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  • 151.
    Peng, Ivy Bo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Data Movement on Emerging Large-Scale Parallel Systems2017Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [sv]

    Storskaliga HPC-system är en viktig drivkraft för att lösa datorproblem i vetenskapliga samhällen. Nästa generations HPC-system kommer inte bara att växa i skala utan också i heterogenitet. Denna ökade systemkomplexitet medför flera utmaningar för dataförflyttning i HPC-applikationer. Dataförflyttning på nya HPC-system kräver asynkron, finkorrigerad kommunikation och en effektiv dataplacering i huvudminnet.

    Denna avhandling föreslår en innovativ programmeringsmodell och algoritm för att förbereda HPC-applikationer för nästa generation: (1) en dataströmningsmodell som stöder nya dataintensiva applikationer på superdatorer, (2) en kopplingsmodell som förbättrar parallelliteten och minskar obalans i applikationer, (3) en ny metologi och struktur för att förutse effekten av storskaliga, heterogena minnessystem på HPC-applikationer, och (4) en datalägesalgoritm som använder en uppsättning av regler och ett beslutsträd för att bestämma kartläggningen av data-till-minnet i det heterogena huvudminnet.

    Den föreslagna programmeringsmodellen i denna avhandling är utvärderad på flera superdatorer med olika processorer och sammankopplingsnät. Utvärderingen använder en mängd olika applikationer som representerar konventionella vetenskapliga applikationer och nya dataanalyser på HPC-system. Experimentella resultat på testbädden i petascala visar att programmeringsmodellen förbättrar prestandan när systemskalan ökar. Denna trend indikerar att modellen är ett värdefullt bidrag till framtida HPC-system.

  • 152.
    Peng, Ivy Bo
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Gioiosa, Roberto
    Kestor, Gokcen
    Cicotti, Pietro
    Laure, Erwin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    RTHMS: A Tool for Data Placement on Hybrid Memory System2017Ingår i: ACM SIGPLAN NOTICES, ASSOC COMPUTING MACHINERY , 2017, Vol. 52, nr 9, s. 82-91Konferensbidrag (Refereegranskat)
    Abstract [en]

    Traditional scientific and emerging data analytics applications require fast, power-efficient, large, and persistent memories. Combining all these characteristics within a single memory technology is expensive and hence future supercomputers will feature different memory technologies side-by-side. However, it is a complex task to program hybrid-memory systems and to identify the best object-to-memory mapping. We envision that programmers will probably resort to use default configurations that only require minimal interventions on the application code or system settings. In this work, we argue that intelligent, fine-grained data placement can achieve higher performance than default setups. We present an algorithm for data placement on hybrid-memory systems. Our algorithm is based on a set of single-object allocation rules and global data placement decisions. We also present RTHMS, a tool that implements our algorithm and provides recommendations about the object-to-memory mapping. Our experiments on a hybrid memory system, an Intel Knights Landing processor with DRAM and HBM, show that RTHMS is able to achieve higher performance than the default configuration. We believe that RTHMS will be a valuable tool for programmers working on complex hybrid-memory systems.

  • 153.
    Peng, Ivy Bo
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Gioiosa, Roberto
    Kestor, Gokcen
    Laure, Erwin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Preparing HPC Applications for the Exascale Era: A Decoupling Strategy2017Ingår i: 2017 46th International Conference on Parallel Processing (ICPP), Institute of Electrical and Electronics Engineers (IEEE), 2017, artikel-id 8025274Konferensbidrag (Refereegranskat)
    Abstract [en]

    Production-quality parallel applications are often a mixture of diverse operations, such as computation- and communication-intensive, regular and irregular, tightly coupled and loosely linked operations. In conventional construction of parallel applications, each process performs all the operations, which might result inefficient and seriously limit scalability, especially at large scale. We propose a decoupling strategy to improve the scalability of applications running on large-scale systems. Our strategy separates application operations onto groups of processes and enables a dataflow processing paradigm among the groups. This mechanism is effective in reducing the impact of load imbalance and increases the parallel efficiency by pipelining multiple operations. We provide a proof-of-concept implementation using MPI, the de-facto programming system on current supercomputers. We demonstrate the effectiveness of this strategy by decoupling the reduce, particle communication, halo exchange and I/O operations in a set of scientific and data-analytics applications. A performance evaluation on 8,192 processes of a Cray XC40 supercomputer shows that the proposed approach can achieve up to 4x performance improvement.

  • 154.
    Peng, Ivy Bo
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Laure, Erwin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Holmes, D.
    Bull, M.
    A Data streaming model in MPI2015Ingår i: Proceedings of the 3rd ExaMPI Workshop at the International Conference on High Performance Computing, Networking, Storage and Analysis, SC 2015, ACM Digital Library, 2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    Data streaming model is an effective way to tackle the chal-lenge of data-intensive applications. As traditional HPC applications generate large volume of data and more data-intensive applications move to HPC infrastructures, it is nec-essary to investigate the feasibility of combining message-passing and streaming programming models. MPI, the de facto standard for programming on HPC, cannot intuitively express the communication pattern and the functional op-erations required in streaming models. In this work, we de-signed and implemented a data streaming library MPIStream atop MPI to allocate data producers and consumers, to stream data continuously or irregularly and to process data at run-Time. In the same spirit as the STREAM benchmark, we developed a parallel stream benchmark to measure data processing rate. The performance of the library largely de-pends on the size of the stream element, the number of data producers and consumers and the computational intensity of processing one stream element. With 2,048 data produc-ers and 2,048 data consumers in the parallel benchmark, MPIStream achieved 200 GB/s processing rate on a Blue Gene/Q supercomputer. We illustrate that a streaming li-brary for HPC applications can effectively enable irregular parallel I/O, application monitoring and threshold collective operations. © 2015 ACM.

  • 155.
    Peters, Christopher
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Doggett, Michael
    Foreword to special section on SIGGRAD 20152016Ingår i: Computers & graphics, ISSN 0097-8493, E-ISSN 1873-7684, Vol. 57, s. A1-A2Artikel i tidskrift (Refereegranskat)
  • 156. Piccinini, Filippo
    et al.
    Balassa, Tamas
    Szkalisity, Abel
    Molnar, Csaba
    Paavolainen, Lassi
    Kujala, Kaisa
    Buzas, Krisztina
    Sarazova, Marie
    Pietiainen, Vilja
    Kutay, Ulrike
    Smith, Kevin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Horvath, Peter
    Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data2017Ingår i: CELL SYSTEMS, ISSN 2405-4712, Vol. 4, nr 6, s. 651-+Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org.

  • 157.
    Rivas-Gomez, Sergio
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Peng, Ivy Bo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Laure, E.
    Kestor, G.
    Gioiosa, R.
    Extending message passing interface windows to storage2017Ingår i: Proceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017, Institute of Electrical and Electronics Engineers Inc. , 2017, s. 728-730Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents an extension to MPI supporting the one-sided communication model and window allocations in storage. Our design transparently integrates with the current MPI implementations, enabling applications to target MPI windows in storage, memory or both simultaneously, without major modifications. Initial performance results demonstrate that the presented MPI window extension could potentially be helpful for a wide-range of use-cases and with low-overhead.

  • 158.
    Romero, Mario
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    A Case Study in Expo-Based Learning Applied to Information Visualization2015Ingår i: SIGRAD 2015 / [ed] L. Kjelldahl and C. Peters, Linköping University Electronic Press, 2015, , s. 4Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present preliminary results of the effect of Expo-Based Learning (EBL) applied to a course on information visualization. We define EBL as project-based learning (PBL) augmented with constructively-aligned large public demos [RTP14]. In this paper, we analyze the results of challenging and grading enrolled students to compete and present their projects publicly at an open student competition organized by a second university. We surveyed the students at the end of the course before the competition started and the end of the competition. We present the result of the impact of the student competition as it relates to the intended learning outcomes from the perspective of the students.

  • 159.
    Romero, Mario
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Georgia Institute of Technology.
    Flat is the New Pitch-Black: Discussing Blind use of Touchscreens2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    The increasingly ubiquitous touchscreen, from the smart phone to the treadmill, is a significant hurdle for blind individuals who cannot rely on their sense of touch for decoding its interface. Advances in smart phone screen readers, such as the iPhone’s Voice Over, have enabled blind users to effectively navigate touchscreens. While Voice Over efficiently outputs information, text input remained a challenge. To address this, we previously introduced BrailleTouch, a soft braille keyboard for efficient blind text entry on touchscreens. In this position paper, we present the tailored touch-based user experience design and evaluation techniques we developed for BrailleTouch which we have not previously discussed.

  • 160.
    Romero, Mario
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Andrée, Jonas
    Peters, Christopher
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Thuresson, Björn
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Designing and Evaluating Embodied Sculpting: a Touching Experience2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    We discuss the design and evaluation of embodied sculpting, the mediated experience of creating a virtual object with volume which users can see, hear, and touch as they mold the material with their body. Users’ digitized bodies share the virtual space of the digital model through a depth-sensor camera. They can use their hands, bodies, or any object to shape the sculpture. As they mold the model, they see a real-time rendering of it and receive sound and haptic feedback of the interaction. We discuss the opportunities and challenges of both designing for haptic embodiment and evaluating it through haptic experimentation.

  • 161.
    Romero, Mario
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Georgia Institute of Technology.
    Björn, ThuressonKTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).Peters, ChristopherKTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).Landazuri, Natalia
    Expo-Based Learning (EBL): Augmenting Project-Based Learning with Large Public Presentations2015Proceedings (redaktörskap) (Refereegranskat)
  • 162.
    Romero, Mario
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Thuresson, Björn
    KTH, Skolan för datavetenskap och kommunikation (CSC), High Performance Computing and Visualization (HPCViz).
    Peters, Christopher
    KTH, Skolan för datavetenskap och kommunikation (CSC), High Performance Computing and Visualization (HPCViz).
    Kis, Filip
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Coppard, J.
    Andrée, Jenny
    KTH.
    Landázuri, N.
    Augmenting PBL with large public presentations: A case study in interactive graphics pedagogy2014Ingår i: ITICSE 2014 - Proceedings of the 2014 Innovation and Technology in Computer Science Education Conference, 2014, s. 15-20Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a case study analyzing and discussing the effects of introducing the requirement of public outreach of original student work into the project-based learning of Advanced Graphics and Interaction (AGI) at KTH Royal Institute of Technology. We propose Expo-Based Learning as Project-Based Learning augmented with the constructively aligned goal of achieving public outreach beyond the course. We promote this outreach through three challenges: 1) large public presentations; 2) multidisciplinary collaboration; and 3) professional portfolio building. We demonstrate that the introduction of these challenges, especially the public presentations, had lasting positive impact in the intended technical learning outcomes of AGI with the added benefit of learning team work, presentation skills, timeliness, accountability, self-motivation, technical expertise, and professionalism.

  • 163. Sahasranamam, Ajith
    et al.
    Vlachos, Ioannis
    Aertsen, Ad
    Kumar, Arvind
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.
    Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity2016Ingår i: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, artikel-id 26029Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.

  • 164.
    Sahlin, Kristoffer
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Frånberg, M.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). KTH, Centra, SeRC - Swedish e-Science Research Centre. Stockholm University, Sweden.
    Structural Variation Detection with Read Pair Information: An Improved Null Hypothesis Reduces Bias2017Ingår i: Journal of Computational Biology, ISSN 1066-5277, E-ISSN 1557-8666, Vol. 24, nr 6, s. 581-589Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reads from paired-end and mate-pair libraries are often utilized to find structural variation in genomes, and one common approach is to use their fragment length for detection. After aligning read pairs to the reference, read pair distances are analyzed for statistically significant deviations. However, previously proposed methods are based on a simplified model of observed fragment lengths that does not agree with data. We show how this model limits statistical analysis of identifying variants and propose a new model by adapting a model we have previously introduced for contig scaffolding, which agrees with data. From this model, we derive an improved null hypothesis that when applied in the variant caller CLEVER, reduces the number of false positives and corrects a bias that contributes to more deletion calls than insertion calls. We advise developers of variant callers with statistical fragment length-based methods to adapt the concepts in our proposed model and null hypothesis.

  • 165.
    Saikia, Himangshu
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Comparison and Tracking Methods for Interactive Visualization of Topological Structures in Scalar Fields2017Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Scalar fields occur quite commonly in several application areas in both static and time-dependent forms. Hence a proper visualization of scalar fieldsneeds to be equipped with tools to extract and focus on important features of the data. Similarity detection and pattern search techniques in scalar fields present a useful way of visualizing important features in the data. This is done by isolating these features and visualizing them independently or show all similar patterns that arise from a given search pattern. Topological features are ideal for this purpose of isolating meaningful patterns in the data set and creating intuitive feature descriptors. The Merge Tree is one such topological feature which has characteristics ideally suited for this purpose. Subtrees of merge trees segment the data into hierarchical regions which are topologically defined. This kind of feature-based segmentation is more intelligent than pure data based segmentations involving windows or bounding volumes. In this thesis, we explore several different techniques using subtrees of merge trees as features in scalar field data. Firstly, we begin with a discussion on static scalar fields and devise techniques to compare features - topologically segmented regions given by the subtrees of the merge tree - against each other. Second, we delve into time-dependent scalar fields and extend the idea of feature comparison to spatio-temporal features. In this process, we also come up with a novel approach to track features in time-dependent data considering the entire global network of likely feature associations between consecutive time steps.The highlight of this thesis is the interactivity that is enabled using these feature-based techniques by the real-time computation speed of our algorithms. Our techniques are implemented in an open-source visualization framework Inviwo and are published in several peer-reviewed conferences and journals.

  • 166.
    Saikia, Himangshu
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    Seidel, H. -P
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    Extended Branch Decomposition Graphs: Structural Comparison of Scalar Data2014Ingår i: Computer Graphics Forum (Proc. EuroVis), ISSN 1467-8659, Vol. 33, nr 3, s. 41-50Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a method to find repeating topological structures in scalar data sets. More precisely, we compare all subtrees of two merge trees against each other - in an efficient manner exploiting redundancy. This provides pair-wise distances between the topological structures defined by sub/superlevel sets, which can be exploited in several applications such as finding similar structures in the same data set, assessing periodic behavior in time-dependent data, and comparing the topology of two different data sets. To do so, we introduce a novel data structure called the extended branch decomposition graph, which is composed of the branch decompositions of all subtrees of the merge tree. Based on dynamic programming, we provide two highly efficient algorithms for computing and comparing extended branch decomposition graphs. Several applications attest to the utility of our method and its robustness against noise.

  • 167.
    Saikia, Himangshu
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Seidel, Hans-Peter
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Fast Similarity Search in Scalar Fields using Merging Histograms2015Ingår i: Topological Methods in Data Analysis and Visualization IV: Theory, Algorithms, and Applications, Springer, 2015, s. 121-134Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Similarity estimation in scalar fields using level set topology has attracted a lot of attention in the recent past. Most existing techniques match parts of contour or merge trees against each other by estimating a best overlap between them. Due to their combinatorial nature, these methods can be computationally expensive or prone to instabilities. In this paper, we use an inexpensive feature descriptor to compare subtrees of merge trees against each other. It is the data histogram of the voxels encompassed by a subtree. A small modification of the merge tree computation algorithm allows for obtaining these histograms very efficiently. Furthermore, the descriptor is robust against instabilities in the merge tree. The method is useful in an interactive environment, where a user can search for all structures similar to an interactively selected one. Our method is conservative in the sense that it finds all similar structures, with the rare occurrence of some false positives. We show with several examples the effectiveness, efficiency and accuracy of our method.

  • 168.
    Saikia, Himangshu
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Fast Topology-based Feature Tracking using a Directed Acyclic GraphManuskript (preprint) (Övrigt vetenskapligt)
  • 169.
    Saikia, Himangshu
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Global Feature Tracking and Similarity Estimation in Time-Dependent Scalar Fields2017Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 36, nr 3, s. 1-11Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present an algorithm for tracking regions in time-dependent scalar fields that uses global knowledge from all time steps for determining the tracks. The regions are defined using merge trees, thereby representing a hierarchical segmentation of the data in each time step. The similarity of regions of two consecutive time steps is measured using their volumetric overlap and a histogram difference. The main ingredient of our method is a directed acyclic graph that records all relevant similarity information as follows: the regions of all time steps are the nodes of the graph, the edges represent possible short feature tracks between consecutive time steps, and the edge weights are given by the similarity of the connected regions. We compute a feature track as the global solution of a shortest path problem in the graph. We use these results to steer the - to the best of our knowledge - first algorithm for spatio-temporal feature similarity estimation. Our algorithm works for 2D and 3D time-dependent scalar fields. We compare our results to previous work, showcase its robustness to noise, and exemplify its utility using several real-world data sets.

  • 170. Schulze, M.
    et al.
    Esturo, J. Martinez
    Günther, T.
    Rössl, C.
    Seidel, H. -P
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    Theisel, H.
    Sets of Globally Optimal Stream Surfaces for Flow Visualization2014Ingår i: Computer Graphics Forum (Proc. EuroVis), ISSN 1467-8659, Vol. 33, nr 3, s. 1-10Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Stream surfaces are a well-studied and widely used tool for the visualization of 3D flow fields. Usually, stream surface seeding is carried out manually in time-consuming trial and error procedures. Only recently automatic selection methods were proposed. Local methods support the selection of a set of stream surfaces, but, contrary to global selection methods, they evaluate only the quality of the seeding lines but not the quality of the whole stream surfaces. Global methods, on the other hand, only support the selection of a single optimal stream surface until now. However, for certain flow fields a single stream surface is not sufficient to represent all flow features. In our work, we overcome this limitation by introducing a global selection technique for a set of stream surfaces. All selected surfaces optimize global stream surface quality measures and are guaranteed to be mutually distant, such that they can convey different flow features. Our approach is an efficient extension of the most recent global selection method for single stream surfaces. We illustrate its effectiveness on a number of analytical and simulated flow fields and analyze the quality of the results in a user study.

  • 171. Spreizer, Sebastian
    et al.
    Angelhuber, Martin
    Bahuguna, Jyotika
    Aertsen, Ad
    Kumar, Arvind
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity2017Ingår i: eNeuro, ISSN 2373-2822Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The striatum is the main input nucleus of the basal ganglia. Characterizing striatal activity dynamics is crucial to understanding mechanisms underlying action-selection, -initiation and -execution. Here, we studied the effects of spatial network connectivity on the spatio-temporal structure of striatal activity. We show that a striatal network with non-monotonically changing distance-dependent connectivity (according to a Gamma distribution) can exhibit a wide repertoire of spatio-temporal dynamics, ranging from spatially homogeneous asynchronous-irregular (AI) activity to a state with stable, spatially localized activity bumps, as in ‘winner-take-all’ (WTA) dynamics. Among these regimes, the unstable activity bumps (Transition Activity, TA) regime closely resembles the experimentally observed spatio-temporal activity dynamics and neuronal assemblies in the striatum. By contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can only exhibit an AI state. Thus, given the observation of spatially compact neuronal clusters in the striatum, our model suggests that recurrent connectivity among striatal projection neurons should vary non-monotonically. In brain disorders such as Parkinson’s disease, increased cortical inputs and high striatal firing rates are associated with a reduction in stimulus sensitivity. Consistent with this, our model suggests that strong cortical inputs drive the striatum to a WTA state, leading to low stimulus sensitivity and high variability. By contrast, the AI and TA states show high stimulus sensitivity and reliability. Thus, based on these results, we propose that in a healthy state the striatum operates in a AI/TA state and that lack of dopamine pushes it into a WTA state.Significance Statement Recent findings suggest that striatal activity is organized in spatially compact neuron clusters. Here, we show that striatal projection neurons should have a non-monotonically changing distance-dependent connectivity to obtain spatially localized activity patterns in striatum. Among the different states a striatal network can show, asynchronous-irregular and transition activity states closely resemble striatal activity in the healthy state. By contrast, strong cortical inputs as observed in Parkinson’s disease (PD) drive the network into a winner-take-all state, in which the striatum looses its stimulus sensitivity. Thus, our model makes specific predictions about the spatial network connectivity in the striatum and provides new insights about how the striatum might make a transition from a healthy state to a PD state.

  • 172.
    Spühler, Jeannette H.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Niclas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hoffman, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    3D Fluid-Structure Interaction Simulation of Aortic Valves Using a Unified Continuum ALE FEM Model2018Ingår i: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, artikel-id 363Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Due to advances in medical imaging, computational fluid dynamics algorithms and high performance computing, computer simulation is developing into an important tool for understanding the relationship between cardiovascular diseases and intraventricular blood flow. The field of cardiac flow simulation is challenging and highly interdisciplinary. We apply a computational framework for automated solutions of partial differential equations using Finite Element Methods where any mathematical description directly can be translated to code. This allows us to develop a cardiac model where specific properties of the heart such as fluid-structure interaction of the aortic valve can be added in a modular way without extensive efforts. In previous work, we simulated the blood flow in the left ventricle of the heart. In this paper, we extend this model by placing prototypes of both a native and a mechanical aortic valve in the outflow region of the left ventricle. Numerical simulation of the blood flow in the vicinity of the valve offers the possibility to improve the treatment of aortic valve diseases as aortic stenosis (narrowing of the valve opening) or regurgitation (leaking) and to optimize the design of prosthetic heart valves in a controlled and specific way. The fluid-structure interaction and contact problem are formulated in a unified continuum model using the conservation laws for mass and momentum and a phase function. The discretization is based on an Arbitrary Lagrangian-Eulerian space-time finite element method with streamline diffusion stabilization, and it is implemented in the open source software Unicorn which shows near optimal scaling up to thousands of cores. Computational results are presented to demonstrate the capability of our framework.

  • 173.
    Spühler, Jeannette Hiromi
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Patient-Specific Finite Element Modeling of the Blood Flow in the Left Ventricle of a Human Heart2017Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Heart disease is the leading cause of death in the world. Therefore, numerous studies are undertaken to identify indicators which can be applied to discover cardiac dysfunctions at an early age. Among others, the fluid dynamics of the blood flow (hemodymanics) is considered to contain relevant information related to abnormal performance of the heart.This thesis presents a robust framework for numerical simulation of the fluid dynamics of the blood flow in the left ventricle of a human heart and the fluid-structure interaction of the blood and the aortic leaflets.We first describe a patient-specific model for simulating the intraventricular blood flow. The motion of the endocardial wall is extracted from data acquired with medical imaging and we use the incompressible Navier-Stokes equations to model the hemodynamics within the chamber. We set boundary conditions to model the opening and closing of the mitral and aortic valves respectively, and we apply a stabilized Arbitrary Lagrangian-Eulerian (ALE) space-time finite element method to simulate the blood flow. Even though it is difficult to collect in-vivo data for validation, the available data and results from other simulation models indicate that our approach possesses the potential and capability to provide relevant information about the intraventricular blood flow.To further demonstrate the robustness and clinical feasibility of our model, a semi-automatic pathway from 4D cardiac ultrasound imaging to patient-specific simulation of the blood flow in the left ventricle is developed. The outcome is promising and further simulations and analysis of large data sets are planned.In order to enhance our solver by introducing additional features, the fluid solver is extended by embedding different geometrical prototypes of both a native and a mechanical aortic valve in the outflow area of the left ventricle.Both, the contact as well as the fluid-structure interaction, are modeled as a unified continuum problem using conservation laws for mass and momentum. To use this ansatz for simulating the valvular dynamics is unique and has the expedient properties that the whole problem can be described with partial different equations and the same numerical methods for discretization are applicable.All algorithms are implemented in the high performance computing branch of Unicorn, which is part of the open source software framework FEniCS-HPC. The strong advantage of implementing the solvers in an open source software is the accessibility and reproducibility of the results which enhance the prospects of developing a method with clinical relevance.

  • 174.
    Spühler, Jeannette Hiromi
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Degirmenci, Niyazi Cem
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hoffman, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    A 3D full-friction contact model for fluid-structure interaction problemsManuskript (preprint) (Övrigt vetenskapligt)
  • 175.
    Spühler, Jeannette Hiromi
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Niclas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hoffman, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    3D Fluid-Structure Interaction Simulation of Aortic Valves Using a Unified Continuum ALE-FEM ModelManuskript (preprint) (Övrigt vetenskapligt)
  • 176.
    Spühler, Jeannette Hiromi
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). BCAM - Basque Center for Applied Mathematics, Spain.
    Jansson, Niclas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hoffman, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). BCAM - Basque Center for Applied Mathematics, Spain.
    A finite element framework for high performance computer simulation of blood flow in the left ventricle of the human heart2015Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Progress in medical imaging, computational fluid dynamics and high performance computing (HPC) enables computer simulations to emerge as a significant tool to enhance our understanding of the relationship between cardiac diseases and hemodynamics. The field of cardiac modelling is diverse, covering different aspects on microscopic and macroscopic level. In our research, we develop a cardiac model which is embedded in a computational environment where specific properties of the heart such as fluid-structure interaction of the aortic valve can be modeled, or numerical and computational algorithms as parallel computing or adaptivity can be added in a modular way without extensive efforts. In this paper, we present a patient-specific Arbitrary Lagrangian-Eulerian (ALE) finite element framework for simulating the blood flow in the left ventricle of a human heart using HPC, which forms the core of our cardiac model. The mathematical model is described together with the discretization method, mesh smoothing algorithms, and the parallel implementation in Unicorn which is part of the open source software framework FEniCS-HPC. The parallel performance is demonstrated, a convergence study is conducted and intraventricular flow patterns are visualized. The results capture essential features observed with other computational models and imaging techniques, and thus indicate that our framework possesses the potential to provide relevant clinical information for diagnosis and medical treatment. Several studies have been conducted to simulate the three dimensional blood flow in the left ventricle of the human heart with prescribed wall movement. Our contribution to the field of cardiac research lies in establishing an open source framework modular both in modelling and numerical algorithms.

  • 177. Stöter, T.
    et al.
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    Seidel, H. -P
    Theisel, H.
    Implicit Integral Surfaces2012Ingår i: Proc. Vision, Modeling and Visualization, 2012, s. 127-134Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present an implicit method for globally computing all four classic types of integral surfaces – stream, path, streak, and time surfaces – in 3D time-dependent vector fields. Our novel formulation is based on the representation of a time surface as implicit isosurface of a 3D scalar function advected by the flow field. The evolution of a time surface is then given as an isovolume in 4D space-time spanned by a series of advected scalar functions. Based on this, the other three integral surfaces are described as the intersection of two isovolumes derived from different scalar functions. Our method uses a dense flow integration to compute integral surfaces globally in the entire domain. This allows to change the seeding structure efficiently by simply defining new isovalues. We propose two rendering methods that exploit the implicit nature of our integral surfaces: 4D raycasting, and projection into a 3D volume. Furthermore, we present a marching cubes inspired surface extraction method to convert the implicit surface representation to an explicit triangle mesh. In contrast to previous approaches for implicit stream surfaces, our method allows for multiple voxel intersections, covers all regions of the flow field, and provides full control over the seeding line within the entire domain.

  • 178.
    Sweeney, Yann
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). School of Informatics, University of Edinburgh, UK.
    Functional Relevance of Homeostatic Intrinsic Plasticity in Neurons and Networks2016Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    Maintaining the intrinsic excitability of neurons is crucial for stable brain activity. This can be achieved by the homeostatic regulation of membrane ion channel conductances, although it is not well understood how these processes influence broader aspects of neuron and network function. One of the many mechanisms which contribute towards this task is the modulation of potassium channel conductances by activity-dependent nitric oxide signalling. Here, we first investigate this mechanism in a conductance-based neuron model. By fitting the model to experimental data we find that nitric oxide signalling improves synaptic transmission fidelity at high firing rates, but that there is an increase in the metabolic cost of action potentials associated with this improvement. Although the improvement in function had been observed previously in experiment, the metabolic constraint was unknown. This additional constraint provides a plausible explanation for the selective activation of nitric oxide signalling only at high firing rates. In addition to mediating homeostatic control of intrinsic excitability, nitric oxide can diffuse freely across cell membranes, providing a unique mechanism for neurons to communicate within a network, independent of synaptic connectivity. We next conduct a theoretical investigation of the distinguishing roles of diffusive homeostasis mediated by nitric oxide in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis robustly maintain stable activity. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that diffusive homeostasis interferes less than non-diffusive homeostasis in the synaptic weight dynamics of networks undergoing Hebbian plasticity. Overall, these results suggest a novel homeostatic mechanism for maintaining stable network activity while simultaneously minimising metabolic cost and conserving network functionality.

  • 179. Szalisznyó, K.
    et al.
    Silverstein, David
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Karolinska Institutet, Sweden.
    Teichmann, M.
    Duffau, H.
    Smits, A.
    Cortico-striatal language pathways dynamically adjust for syntactic complexity: A computational study2017Ingår i: Brain and Language, ISSN 0093-934X, E-ISSN 1090-2155, Vol. 164, s. 53-62Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity.

  • 180.
    Thoman, Peter
    et al.
    Univ Innsbruck, A-6020 Innsbruck, Austria..
    Dichev, Kiril
    Queens Univ Belfast, Belfast BT7 1NN, Antrim, North Ireland..
    Heller, Thomas
    Univ Erlangen Nurnberg, D-91058 Erlangen, Germany..
    Iakymchuk, Roman
    KTH.
    Aguilar, Xavier
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hasanov, Khalid
    IBM Ireland, Dublin 15, Ireland..
    Gschwandtner, Philipp
    Univ Innsbruck, A-6020 Innsbruck, Austria..
    Lemarinier, Pierre
    IBM Ireland, Dublin 15, Ireland..
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jordan, Herbert
    Univ Innsbruck, A-6020 Innsbruck, Austria..
    Fahringer, Thomas
    Univ Innsbruck, A-6020 Innsbruck, Austria..
    Katrinis, Kostas
    IBM Ireland, Dublin 15, Ireland..
    Laure, Erwin
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Centra, Parallelldatorcentrum, PDC.
    Nikolopoulos, Dimitrios S.
    Queens Univ Belfast, Belfast BT7 1NN, Antrim, North Ireland..
    A taxonomy of task-based parallel programming technologies for high-performance computing2018Ingår i: Journal of Supercomputing, ISSN 0920-8542, E-ISSN 1573-0484, Vol. 74, nr 4, s. 1422-1434Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Task-based programming models for shared memory-such as Cilk Plus and OpenMP 3-are well established and documented. However, with the increase in parallel, many-core, and heterogeneous systems, a number of research-driven projects have developed more diversified task-based support, employing various programming and runtime features. Unfortunately, despite the fact that dozens of different task-based systems exist today and are actively used for parallel and high-performance computing (HPC), no comprehensive overview or classification of task-based technologies for HPC exists. In this paper, we provide an initial task-focused taxonomy for HPC technologies, which covers both programming interfaces and runtime mechanisms. We demonstrate the usefulness of our taxonomy by classifying state-of-the-art task-based environments in use today.

  • 181. Toth, Gabor
    et al.
    Jia, Xianzhe
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Peng, Ivy Bo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Chen, Yuxi
    Daldorff, Lars K. S.
    Tenishev, Valeriy M.
    Borovikov, Dmitry
    Haiducek, John D.
    Gombosi, Tamas I.
    Glocer, Alex
    Dorelli, John C.
    Extended magnetohydrodynamics with embedded particle-in-cell simulation of Ganymede's magnetosphere2016Ingår i: Journal of Geophysical Research - Space Physics, ISSN 2169-9380, E-ISSN 2169-9402, Vol. 121, nr 2, s. 1273-1293Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We have recently developed a new modeling capability to embed the implicit particle-in-cell (PIC) model iPIC3D into the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme magnetohydrodynamic (MHD) model. The MHD with embedded PIC domains (MHD-EPIC) algorithm is a two-way coupled kinetic-fluid model. As one of the very first applications of the MHD-EPIC algorithm, we simulate the interaction between Jupiter's magnetospheric plasma and Ganymede's magnetosphere. We compare the MHD-EPIC simulations with pure Hall MHD simulations and compare both model results with Galileo observations to assess the importance of kinetic effects in controlling the configuration and dynamics of Ganymede's magnetosphere. We find that the Hall MHD and MHD-EPIC solutions are qualitatively similar, but there are significant quantitative differences. In particular, the density and pressure inside the magnetosphere show different distributions. For our baseline grid resolution the PIC solution is more dynamic than the Hall MHD simulation and it compares significantly better with the Galileo magnetic measurements than the Hall MHD solution. The power spectra of the observed and simulated magnetic field fluctuations agree extremely well for the MHD-EPIC model. The MHD-EPIC simulation also produced a few flux transfer events (FTEs) that have magnetic signatures very similar to an observed event. The simulation shows that the FTEs often exhibit complex 3-D structures with their orientations changing substantially between the equatorial plane and the Galileo trajectory, which explains the magnetic signatures observed during the magnetopause crossings. The computational cost of the MHD-EPIC simulation was only about 4 times more than that of the Hall MHD simulation. Key Points

  • 182.
    Tully, Philip
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). University of Edinburgh School of Informatics.
    Spike-Based Bayesian-Hebbian Learning in Cortical and Subcortical Microcircuits2017Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Cortical and subcortical microcircuits are continuously modified throughout life. Despite ongoing changes these networks stubbornly maintain their functions, which persist although destabilizing synaptic and nonsynaptic mechanisms should ostensibly propel them towards runaway excitation or quiescence. What dynamical phenomena exist to act together to balance such learning with information processing? What types of activity patterns

    do they underpin, and how do these patterns relate to our perceptual experiences? What enables learning and memory operations to occur despite such massive and constant neural reorganization? Progress towards answering many of these questions can be pursued through large-scale neuronal simulations. 

     

    In this thesis, a Hebbian learning rule for spiking neurons inspired by statistical inference is introduced. The spike-based version of the Bayesian Confidence Propagation Neural Network (BCPNN) learning rule involves changes in both synaptic strengths and intrinsic neuronal currents. The model is motivated by molecular cascades whose functional outcomes are mapped onto biological mechanisms such as Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability. Temporally interacting memory traces enable spike-timing dependence, a stable learning regime that remains competitive, postsynaptic activity regulation, spike-based reinforcement learning and intrinsic graded persistent firing levels. 

     

    The thesis seeks to demonstrate how multiple interacting plasticity mechanisms can coordinate reinforcement, auto- and hetero-associative learning within large-scale, spiking, plastic neuronal networks. Spiking neural networks can represent information in the form of probability distributions, and a biophysical realization of Bayesian computation can help reconcile disparate experimental observations.

  • 183.
    Tully, Philip J.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Karolinska Inst, Sweden.
    Lindén, Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Karolinska Inst, Sweden.
    Hennig, Matthias H.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Karolinska Inst, Sweden.
    Spike-Based Bayesian-Hebbian Learning of Temporal Sequences2016Ingår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, nr 5, artikel-id e1004954Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

  • 184. Valero-Lara, P.
    et al.
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    LBM-HPC - An open-source tool for fluid simulations. Case study: Unified parallel C (UPC-PGAS)2015Ingår i: Proceedings - IEEE International Conference on Cluster Computing, ICCC, Institute of Electrical and Electronics Engineers (IEEE), 2015, s. 318-321Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main motivation of this work is the evaluation of the Unified Parallel C (UPC) model, for Boltzmann-fluid simulations. UPC is one of the current models in the so-called Partitioned Global Address Space paradigm. This paradigm attempts to increase the simplicity of codes and achieve a better efficiency and scalability. Two different UPC-based implementations, explicit and implicit, are presented and evaluated. We compare the fundamental features of our UPC implementations with other parallel programming model, MPI-OpenMP. In particular each of the major steps of any LBM code, i.e., Boundary Conditions, Communication, and LBM solver, are analyzed.

  • 185. Valero-Lara, P.
    et al.
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Basque Center for Applied Mathematics (BCAM).
    Multi-domain grid refinement for lattice-Boltzmann simulations on heterogeneous platforms2015Ingår i: Proceedings - IEEE 18th International Conference on Computational Science and Engineering, CSE 2015, IEEE Computer Society, 2015, s. 1-8Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main contribution of the present work consists of several parallel approaches for grid refinement based on a multi-domain decomposition for lattice-Boltzmann simulations. The proposed method for discretizing the fluid incorporates different regular Cartesian grids with no homogeneous spatial domains, which are in need to be communicated each other. Three different parallel approaches are proposed, homogeneous Multicore, homogeneous GPU, and heterogeneous Multicore-GPU. Although, the homogeneous implementations exhibit satisfactory results, the heterogeneous approach achieves up to 30% extra efficiency, in terms of Millions of Fluid Lattice Updates per Second (MFLUPS), by overlapping some of the steps on both architectures, Multicore and GPU. © 2015 IEEE.

  • 186. Valero-Lara, P.
    et al.
    Krishnasamy, E.
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Basque Center for Applied Mathematics (BCAM), Spain.
    Towards HPC-embedded. Case study: Kalray and message-passing on NoC2017Ingår i: Scalable Computing: Practice and Experience, ISSN 1895-1767, E-ISSN 1895-1767, Vol. 18, nr 2, s. 151-160Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Today one of the most important challenges in HPC is the development of computers with a low power consumption. In this context, recently, new embedded many-core systems have emerged. One of them is Kalray. Unlike other many-core architectures, Kalray is not a co-processor (self-hosted). One interesting feature of the Kalray architecture is the Network on Chip (NoC) connection. Habitually, the communication in many-core architectures is carried out via shared memory. However, in Kalray, the communication among processing elements can also be via Message-Passing on the NoC. One of the main motivations of this work is to present the main constraints to deal with the Kalray architecture. In particular, we focused on memory management and communication. We assess the use of NoC and shared memory on Kalray. Unlike shared memory, the implementation of Message-Passing on NoC is not transparent from programmer point of view. The synchronization among processing elements and NoC is other of the challenges to deal with in the Karlay processor. Although the synchronization using Message-Passing is more complex and consuming time than using shared memory, we obtain an overall speedup close to 6 when using Message-Passing on NoC with respect to the use of shared memory. Additionally, we have measured the power consumption of both approaches. Despite of being faster, the use of NoC presents a higher power consumption with respect to the approach that exploits shared memory. This additional consumption in Watts is about a 50%. However, the reduction in time by using NoC has an important impact on the overall power consumption as well.

  • 187. Valero-Lara, Pedro
    et al.
    Nookala, Poornima
    Pelayo, Fernando L.
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). BCAM, Bilbao, Spain.
    Dimitropoulos, Serapheim
    Raicu, Ioan
    MANY-TASK COMPUTING ON MANY-CORE ARCHITECTURES2016Ingår i: Scalable Computing: Practice and Experience, ISSN 1895-1767, E-ISSN 1895-1767, Vol. 17, nr 1, s. 33-46Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids, cloud and supercomputers, but it is not so popular in shared memory parallel processors. In this sense and given the spectacular growth in performance and in number of cores integrated in many-core architectures, the study of MTC on such architectures is becoming more and more relevant. In this paper, authors present what are those programming mechanisms to take advantages of such massively parallel features for the particular target of MTC. Also, the hardware features of the two dominant many-core platforms (NVIDIA's GPUs and Intel Xeon Phi) are also analyzed for our specific framework. Given the important differences in terms of hardware and software in our two many-core platforms, we have considered different strategies based on CUDA (for GPUs) and OpenMP (for Intel Xeon Phi). We carried out several test cases based on an appropriate and widely studied problem for benchmarking as matrix multiplication. Essentially, this study consisted of comparing the time consumed for computing in parallel several tasks one by one (the whole computational resources are used just to compute one task at a time) with the time consumed for computing in parallel the same set of tasks simultaneously (the whole computational resources are used for computing the set of tasks at very same time). Finally, we compared both software-hardware scenarios to identify the most relevant computer features in each of our many-core architectures.

  • 188. Vencels, J.
    et al.
    Delzanno, G. L.
    Manzini, G.
    Markidis, S.
    Peng, I. Bo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Roytershteyn, V.
    SpectralPlasmaSolver: A Spectral Code for Multiscale Simulations of Collisionless, Magnetized Plasmas2016Ingår i: Journal of Physics, Conference Series, ISSN 1742-6588, E-ISSN 1742-6596, Vol. 719, nr 1, artikel-id 12022Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present the design and implementation of a spectral code, called SpectralPlasmaSolver (SPS), for the solution of the multi-dimensional Vlasov-Maxwell equations. The method is based on a Hermite-Fourier decomposition of the particle distribution function. The code is written in Fortran and uses the PETSc library for solving the non-linear equations and preconditioning and the FFTW library for the convolutions. SPS is parallelized for shared- memory machines using OpenMP. As a verification example, we discuss simulations of the two-dimensional Orszag-Tang vortex problem and successfully compare them against a fully kinetic Particle-In-Cell simulation. An assessment of the performance of the code is presented, showing a significant improvement in the code running-time achieved by preconditioning, while strong scaling tests show a factor of 10 speed-up using 16 threads.

  • 189. Vlachos, Ioannis
    et al.
    Deniz, Taskin
    Aertsen, Ad
    Kumar, Arvind
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). University of Freiburg, Germany.
    Recovery of dynamics and function in spiking neural networks with closed-loop control2016Ingår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, nr 2, s. e1004720-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    There is a growing interest in developing novel brain stimulation methods to control disease-related aberrant neural activity and to address basic neuroscience questions. Conventional methods for manipulating brain activity rely on open-loop approaches that usually lead to excessive stimulation and, crucially, do not restore the original computations performed by the network. Thus, they are often accompanied by undesired side-effects. Here, we introduce delayed feedback control (DFC), a conceptually simple but effective method, to control pathological oscillations in spiking neural networks (SNNs). Using mathematical analysis and numerical simulations we show that DFC can restore a wide range of aberrant network dynamics either by suppressing or enhancing synchronous irregular activity. Importantly, DFC, besides steering the system back to a healthy state, also recovers the computations performed by the underlying network. Finally, using our theory we identify the role of single neuron and synapse properties in determining the stability of the closed-loop system.

  • 190.
    Wang, Ruoli
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Mekanik, Biomekanik. KTH, Skolan för teknikvetenskap (SCI), Centra, BioMEx. Karolinska Institutet, Sweden.
    Herman, Pawel
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Ekeberg, Örjan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Gäverth, Johan
    Dept Women's and Children's Health, Karolinska Institutet.
    Fagergren, Anders
    AggeroMedTech AB, Stockholm.
    Forssberg, Hans
    Dept Women's and Children's Health, Karolinska Institutet.
    Neural and non-neural related properties in the spastic wrist flexors: An optimization study2017Ingår i: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 47, s. 198-209Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Quantifying neural and non-neural contributions to increased joint resistance in spasticity is essential for a better understanding of its pathophysiological mechanisms and evaluating different intervention strategies. However, direct measurement of spasticity-related manifestations, e.g., motoneuron and biophysical properties in humans, is extremely challenging. In this vein, we developed a forward neuromusculoskeletal model that accounts for dynamics of muscle spindles, motoneuron pools, muscle activation and musculotendon of wrist flexors and relies on the joint angle and resistant torque as the only input measurement variables. By modeling the stretch reflex pathway, neural and non-neural related properties of the spastic wrist flexors were estimated during the wrist extension test. Joint angle and resistant torque were collected from 17 persons with chronic stroke and healthy controls using NeuroFlexor, a motorized force measurement device during the passive wrist extension test. The model was optimized by tuning the passive and stretch reflex-related parameters to fit the measured torque in each participant. We found that persons with moderate and severe spasticity had significantly higher stiffness than controls. Among subgroups of stroke survivors, the increased neural component was mainly due to a lower muscle spindle rate at 50% of the motoneuron recruitment. The motoneuron pool threshold was highly correlated to the motoneuron pool gain in all subgroups. The model can describe the overall resistant behavior of the wrist joint during the test. Compared to controls, increased resistance was predominantly due to higher elasticity and neural components. We concluded that in combination with the NeuroFlexor measurement, the proposed neuromusculoskeletal model and optimization scheme served as suitable tools for investigating potential parameter changes along the stretch-reflex pathway in persons with spasticity.

  • 191. Wang, Z.
    et al.
    Esturo, J. M.
    Seidel, H. -P
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics, Germany .
    Stream Line-Based Pattern Search in Flows2016Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We propose a method that allows users to define flow features in form of patterns represented as sparse sets of stream line segments. Our approach finds similar occurrences in the same or other time steps. Related approaches define patterns using dense, local stencils or support only single segments. Our patterns are defined sparsely and can have a significant extent, i.e., they are integration-based and not local. This allows for a greater flexibility in defining features of interest. Similarity is measured using intrinsic curve properties only, which enables invariance to location, orientation, and scale. Our method starts with splitting stream lines using globally consistent segmentation criteria. It strives to maintain the visually apparent features of the flow as a collection of stream line segments. Most importantly, it provides similar segmentations for similar flow structures. For user-defined patterns of curve segments, our algorithm finds similar ones that are invariant to similarity transformations. We showcase the utility of our method using different 2D and 3D flow fields.

  • 192. Wang, Z.
    et al.
    Esturo, J. Martinez
    Seidel, H. -P
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    Pattern Search in Flows based on Similarity of Stream Line Segments2014Ingår i: Proc. Vision, Modeling and Visualization, 2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose a method that allows users to define flow features in form of patterns represented as sparse sets of stream line segments. Our approach finds similar occurrences in the same or other time steps. Related approaches define patterns using dense, local stencils or support only single segments. Our patterns are defined sparsely and can have a significant extent, i.e., they are integration-based and not local. This allows for a greater flexibility in defining features of interest. Similarity is measured using intrinsic curve properties only, which enables invariance to location, orientation, and scale. Our method starts with splitting stream lines using globally-consistent segmentation criteria. It strives to maintain the visually apparent features of the flow as a collection of stream line segments. Most importantly, it provides similar segmentations for similar flow structures. For user-defined patterns of curve segments, our algorithm finds similar ones that are invariant to similarity transformations. We showcase the utility of our method using different 2D and 3D flow fields.

  • 193. Wang, Z.
    et al.
    Seidel, H. -P
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hierarchical Hashing for Pattern Search in 3D Vector Fields2015Ingår i: Proc. Vision, Modeling and Visualization, 2015, s. 1-48Konferensbidrag (Refereegranskat)
    Abstract [en]

    The expressiveness of many visualization methods for 3D vector fields is often limited by occlusion, i.e., interesting flow patterns hide each other or are hidden by laminar flow. Automatic detection of patterns in 3D vector fields has gained attention recently, since it allows to highlight user-defined patterns and separate the wheat from the chaff. We propose an algorithm which is able to detect 3D flow patterns of arbitrary extent in a robust manner. We encode the local flow behavior in scale space using a sequence of hierarchical base descriptors, which are pre-computed and hashed into a number of hash tables. This ensures a fast fetching of similar occurrences in the flow and requires only a constant number of table lookups. In contrast to many previous approaches, our method supports patterns of arbitrary shape and extent. We achieve this by assembling these patterns using several smaller spheres. The results are independent of translation, rotation, and scaling. Our experiments show that our approach encompasses the state of the art with respect to both the computational costs and the accuracy.

  • 194. Wang, Z.
    et al.
    Seidel, H. -P
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Multi-field Pattern Matching based on Sparse Feature Sampling2016Ingår i: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 22, nr 1, s. 807-816Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present an approach to pattern matching in 3D multi-field scalar data. Existing pattern matching algorithms work on single scalar or vector fields only, yet many numerical simulations output multi-field data where only a joint analysis of multiple fields describes the underlying phenomenon fully. Our method takes this into account by bundling information from multiple fields into the description of a pattern. First, we extract a sparse set of features for each 3D scalar field using the 3D SIFT algorithm (Scale-Invariant Feature Transform). This allows for a memory-saving description of prominent features in the data with invariance to translation, rotation, and scaling. Second, the user defines a pattern as a set of SIFT features in multiple fields by e.g. brushing a region of interest. Third, we locate and rank matching patterns in the entire data set. Experiments show that our algorithm is efficient in terms of required memory and computational efforts.

  • 195.
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    Differential Descriptions for Characteristic Curves and their Possible Role in Flow Analysis2014Övrigt (Övrigt vetenskapligt)
  • 196.
    Weinkauf, Tino
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). Max Planck Institute for Informatics.
    On the (Un)Suitability of Strict Feature Definitions for Uncertain Data2014Ingår i: Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization / [ed] Chen, M.; Hagen, H.; Hansen, C.; Johnson, C.; Kaufmann, A., Springer , 2014Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    We discuss strategies to successfully work with strict feature definitions such as topology in the presence of noisy/uncertain data. To that end, we review previous work from the literature and identify three strategies: the development of fuzzy analogs to strict feature definitions, the aggregation of features, and the filtering of features. Regarding the latter, we will present a detailed discussion of filtering ridges/valleys and topological structures.

  • 197. Wendt, Fabian F
    et al.
    Yu, Yi-Hsiang
    Nielsen, Kim
    Ruehl, Kelley
    Bunnik, Tim
    Touzon, Imanol
    Nam, Bo Woo
    Kim, Jeong Seok
    Kim, Kyong-Hwan
    Janson, Carl Erik
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hoffman, Johan
    et al.,
    International Energy Agency Ocean Energy Systems Task 10 Wave Energy Converter Modeling Verification and Validation2017Ingår i: 12th European Wave and Tidal Energy Conference European Wave and Tidal Energy Conference, 2017Konferensbidrag (Refereegranskat)
  • 198. Winsnes, C. F.
    et al.
    Sullivan, D. P.
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Smith, Kevin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Lundberg, Emma
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Multi-label prediction of subcellular localization in confocal images using deep neural networks2016Ingår i: Molecular Biology of the Cell, ISSN 1059-1524, E-ISSN 1939-4586, Vol. 27Artikel i tidskrift (Refereegranskat)
  • 199.
    Wärnberg, Emil
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Modelling Low Dimensional Neural Activity2016Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Ett antal nyligen publicerade studier has visat att dimensionaliten för neural aktivitet är låg. Dock är det inte klarlagt vilka nätverksstrukturer som kan uppbringa denna typ av aktivitet. I denna uppsats diskuterar jag möjliga lösningsförslag, och demonstrerar att ett nätverk med en flerdimensionell attraktor ger upphov till lågdimensionell aktivitet. Nätverket skapas med hjälp av the Neural Engineering Framework, och uppvisar ett flertal biologiskt trovärdiga egenskaper. I synnerhet är fördelningen av synapsvikter log-normalt fördelad.

  • 200.
    Yang, Fangkai
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Li, Chengjie
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Palmberg, Robin
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Van der Heide, Ewoud
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Peters, Christopher
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Expressive Virtual Characters for Social Demonstration Games2017Ingår i: 2017 9th International Conference on Virtual Worlds and Games for Serious Applications, VS-Games 2017 - Proceedings, IEEE, 2017, s. 217-224Konferensbidrag (Refereegranskat)
    Abstract [en]

    Virtual characters are an integral part of many game and learning environments and have practical applications as tutors, demonstrators or even representations of the user. However, creating virtual character behaviors can be a time-consuming and complex task requiring substantial technical expertise. To accelerate and better enable the use of virtual characters in social games, we present a virtual character behavior toolkit for the development of expressive virtual characters. It is a midlleware toolkit which sits on top of the game engine with a focus on providing high-level character behaviors to quickly create social games. The toolkit can be adapted to a wide range of scenarios related to social interactions with individuals and groups at multiple distances in the virtual environment and supports customization and control of facial expressions, body animations and group formations. We describe the design of the toolkit, providing an examplar of a small game that is being created with it and our intended future work on the system.

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