USSR: An UltraSound Sparse Regularization framework

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Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel, Florian Martinez, Marcel Arditi

Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution of the image reconstruction problem. An alternative to DAS consists in using iterative techniques which require both an a ...

2017

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

Parallel Inverse Kinematics for Multithreaded Architectures

Ronan Boulic, Benoît Le Callennec, Mentar Mahmudi, Pawan Kumar Harish

In this article, we present a parallel prioritized Jacobian-based inverse kinematics algorithm for multithreaded architectures. We solve damped least squares inverse kinematics using a parallel line search by identifying and sampling critical input paramet ...

Association for Computing Machinery2016

Characterization of the Impact of Hardware Islands on OLTP

Anastasia Ailamaki, Miguel Sérgio De Oliveira Branco, Pinar Tözün, Danica Porobic, Ippokratis Pandis

Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database sys ...

Springer Verlag2016

Automated Classification of Data Races Under Both Strong and Weak Memory Models

George Candea, Cristian Zamfir, Baris Can Cengiz Kasikci

Data races are one of the main causes of concurrency problems in multithreaded programs. Whether all data races are bad, or some are harmful and others are harmless, is still the subject of vigorous scientific debate [Narayanasamy et al. 2007; Boehm 2012]. ...

Assoc Computing Machinery2015

GPU Acceleration for Simulating Massively Parallel Many-Core Platforms

David Atienza Alonso, Luca Benini, Martino Ruggiero, Shivani Raghav

Emerging massively parallel architectures such as a general-purpose processor plus many-core programmable accelerators are creating an increasing demand for novel methods to perform their architectural simulation. Most state-of-the-art simulation technolog ...

Institute of Electrical and Electronics Engineers2015

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

Transactions Chasing Scalability and Instruction Locality on Multicores

Pinar Tözün

For several decades, online transaction processing (OLTP) has been one of the main server applications that drives innovations in the data management ecosystem, and in turn the database and computer architecture communities. Recent hardware trends oblige s ...

EPFL2014

Scalable Simulation Methodologies for Many-Core Heterogeneous Systems

Shivani Raghav

With increasing complexity and performance demands of emerging compute-intensive data-parallel workloads, many-core computing systems are becoming a popular trend in computer design. Fast and scalable simulation methods are needed to make meaningful predic ...

EPFL2014

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