Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform

Austrian High-Performance-Computing meeting (AHPC2020)

This booklet is a collection of abstracts presented at the AHPC conference

Indiana University’s advanced cyberinfrastructure in service of IU strategic goals: Activities of the Research Technologies Division of UITS and National Center for Genome Analysis Support – two Pervasive Technology Institute cyberinfrastructure and service centers - during FY2014

This report presents information on the activities of the Research Technologies Division of UITS and the National Center for Genome Analysis Support, two cyberinfrastructure and service centers of the Pervasive Technology Institute. Research Technologies (RT) is a subunit of University Information Technology Services (UITS) and it operates and supports the largest computational, data, and visualization systems at IU. The National Center for Genome Analysis Support (NCGAS) is primarily federally funded, serving the national community of genome scientists. NCGAS leadership is drawn from the Office of the Vice President for Information Technology, UITS, the College, and the School of Informatics and Computing. This report focuses on contributions of RT and NCGAS to accomplishment of IU’s bicentennial goals, and is organized according to those goals. Together the activities of NCGAS and RT represent a large share of the activities of PTI in support of the IU community. PTI’s Research Centers (Data to Insight Center, Digital Science Center, and the Center for Applies Cybersecurity Research) also provide support to the IU community in various forms but the primary focus of these research centers is informatics, information technology, and computer science research

Book of Abstracts of the Sixth SIAM Workshop on Combinatorial Scientific Computing

Book of Abstracts of CSC14 edited by Bora UçarInternational audienceThe Sixth SIAM Workshop on Combinatorial Scientific Computing, CSC14, was organized at the Ecole Normale Supérieure de Lyon, France on 21st to 23rd July, 2014. This two and a half day event marked the sixth in a series that started ten years ago in San Francisco, USA. The CSC14 Workshop's focus was on combinatorial mathematics and algorithms in high performance computing, broadly interpreted. The workshop featured three invited talks, 27 contributed talks and eight poster presentations. All three invited talks were focused on two interesting fields of research specifically: randomized algorithms for numerical linear algebra and network analysis. The contributed talks and the posters targeted modeling, analysis, bisection, clustering, and partitioning of graphs, applied in the context of networks, sparse matrix factorizations, iterative solvers, fast multi-pole methods, automatic differentiation, high-performance computing, and linear programming. The workshop was held at the premises of the LIP laboratory of ENS Lyon and was generously supported by the LABEX MILYON (ANR-10-LABX-0070, Université de Lyon, within the program ''Investissements d'Avenir'' ANR-11-IDEX-0007 operated by the French National Research Agency), and by SIAM

Non-selective Refocusing Pulse Design in Parallel Transmission for Magnetic Resonance Imaging of the Human Brain at Ultra High Field

In Magnetic Resonance Imaging (MRI), the increase of the static magnetic field strength is used to provide in theory a higher signal-to-noise ratio, thereby improving the overall image quality. The purpose of ultra-high-field MRI is to achieve a spatial image resolution sufficiently high to be able to distinguish structures so fine that they are currently impossible to view in a non-invasive manner. However, at such static magnetic fields strengths, the wavelength of the electromagnetic waves sent to flip the water proton spins is of the same order of magnitude than the scanned object. Interference wave phenomena are then observed, which are caused by the radiofrequency (RF) field inhomogeneity within the object. These generate signal and/or contrast artifacts in MR images, making their exploitation difficult, if not impossible, in certain areas of the body. It is therefore crucial to provide solutions to mitigate the non-uniformity of the spins excitation. Failing this, these imaging systems with very high fields will not reach their full potential.For relevant high field clinical diagnosis, it is therefore necessary to create RF pulses homogenizing the excitation of all spins (here of the human brain), and optimized for each individual to be imaged. For this, an 8-channel parallel transmission system (pTX) was installed in our 7 Tesla scanner. While most clinical MRI systems only use a single transmission channel, the pTX extension allows to simultaneously playing various forms of RF pulses on all channels. The resulting sum of the interference must be optimized in order to reduce the non-uniformity typically seen.The objective of this thesis is to synthesize this type of tailored RF pulses, using parallel transmission. These pulses will have as an additional constraint the compliance with the international exposure limits for radiofrequency exposure, which induces a temperature rise in the tissue. In this sense, many electromagnetic and temperature simulations were carried out as an introduction of this thesis, in order to assess the relationship between the recommended RF exposure limits and the temperature rise actually predicted in tissues.This thesis focuses specifically on the design of all RF refocusing pulses used in non-selective MRI sequences based on the spin-echo. Initially, only one RF pulse was generated for a simple application: the reversal of spin dephasing in the transverse plane, as part of a classic spin echo sequence. In a second time, sequences with very long refocusing echo train applied to in vivo imaging are considered. In all cases, the mathematical operator acting on the magnetization, and not its final state as is done conventionally, is optimized. The gain in high field imaging is clearly visible, as the necessary mathematical operations (that is to say, the rotation of the spins) are performed with a much greater fidelity than with the methods of the state of the art. For this, the generation of RF pulses is combining a k-space-based spin excitation method, the kT-points, and an optimization algorithm, called Gradient Ascent Pulse Engineering (GRAPE), using optimal control.This design is relatively fast thanks to analytical calculations rather than finite difference methods. The inclusion of a large number of parameters requires the use of GPUs (Graphics Processing Units) to achieve computation times compatible with clinical examinations. This method of designing RF pulses has been experimentally validated successfully on the NeuroSpin 7 Tesla scanner, with a cohort of healthy volunteers. An imaging protocol was developed to assess the image quality improvement using these RF pulses compared to typically used non-optimized RF pulses. All methodological developments made during this thesis have contributed to improve the performance of ultra-high-field MRI in NeuroSpin, while increasing the number of MRI sequences compatible with parallel transmission.En Imagerie par Résonance Magnétique (IRM), l’augmentation du champ magnétique statique permet en théorie de fournir un rapport signal sur bruit accru, améliorant la qualité des images. L’objectif de l’IRM à ultra haut champ est d’atteindre une résolution spatiale suffisamment haute pour pouvoir distinguer des structures si fines qu’elles sont actuellement impossibles à visualiser de façon non-invasive. Cependant, à de telles valeurs de champs magnétiques, la longueur d’onde du rayonnement électromagnétique envoyé pour basculer les spins des protons de l’eau est du même ordre de grandeur que l’objet dont on souhaite faire l’image. Des phénomènes d’interférences sont observés, ce qui se traduit par l’inhomogénéité de ce champ radiofréquence (RF) au sein de l’objet. Ces interférences engendrent des artefacts de signal et/ou de contraste dans les images IRM, et rendent ainsi leur exploitation délicate. Il est donc crucial de fournir des solutions pour atténuer la non-uniformité de l’excitation des spins, à défaut de quoi de tels systèmes ne pourront atteindre leurs pleins potentiels. Pour obtenir des diagnostics pertinents à très haut champ, il est donc nécessaire de créer des impulsions RF homogénéisant l'excitation de l'ensemble des spins (ici du cerveau humain), optimisées pour chaque individu. Pour cela, un système de transmission parallèle (pTX) à 8 canaux a été installé au sein de notre imageur à 7 Tesla. Alors que la plupart des systèmes IRM cliniques n’utilisent qu’un seul canal d’émission, l’extension pTX permet de jouer différentes formes d’impulsions RF de concert. La somme résultante de ces interférences doit alors être optimisée pour atténuer la non-uniformité observée classiquement. L’objectif de cette thèse est donc de synthétiser ce type d’impulsions, en utilisant la pTX. Ces impulsions auront pour contrainte supplémentaire le respect des limitations internationales concernant l'exposition à des champs radiofréquence, qui induit une hausse de température dans les tissus. En ce sens, de nombreuses simulations électromagnétiques et de températures ont été réalisées en introduction de cette thèse, afin d’évaluer la relation entre les seuils recommandés d’exposition RF et l’élévation de température prédite dans les tissus. Cette thèse porte plus spécifiquement sur la conception de l’ensemble des impulsions RF refocalisantes utilisées dans des séquences IRM non-sélectives, basées sur l’écho de spin. Dans un premier temps, seule une impulsion RF a été générée, pour une application simple : l’inversion du déphasage des spins dans le plan transverse. Dans un deuxième temps, sont considérées les séquences à long train d’échos de refocalisation appliquées à l’in vivo. Ici, l’opérateur mathématique agissant sur la magnétisation, et non pas son état final comme il est fait classiquement, est optimisé. Le gain en imagerie à très haut champ est clairement visible puisque les opérations mathématiques (la rotation des spins) voulues sont réalisées avec plus de fidélité que dans le cadre des méthodes de l’état de l’art. Pour cela, la génération de ces impulsions RF combine une méthode d’excitation des spins avec navigation dans l’espace de Fourier, les kT-points, et un algorithme d’optimisation, appelé Gradient Ascent Pulse Engineering (GRAPE), utilisant le contrôle optimal. Cette conception est rapide grâce à des calculs analytiques plus directs que des méthodes de différences finies. La prise en compte d’un grand nombre de paramètres nécessite l’usage de GPUs (Graphics Processing Units) pour atteindre des temps de calcul compatibles avec un examen clinique. Cette méthode de conception d’impulsions RF a été validée expérimentalement sur l’imageur 7 Tesla de NeuroSpin, sur une cohorte de volontaires sains

Solutions for the optimization of the software interface on an FPGA-based NIC

The theme of the research is the study of solutions for the optimization of the software interface on FPGA-based Network Interface Cards. The research activity was carried out in the APE group at INFN (Istituto Nazionale di Fisica Nucleare), which has been historically active in designing of high performance scalable networks for hybrid nodes (CPU/GPU) clusters. The result of the research is validated on two projects the APE group is currently working on, both allowing fast prototyping for solutions and hardware-software co-design: APEnet (a PCIe FPGA-based 3D torus network controller) and NaNet (FPGA-based family of NICs mainly dedicated to real-time, low-latency computing systems such as fast control systems or High Energy Physics Data Acquisition Systems). NaNet is also used to validate a GPU-controlled device driver to improve network perfomances, i.e. even lower latency of the communication, while used in combination with existing user-space software. This research is also gaining results in the "Horizon2020 FET-HPC ExaNeSt project", which aims to prototype and develop solutions for some of the crucial problems on the way towards production of Exascale-level Supercomputers, where the APE group is actively contribuiting to the development of the network / interconnection infrastructure