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Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

Theo Lasser, Paul James Marchand, Daniel Pawel Szlag, Marcin Antoni Sylwestrzak

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for m ...

Elsevier2017

Contrast measures for predicting perceptual effects of daylight in architectural renderings

Marilyne Andersen, María Lovísa Ámundadóttir, Siobhan Francois Rockcastle

Daylit architecture is perceived as a dynamic luminous composition, yet most existing performance metrics were designed to evaluate natural illumination for its ability to adequately illuminate a two-dimensional task surface and avoid glare-based discomfor ...

SAGE Publications2017

An Accelerator for High Efficient Vision Processing

Paolo Ienne, Robert Fasthuber, Zidong Du, Qi Guo

In recent years, neural network accelerators have been shown to achieve both high energy efficiency and high performance for a broad application scope within the important category of recognition and mining applications. Still, both the energy efficiency a ...

Ieee-Inst Electrical Electronics Engineers Inc2017

An improvement on the number of simplices in F-q(d)

Van Thang Pham

Let epsilon be a set of points in F-q(d). Bennett et al. (2016) proved that if \epsilon\ >> [GRAHICS] then epsilon determines a positive proportion of all k-simplices. In this paper, we give an improvement of this result in the case when epsilon is the Car ...

Elsevier Science Bv2017

Parallelizing the Chambolle Algorithm for Performance Optimized Mapping on FPGA devices

David Atienza Alonso, Abdulkadir Akin, Ivan Beretta, Alessandro Antonio Nacci

The performance and the efficiency of recent computing platforms have been deeply influenced by the widespread adoption of hardware accelerators, such as Graphics Processing Units (GPUs) or Field Programmable Gate Arrays (FPGAs), which are often employed t ...

Assoc Computing Machinery2016

Accelerating Machine Learning with Non-Volatile Memory: exploring device and circuit tradeoffs

Alessandro Fumarola, Severin Sidler

Large arrays of the same nonvolatile memories (NVM) being developed for Storage-Class Memory (SCM) such as Phase Change Memory (PCM) and Resistance RAM (ReRAM) - can also be used in non-Von Neumann neuromorphic computational schemes, with device conductanc ...

Ieee2016

Real-Time Computational Gigapixel Multi-Camera Systems

Vladan Popovic

The standard cameras are designed to truthfully mimic the human eye and the visual system. In recent years, commercially available cameras are becoming more complex, and offer higher image resolutions than ever before. However, the quality of conventional ...

EPFL2016

Interior Tomography Using 1D Generalized Total Variation. Part II: Multiscale Implementation

Michaël Unser, John Paul Ward

To address the classic interior tomography problem where projections at each view extend only to the shadow of a circular region completely interior to the subject being scanned, previously we showed that the exact recovery of two- and three-dimensional pi ...

Siam Publications2015

Enhancing Design Space Exploration by Extending CPU/GPU Specifications onto FPGAs

Andreas Peter Burg, Paolo Ienne, Georgios Karakonstantis, David Novo Bruna, Madhura Purnaprajna, Gabriel Falcao Paiva Fernandes, João Maria Duarte Andrade

The design cycle for complex special-purpose computing systems is extremely costly and time-consuming. It involves a multiparametric design space exploration for optimization, followed by design verification. Designers of special purpose VLSI implementatio ...

Assoc Computing Machinery2015

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