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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Georgios Smaragdos Danish Anis Khan Ioannis Sourdis Christos Strydis Alirad Malek Stavros Tzilis Neuroscience dept. Erasmus University Medical Center The Netherlands Computer Science and Engineering dept. Chalmers University of Technology Sweden

Recent trends in semiconductor technology have dictated the constant reduction of device size. One negative effect stemming from the reduction in size and increased complexity is the reduced device reliability. This paper is centered around the matter of permanent fault tolerance and graceful system degradation in the presence of permanent faults. We take advantage of the natural redundancy of homogeneous multicores following a sparing strategy to reuse functional pipeline stages of faulty cores. This is done by incorporating reconfigurable interconnects next to which the cores of the system are placed, providing the flexibility to redirect the data-flow from the faulty pipeline stages of damaged cores to spare (still) functional ones. Several micro-architectural changes are introduced to decouple the processor stages and allow them to be interchangeable. The proposed approach is a clear departure from previous ones by offering full flexibility as well as highly graceful performance degradation at reasonable costs. More specifically, our coarsegrain fault tolerant multicore array provides up to ×4 better availability compared to a conventional multicore and up to ×2 higher probability to deliver at least one functioning core in high fault densities. For our benchmarks, our design (synthesized for STM 65nm SP technology) incurs a total execution-time overhead for the complete system ranging from ×1.37 to ×3.3 compared to a (baseline) non-fault-tolerant system, depending on the permanent-fault density. The area overhead is 19.5% and the energy consumption, without incorporating any power/energy- saving technique, is estimated on average to be 20.9% higher compared to the baseline, unprotected design.

关键词： Pipelines Multicore processing Delays Wires Fault tolerance Fault tolerant systems Registers

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Galaxy clusters selected via the Sunyaev-Zel’dovich effect in the SPTpol 100-Square-Degree survey

arXiv

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arXiv 2019年

作者： Huang, N. Bleem, L.E. Stalder, B. Ade, P.A.R. Allen, S.W. Anderson, A.J. Austermann, J.E. Avva, J.S. Beall, J.A. Bender, A.N. Benson, B.A. Bianchini, F. Bocquet, S. Brodwin, M. Carlstrom, J.E. Chang, C.L. Chiang, H.C. Citron, R. Corbett Moran, C. Crawford, T.M. Crites, A.T. de Haan, T. Dobbs, M.A. Everett, W. Floyd, B. Gallicchio, J. George, E.M. Gilbert, A. Gladders, M.D. Guns, S. Gupta, N. Halverson, N.W. Harrington, N. Henning, J.W. Hilton, G.C. Holder, G.P. Holzapfel, W.L. Hrubes, J.D. Hubmayr, J. Irwin, K.D. Khullar, G. Knox, L. Lee, A.T. Li, D. Lowitz, A. McDonald, M. McMahon, J.J. Meyer, S.S. Mocanu, L.M. Montgomery, J. Nadolski, A. Natoli, T. Nibarger, J.P. Noble, G. Novosad, V. Padin, S. Patil, S. Pryke, C. Reichardt, C.L. Ruhl, J.E. Saliwanchik, B.R. Saro, A. Sayre, J.T. Schaffer, K.K. Sharon, K. Sievers, C. Smecher, G. Stark, A.A. Story, K.T. Tucker, C. Vanderlinde, K. Veach, T. Vieira, J.D. Wang, G. Whitehorn, N. Wu, W.L.K. Department of Physics University of California BerkeleyCA94720 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States LSST 950 N Cherry Ave TucsonAZ United States Cardiff University CardiffCF10 3XQ United Kingdom Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall StanfordCA94305 United States Department of Physics Stanford University 382 Via Pueblo Mall StanfordCA94305 United States SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo ParkCA94025 United States Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Department of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 München81679 Germany Department of Physics and Astronomy University of Missouri 5110 Rockhill Road Kansas CityMO64110 United States Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics McGill University 3600 Rue University MontrealQCH3A 2T8 Canada School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Durban South Africa University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States TAPIR Walter Burke Institute for Theoretical Physics California Institute of Technology 1200 E California Blvd PasadenaCA91125 United States California Institute of Technology MS 249-17 1216 E. California Blvd. PasadenaCA91125

We present a catalog of galaxy cluster candidates detected in 100 square degrees surveyed with the SPTpol receiver on the South Pole Telescope. The catalog contains 89 candidates detected with a signal-to-noise ratio greater than 4.6. The candidates are selected using the Sunyaev-Zel’dovich effect at 95 and 150 GHz. Using both space- and ground-based optical and infrared telescopes, we have confirmed 81 candidates as galaxy clusters. We use these follow-up images and archival images to estimate photometric redshifts for 66 galaxy clusters and spectroscopic observations to obtain redshifts for 13 systems. An additional 2 galaxy clusters are confirmed using the overdensity of near-infrared galaxies only, and are presented without redshifts. We find that 15 candidates (18% of the total sample) are at redshift of z ≥ 1.0, with a maximum confirmed redshift of zmax = 1.38 ± 0.10. We expect this catalog to contain every galaxy cluster with M500c > 2.6×1014M☉h−701 and z > 0.25 in the survey area. The mass threshold is approximately constant above z = 0.25, and the complete catalog has a median mass of approximately M500c = 2.7 × 1014M☉h−701. Compared to previous SPT works, the increased dept. of the millimeter-wave data (11.2 and 6.5 µK-arcmin at 95 and 150 GHz, respectively) makes it possible to find more galaxy clusters at high redshift and lower mass. Copyright © 2019, The Authors. All rights reserved.

关键词： Infrared devices

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Dark Energy Survey year 1 results: Joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions

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Physical Review D 2019年第2期100卷 023541-023541页

作者： T. M. C. Abbott F. B. Abdalla A. Alarcon S. Allam J. Annis S. Avila K. Aylor M. Banerji N. Banik E. J. Baxter K. Bechtol M. R. Becker B. A. Benson G. M. Bernstein E. Bertin F. Bianchini J. Blazek L. E. Bleem S. L. Bridle D. Brooks E. Buckley-Geer D. L. Burke J. E. Carlstrom A. Carnero Rosell M. Carrasco Kind J. Carretero F. J. Castander R. Cawthon C. Chang C. L. Chang H-M. Cho A. Choi R. Chown T. M. Crawford A. T. Crites M. Crocce C. E. Cunha C. B. D’Andrea L. N. da Costa C. Davis T. de Haan J. DeRose S. Desai J. De Vicente H. T. Diehl J. P. Dietrich M. A. Dobbs S. Dodelson P. Doel A. Drlica-Wagner T. F. Eifler J. Elvin-Poole W. B. Everett B. Flaugher P. Fosalba O. Friedrich J. Frieman J. García-Bellido M. Gatti E. Gaztanaga E. M. George D. W. Gerdes T. Giannantonio D. Gruen R. A. Gruendl J. Gschwend G. Gutierrez N. W. Halverson N. L. Harrington W. G. Hartley G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid Z. Hou B. Hoyle J. D. Hrubes D. Huterer B. Jain D. J. James M. Jarvis T. Jeltema M. W. G. Johnson M. D. Johnson S. Kent D. Kirk L. Knox N. Kokron E. Krause K. Kuehn O. Lahav A. T. Lee E. M. Leitch T. S. Li M. Lima H. Lin D. Luong-Van N. MacCrann M. A. G. Maia A. Manzotti D. P. Marrone J. L. Marshall P. Martini J. J. McMahon F. Menanteau S. S. Meyer R. Miquel L. M. Mocanu J. J. Mohr J. Muir T. Natoli A. Nicola B. Nord Y. Omori S. Padin S. Pandey A. A. Plazas A. Porredon J. Prat C. Pryke M. M. Rau C. L. Reichardt R. P. Rollins A. K. Romer A. Roodman A. J. Ross E. Rozo J. E. Ruhl E. S. Rykoff S. Samuroff C. Sánchez E. Sanchez J. T. Sayre V. Scarpine K. K. Schaffer L. F. Secco S. Serrano I. Sevilla-Noarbe E. Sheldon E. Shirokoff G. Simard M. Smith M. Soares-Santos F. Sobreira Z. Staniszewski A. A. Stark K. T. Story E. Suchyta M. E. C. Swanson G. Tarle D. Thomas M. A. Troxel D. L. Tucker K. Vanderlinde J. D. Vieira P. Vielzeuf V. Vikram A. R. Walker R. H. Wechsler J. Weller R. Williamson W. L. K. Wu B. Yanny O. Zahn Y. Zhang J. Zuntz Cerro Tololo Inter-American Observatory National Optical Astronomy Observatory Casilla 603 La Serena Chile Department of Physics & Astronomy University College London Gower Street London WC1E 6BT United Kingdom Department of Physics and Electronics Rhodes University P.O. Box 94 Grahamstown 6140 South Africa Institut d’Estudis Espacials de Catalunya (IEEC) 08193 Barcelona Spain Institute of Space Sciences (ICE CSIC) Campus UAB Carrer de Can Magrans s/n 08193 Barcelona Spain Fermi National Accelerator Laboratory P.O. Box 500 Batavia Illinois 60510 USA Institute of Cosmology & Gravitation University of Portsmouth Portsmouth PO1 3FX United Kingdom Department of Physics University of California Davis California 95616 USA Institute of Astronomy University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Department of Physics and Astronomy University of Pennsylvania Philadelphia Pennsylvania 19104 USA LSST 933 North Cherry Avenue Tucson Arizona 85721 USA Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Astronomy and Astrophysics University of Chicago Chicago Illinois 60637 USA CNRS UMR 7095 Institut d’Astrophysique de Paris F-75014 Paris France Sorbonne Universités UPMC Univ Paris 06 UMR 7095 Institut d’Astrophysique de Paris F-75014 Paris France School of Physics University of Melbourne Parkville VIC 3010 Australia Center for Cosmology and Astro-Particle Physics The Ohio State University Columbus Ohio 43210 USA Institute of Physics Laboratory of Astrophysics École Polytechnique Fédérale de Lausanne (EPFL) Observatoire de Sauverny 1290 Versoix Switzerland High Energy Physics Division Argonne National Laboratory Argonne Illinois 60439 USA Jodrell Bank Center for Astrophysics School of Physic

We perform a joint analysis of the auto and cross-correlations between three cosmic fields: the galaxy density field, the galaxy weak lensing shear field, and the cosmic microwave background (CMB) weak lensing convergence field. These three fields are measured using roughly 1300 sq. deg. of overlapping optical imaging data from first year observations of the Dark Energy Survey (DES) and millimeter-wave observations of the CMB from both the South Pole Telescope Sunyaev-Zel’dovich survey and Planck. We present cosmological constraints from the joint analysis of the two-point correlation functions between galaxy density and galaxy shear with CMB lensing. We test for consistency between these measurements and the DES-only two-point function measurements, finding no evidence for inconsistency in the context of flat ΛCDM cosmological models. Performing a joint analysis of five of the possible correlation functions between these fields (excluding only the CMB lensing autospectrum) yields S8≡σ8Ωm/0.3=0.782−0.025+0.019 and Ωm=0.260−0.019+0.029. We test for consistency between these five correlation function measurements and the Planck-only measurement of the CMB lensing autospectrum, again finding no evidence for inconsistency in the context of flat ΛCDM models. Combining constraints from all six two-point functions yields S8=0.776−0.021+0.014 and Ωm=0.271−0.016+0.022. These results provide a powerful test and confirmation of the results from the first year DES joint-probes analysis.

关键词： Cosmic microwave background Cosmological parameters Evolution of the Universe Large scale structure of the Universe

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Characterizing the performance-energy tradeoff of small ARM Cores in HPC computation 1

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20th International Conference on Parallel Processing, Euro-Par 2014

作者： Laurenzano, Michael A. Tiwari, Ananta Jundt, Adam Peraza, Joshua Ward Jr., William A. Campbell, Roy Carrington, Laura EP Analytics United States Dept. of Computer Science and Engineering University of Michigan United States Performance Modeling and Characterization Lab San Diego Supercomputer Center United States High Performance Computing Modernization Program U.S. Dept. of Defense United States

ISBN: (数字)9783319098739

ISBN: (纸本)9783319098722

Deploying large numbers of small, low-power cores has been gaining traction recently as a system design strategy in high performance computing (HPC). The ARM platform that dominates the embedded and mobile computing segments is now being considered as an alternative to high-end x86 processors that largely dominate HPC because peak performance per watt may be substantially improved using off-the-shelf commodity processors. In this work we methodically characterize the performance and energy of HPC computations drawn from a number of problem domains on current ARM and x86 processors. Unsurprisingly, we find that the performance, energy and energy-delay product of applications running on these platforms varies significantly across problem types and inputs. Using static program analysis we further show that this variation can be explained largely in terms of the capabilities of two processor subsystems: single instruction multiple data (SIMD)/floating point and the cache/memory hierarchy;and that static analysis of this kind is sufficient to predict which platform is best for a particular application/input pair. In the context of these findings, we evaluate how some of the key architectural changes being made for upcoming 64-bit ARM platforms may impact HPC application performance. © 2014 Springer International Publishing Switzerland.

关键词： Static analysis

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Whitening 1/f-type noise in electroencephalogram signals for steady-state visual evoked potential brain-computer interfaces

Whitening 1/f-type noise in electroencephalogram signals for...

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Asilomar Conference on Signals, Systems & computers

作者： Alan Paris Azadeh Vosoughi George Atia Modeling and Simulation Program Dept. of Electrical Engineering and Computer Science University of Central Florida

A method is proposed to whiten 1-f-type background noise in electroencephalogram data by a nonlinear spectral transformation from the frequency domain to a newly-defined ∝-pitch domain. Based on the α-pitch spectra of steady-state visual evoked potentials, an algorithm called octave-averaged spectral rectification is applied which simultaneously attenuates 1-f noise while enhancing resonance peaks. This has important potential benefits for gamma-band brain-computer interfaces.

关键词： Decision support systems Visualization Noise

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Knowledge-based search and multi-objective filters: Proposed structural models of GPCR dimerization 14

Knowledge-based search and multi-objective filters: Proposed...

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5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB 2014

作者： Hashmi, Irina Veltri, Daniel Kabbani, Nadine Shehu, Amarda Dept. of Computer Science George Mason University FairfaxVA22030 United States School of Systems Biology George Mason University ManassasVA20110 United States Dept. of Molecular Neuroscience Krasnow Institute George Mason University FairfaxVA22030 United States Dept. of Bioengineering School of Systems Biology George Mason University FairfaxVA22030 United States

ISBN: (纸本)9781450328944

Many experimental studies point to the ubiquitous role of protein complexation in the cell while lamenting the lack of structural models to permit structure-function studies. This scarcity is due to persisting challenges in protein-protein docking. Methods based on energetic optimization have to handle vast and high-dimensional configuration spaces and inaccurate energy functions only to arrive at the wrong interface. Methods that employ learned models to replace or precede energetic evaluations are limited by the generality of these models. Computational approaches designed to be general often fail to provide realistic models on protein classes of interest in the wet laboratory. One such class are G protein-coupled receptors, which wet-lab studies suggest undergo complexation, possibly affecting drug efficacy. In this paper, we propose a computational protocol to ad- dress the unique challenges posed by these receptors. To deal with challenges, such as receptor size and inaccuracy of energy functions, the protocol takes a geometry-driven approach and integrates in the search geometric constraints posed by the environment where the receptors operate. Various filters are designed to handle the computational cost of energetic evaluation, and analysis techniques based on new scoring strategies, including multi-objective analysis, are employed to reduce the sampled ensemble to a few credible structural models. We demonstrate that dimeric models of the Dopamine D2 receptor targeted to treat psychotic disorders reproduce macroscopic knowledge extracted in the wet-laboratory and can be employed to further spur detailed structure-function studies. Copyright © 2014 ACM.

关键词： Geometry

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An analysis of conformational changes upon RNA-Protein binding 14

An analysis of conformational changes upon RNA-Protein bindi...

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5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB 2014

作者： Sankar, Kannan Jernigan, Robert L. Walia, Rasna R. Honavar, Vasant G. Mann, Carla M. Dobbs, Drena Bioinformatics and Computational Biology Program Dept. of Biochem. Biophysics and Molecular Biology Iowa State University United States Dept. of Biochem. L.H. Baker Center for Bioinformatics and Biological Statistics Iowa State University United States Bioinformatics and Computational Biology Program Dept. of Computer Science Iowa State University United States Bioinformatics and Genomics Program College of Information Sciences and Technology Pennsylvania State University United States Dept. of Genetics Development and Cell Biology L.H. Baker Center for Bioinformatics Iowa State University United States

ISBN: (纸本)9781450328944

RNA-binding proteins (RBPs) have myriad functions in transcription, translation, and post-transcriptional gene regulation, with central roles in normal development as well as in both genetic and infectious diseases. When a protein binds RNA, a conformational change often occurs. For RNA-protein complexes that have been characterized, conformational changes have been observed in the protein, the RNA, or both. These conformational changes have not been sufficiently characterized, however, in part due to the small number of structures of bound and unbound complexes of RNA-binding proteins available until recently. Here we systematically analyze a new dataset of 90 pairs of bound and unbound proteins to evaluate the conformational changes that occur upon RNA binding. Most of the conformational changes were observed in noninterfacial regions of the RNA-binding proteins. Detailed analyses of the modes of RNA binding and any associated conformational changes in proteins are critical for fully understanding the mechanisms of RNA-protein recognition, for developing better RNA-protein docking methods and methods for predicting interfacial residues, and for RNA-based drug design. Copyright © 2014 ACM.

关键词： RNA

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Identifying drug (cocaine) intake events from acute physiological response in the presence of free-living physical activity

Identifying drug (cocaine) intake events from acute physiolo...

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International Symposium on Information Processing in Sensor Networks (IPSN)

作者： Syed Monowar Hossain Amin Ahsan Ali Md. Mahbubur Rahman Emre Ertine David Epstein Ashley Kennedy Kenzie Preston Annie Umbricht Yixin Chen Santosh Kumar Dept. of Computer Science University of Memphis Dept of Electrical & Computer Engineering Ohio State University NIDA Intramural Research Program Dept. of Psychiatry and Behavioral Sciences Johns Hopkins University Dept of Computer Science and Engg. Washington University in St. Louise

A variety of health and behavioral states can potentially be inferred from physiological measurements that can now be collected in the natural free-living environment. The major challenge, however, is to develop computational models for automated detection of health events that can work reliably in the natural field environment. In this paper, we develop a physiologically-informed model to automatically detect drug (cocaine) use events in the free-living environment of participants from their electrocardiogram (ECG) measurements. The key to reliably detecting drug use events in the field is to incorporate the knowledge of autonomic nervous system (ANS) behavior in the model development so as to decompose the activation effect of cocaine from the natural recovery behavior of the parasympathetic nervous system (after an episode of physical activity). We collect 89 days of data from 9 active drug users in two residential lab environments and 922 days of data from 42 active drug users in the field environment, for a total of 11,283 hours. We develop a model that tracks the natural recovery by the parasympathetic nervous system and then estimates the dampening caused to the recovery by the activation of the sympathetic nervous system due to cocaine. We develop efficient methods to screen and clean the ECG time series data and extract candidate windows to assess for potential drug use. We then apply our model on the recovery segments from these windows. Our model achieves 100% true positive rate while keeping the false positive rate to 0.87/day over (9+ hours/day of) lab data and to 1.13/day over (11+ hours/day of) field data.

关键词： Drugs Sensors Electrocardiography Physiology Data models Heart rate Reliability

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Stiffness assessment of carotid artery via portable B-mode ultrasound imager

Stiffness assessment of carotid artery via portable B-mode u...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Chun-Chieh Huang An-Bang Liu Wei-Min Liu Dept. of Computer Science and Information Engineering National Chung-Cheng University Taiwan Neuroscience Center Hualien Tzu Chi Hospital Taiwan

The arterial vessel stiffness is one of the major factors to determine the vascular health, and only can be measured in the professional institutions. We propose an image processing workflow to analyze the common carotid artery (CCA) ultrasound (US) image series collected from a portable US scanner. The temporal variability of CCA lumen is quantified by approximate entropy. Its reproducibility under different data-dependent variables is also studied. In the future such technique can be integrated into mobile devices equipped with US probes, and become easily accessible to the general public.

关键词： Ultrasonic imaging Image segmentation Carotid arteries Biomedical monitoring Ultrasonic variables measurement Probes

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Automatic classification of Alzheimer's disease with resting-state fMRI and graph theory

Automatic classification of Alzheimer's disease with resting...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Ali Khazaee Ataollah Ebrahimzadeh Abbas Babajani-Feremi dept. of Electrical and Computer Engineering Babol (Noshirvani) University of Technology Babol Iran dept. of Pediatrics University of Tennessee Health Science Center Neuroscience Institute Le Bonheur Children's Hospital Memphis USA

Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. After preprocessing of data, signals from 90 brain regions, segmented based on the automated anatomical labeling (AAL) atlas, were extracted and edges of the graph were calculated using the correlation between the signals of all pairs of the brain regions. Then a weighted undirected graph was constructed and graph measures were calculated. Fisher score feature selection algorithm were employed to choose most significant features. Finally, using the selected features, we were able to accurately classify patients with AD from healthy control ones with accuracy of 97.5%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD.

关键词： Classification algorithms Support vector machines Accuracy Feature extraction Alzheimer's disease Biomedical measurement

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