality.
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A Multistage Motion Vector Processing Method for Motion-Compensated Frame Interpolation
IEEE Transactions on Image Processing, 2008Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, a novel, low-complexity motion Vector Processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion Vectors on different block sizes. Our method explicitly considers the reliability of each received motion Vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion Vectors. The motion Vector reliability information is also used as a prior knowledge in motion Vector refinement using a constrained Vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.
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a novel multi stage motion Vector Processing method for motion compensated frame interpolation
International Conference on Image Processing, 2007Co-Authors: Ai-mei Huang, T Q NguyenAbstract:In this paper, a novel multi-stage motion Vector Processing algorithm at the decoder is proposed for motion compensated frame interpolation. We address the problems of discontinuous edges and deformed structures in an interpolated frame by explicitly considering reliability of each received motion Vector. By hierarchically refining motion Vectors with different block sizes, the proposed method is capable of preserving structure information. Experimental results show that the proposed scheme outperforms other methods in terms of visual quality and PSNR, and it is also robust when video sequences have complex scenes and fast motion.
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Motion Vector Processing Based on Residual Energy Information for Motion Compensated Frame Interpolation
2006 International Conference on Image Processing, 2006Co-Authors: Ai-mei Huang, Truong NguyenAbstract:In this paper, we address the problem of motion compensated frame interpolation (MCFI) at the decoder by analyzing received motion Vectors (MVs) and residual error. In the proposed method, the skipped frames are generated at the decoder by using received information from the bitstream. We combine a hierarchical motion Vector correction algorithm and a residual-energy constrained median filter to obtain true motion. Experimental results show that the proposed motion Vector Processing algorithm improves the visual quality of interpolated frames, especially in the motion transition area and the motion boundary.
Emeric Brun - One of the best experts on this subject based on the ideXlab platform.
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competing energy lookup algorithms in monte carlo neutron transport calculations and their optimization on cpu and intel mic architectures
Journal of Computational Science, 2017Co-Authors: Yunsong Wang, Emeric Brun, Fausto Malvagi, Christophe CalvinAbstract:Abstract The Monte Carlo method is a common and accurate way to model neutron transport with minimal approximations. However, such method is rather time-consuming due to its slow convergence rate. More specifically, the energy lookup process for cross sections can take up to 80% of overall computing time and therefore becomes an important performance hot-spot. Several optimization solutions have been already proposed: unionized grid, hashing and fractional cascading methods. In this paper we revisit those algorithms for both CPU and Many Integrated Core (MIC) architectures and introduce Vectorized versions. Tests are performed with the PATMOS Monte Carlo prototype, and algorithms are evaluated and compared in terms of time performance and memory usage. Results show that significant speedup can be achieved over the conventional binary search on both CPU and MIC. Using Vectorization instructions has been proved efficient on manycore architecture due to its 512-bit Vector Processing Unit (VPU); on CPU this improvement is limited by the smaller VPU width. Further optimization like memory reduction turns out to be very important since it largely improves computing performance.
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competing energy lookup algorithms in monte carlo neutron transport calculations and their optimization on cpu and intel mic architectures
International Conference on Conceptual Structures, 2016Co-Authors: Yunsong Wang, Emeric Brun, Fausto Malvagi, Christophe CalvinAbstract:Abstract The Monte Carlo method is a common and accurate way to model neutron transport with minimal approximations. However, such method is rather time-consuming due to its slow convergence rate. More specifically, the energy lookup process for cross sections can take up to 80% of overall computing time and therefore becomes an important performance hotspot. Several optimization solutions have been already proposed: unionized grid, hashing and fractional cascading methods. In this paper we revisit those algorithms for both CPU and manycore (Intel MIC) architectures and introduce Vectorized versions. Tests are performed with the PATMOS Monte Carlo prototype, and algorithms are evaluated and compared in terms of time performance and memory usage. Results show that significant speedup can be achieved over the conventional binary search on both CPU and Intel MIC. Further optimization with Vectorization instructions has been proved very efficient on Intel MIC architecture due to its 512-bit Vector Processing Unit (VPU); on CPU this improvement is limited by the smaller VPU width.
