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Algorithm and architecture co-optimization

Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP


In the 1960s, Marshall McLuhan published the book entitled, The Extensions of Man focusing primarily on television, an electronic media as being the outward extension of human nervous system, which from contemporary interpretation marks the previous stage of Big Data.

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Authors:
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia
Submitted On:
23 February 2016 - 1:44pm
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GlobalSIPS 2015 Panel Discussion Presentation.pdf

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[1] Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia, "Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/569. Accessed: Nov. 17, 2019.
@article{569-15,
url = {http://sigport.org/569},
author = {Lee Barford; Paul Blinzer; Joe Cavallaro; Hong; Jiang; Nick Moore; Yinglong Xia },
publisher = {IEEE SigPort},
title = {Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP},
year = {2015} }
TY - EJOUR
T1 - Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP
AU - Lee Barford; Paul Blinzer; Joe Cavallaro; Hong; Jiang; Nick Moore; Yinglong Xia
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/569
ER -
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia. (2015). Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP. IEEE SigPort. http://sigport.org/569
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia, 2015. Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP. Available at: http://sigport.org/569.
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia. (2015). "Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP." Web.
1. Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia. Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/569

Programmable Data Parallel Accelerator for Mobile Computer Vision

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Authors:
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela
Submitted On:
23 February 2016 - 1:44pm
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globalsip_tta.pdf

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[1] Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela, "Programmable Data Parallel Accelerator for Mobile Computer Vision", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/361. Accessed: Nov. 17, 2019.
@article{361-15,
url = {http://sigport.org/361},
author = {Teemu Nyländen; Ilkka Hautala; Olli Silvén; Jari Hannuksela },
publisher = {IEEE SigPort},
title = {Programmable Data Parallel Accelerator for Mobile Computer Vision},
year = {2015} }
TY - EJOUR
T1 - Programmable Data Parallel Accelerator for Mobile Computer Vision
AU - Teemu Nyländen; Ilkka Hautala; Olli Silvén; Jari Hannuksela
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/361
ER -
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela. (2015). Programmable Data Parallel Accelerator for Mobile Computer Vision. IEEE SigPort. http://sigport.org/361
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela, 2015. Programmable Data Parallel Accelerator for Mobile Computer Vision. Available at: http://sigport.org/361.
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela. (2015). "Programmable Data Parallel Accelerator for Mobile Computer Vision." Web.
1. Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela. Programmable Data Parallel Accelerator for Mobile Computer Vision [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/361

Practical Optimization Algorithms for Image Processing


Several problems in signal processing and machine learning can be casted as optimization problems. In many cases, they are of large-scale, nonlinear, have constraints, and nonsmooth in the unknown parameters. There exists plethora of fast algorithms for smooth convex optimization, but these algorithms are not readily applicable to nonsmooth problems, which has led to a considerable amount of research in this direction. In this paper, we propose a general algorithm for nonsmooth bound-constrained convex optimization problems.

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Authors:
Loic Denis, Eric Thiebaut, J-M Becker
Submitted On:
23 February 2016 - 1:43pm
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posterICIP.pdf

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[1] Loic Denis, Eric Thiebaut, J-M Becker, "Practical Optimization Algorithms for Image Processing", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/223. Accessed: Nov. 17, 2019.
@article{223-15,
url = {http://sigport.org/223},
author = {Loic Denis; Eric Thiebaut; J-M Becker },
publisher = {IEEE SigPort},
title = {Practical Optimization Algorithms for Image Processing},
year = {2015} }
TY - EJOUR
T1 - Practical Optimization Algorithms for Image Processing
AU - Loic Denis; Eric Thiebaut; J-M Becker
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/223
ER -
Loic Denis, Eric Thiebaut, J-M Becker. (2015). Practical Optimization Algorithms for Image Processing. IEEE SigPort. http://sigport.org/223
Loic Denis, Eric Thiebaut, J-M Becker, 2015. Practical Optimization Algorithms for Image Processing. Available at: http://sigport.org/223.
Loic Denis, Eric Thiebaut, J-M Becker. (2015). "Practical Optimization Algorithms for Image Processing." Web.
1. Loic Denis, Eric Thiebaut, J-M Becker. Practical Optimization Algorithms for Image Processing [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/223

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