63 research outputs found

    A shared-disk parallel cluster file system

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    Dissertação apresentada para obtenção do Grau de Doutor em InformĂĄtica Pela Universidade Nova de Lisboa, Faculdade de CiĂȘncias e TecnologiaToday, clusters are the de facto cost effective platform both for high performance computing (HPC) as well as IT environments. HPC and IT are quite different environments and differences include, among others, their choices on file systems and storage: HPC favours parallel file systems geared towards maximum I/O bandwidth, but which are not fully POSIX-compliant and were devised to run on top of (fault prone) partitioned storage; conversely, IT data centres favour both external disk arrays (to provide highly available storage) and POSIX compliant file systems, (either general purpose or shared-disk cluster file systems, CFSs). These specialised file systems do perform very well in their target environments provided that applications do not require some lateral features, e.g., no file locking on parallel file systems, and no high performance writes over cluster-wide shared files on CFSs. In brief, we can say that none of the above approaches solves the problem of providing high levels of reliability and performance to both worlds. Our pCFS proposal makes a contribution to change this situation: the rationale is to take advantage on the best of both – the reliability of cluster file systems and the high performance of parallel file systems. We don’t claim to provide the absolute best of each, but we aim at full POSIX compliance, a rich feature set, and levels of reliability and performance good enough for broad usage – e.g., traditional as well as HPC applications, support of clustered DBMS engines that may run over regular files, and video streaming. pCFS’ main ideas include: · Cooperative caching, a technique that has been used in file systems for distributed disks but, as far as we know, was never used either in SAN based cluster file systems or in parallel file systems. As a result, pCFS may use all infrastructures (LAN and SAN) to move data. · Fine-grain locking, whereby processes running across distinct nodes may define nonoverlapping byte-range regions in a file (instead of the whole file) and access them in parallel, reading and writing over those regions at the infrastructure’s full speed (provided that no major metadata changes are required). A prototype was built on top of GFS (a Red Hat shared disk CFS): GFS’ kernel code was slightly modified, and two kernel modules and a user-level daemon were added. In the prototype, fine grain locking is fully implemented and a cluster-wide coherent cache is maintained through data (page fragments) movement over the LAN. Our benchmarks for non-overlapping writers over a single file shared among processes running on different nodes show that pCFS’ bandwidth is 2 times greater than NFS’ while being comparable to that of the Parallel Virtual File System (PVFS), both requiring about 10 times more CPU. And pCFS’ bandwidth also surpasses GFS’ (600 times for small record sizes, e.g., 4 KB, decreasing down to 2 times for large record sizes, e.g., 4 MB), at about the same CPU usage.Lusitania, Companhia de Seguros S.A, Programa IBM Shared University Research (SUR

    Observing planet formation

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    Planets are thought to form in the circumstellar disks orbiting young stars in formation. According to the core-accretion model, a candidate scenario for Earth-like planets, the interstellar sub-ÎŒ\mum-sized dust particles grow thanks to collisions to mm/cm size and then form km-sized planetesimals via dynamical encounters. Eventually, the rocky planetary cores accrete gas and, depending on the total gas mass attained, a terrestrial planet or a gas giant forms. Modern sub-mm/mm/radio interferometers such as ALMA and VLA detect the thermal emission of dust grains and provide us with an unprecedented sharp view of protoplanetary disks at the spatial scales where planet formation occurs. In recent years, evidence of grain growth in disks has been obtained by extensive sub-mm/mm photometric studies, but so far they only provided disk-averaged estimates of the dust properties. Moreover, the derivation of dust properties from the observed spectral index was done under reasonable - but simplifying - assumptions rather than with a proper modeling of the disk emission. The thesis presents an analysis method that enables - for the first time - the disk structure and the dust properties to be constrained simultaneously by fitting multi-wavelength observations with a self-consistent physical model. The thesis presents also an accelerated version of the computer code that uses modern graphics cards and provides the computational breakthrough needed to exploit the new wealth of information now available. Applying the multi-wavelength analysis to observations of three disks in the Taurus and Ophiuchus star-forming regions, a key result is a radial gradient in the grain-size distribution, with large grains of up to 1 cm1\,\mathrm{cm} size confined to the inner disk and smaller grains of size â‰Ș1 mm\ll 1\,\mathrm{mm} populating the whole disk. Similar results hold for another disk, HD~163296, where in addition the grain size radial profile supports the scenario of enhanced grain growth at the snowline location of the second most abundant volatile in disks, CO. The tool developed in the thesis is also designed to accelerate the analysis of high-resolution observations for demographic studies. By applying the analysis tool to an ALMA disk survey in the Lupus star-forming region, the physical structure of more than 20 disks is obtained, in particular the disks's size and dust mass among other physical parameters. To date, this is the largest sample of disks of the same star-forming region fitted homogeneously with a self-consistent model. Remarkably, the sample is complete in the mass range of 0.7M⊙M_\odot to one M⊙M_\odot. The results are compatible with previous studies based on simpler analyses but also highlight a consistent difference in the disks's luminosity-size correlation between the older (∌3 Myr\sim3\,\mathrm{Myr}) Lupus and the younger (∌1−2 Myr\sim1-2\,\mathrm{Myr} old) Taurus-Auriga region. The application of the analysis developed in this thesis to multi-wavelength observations of large samples of disks with ALMA will allow us to spatially resolve the early growth of solids in numerous protoplanetary disks, and therefore to provide measurements that will be crucial to inform, test, and refine theoretical models of planet formation.Die Entstehung von Planeten und Sternen ist eng miteinander verknĂŒpft. Der Stern bildet sich im Zentrum einer rotierenden Materiescheibe. Die Planeten entstehen wiederum in der zirkumstellaren Scheibe. Das Kern-Akkretions-Modell beschreibt die allmĂ€hliche Entstehung von Planeten in folgender Weise: Interstellare Staubteilchen mit GrĂ¶ĂŸen im Submillimeterbereich wachsen durch Kollisionen auf eine GrĂ¶ĂŸe von Millimetern bzw. Zentimetern heran. Sie stoßen wieder zusammen und bilden im weiteren kilometergroße Planetesimale. Schließlich akkretieren die felsartigen Planetenkerne Gas und bilden dann, je nach akkretierter Gasmasse, einen erdĂ€hnlichen Planeten oder einen Gasriesen. Moderne Interferometer mit WellenlĂ€ngen von Submillimeter ĂŒber Millimeter bis in den Radiobereich wie das Atacama Large Millimetre Array (ALMA) oder das Very Large Array (VLA) detektieren die thermische Emission von Staubkörnern und erlauben eine nie dagewesene Auflösung von protoplanetaren Scheiben bis auf LĂ€ngenskalen, auf denen sich die Planetenbildung ereignet. In den letzten Jahren haben ausfĂŒhrliche photometrische Studien im Submilli\-meter- und Millimeter-WellenlĂ€ngenbereich Hinweise auf Kornwachstum in Scheiben geliefert, allerdings nur gemittelt ĂŒber die gesamte Scheibe. Zudem wurde die Ableitung der Staubeigenschaften vom beobachteten spektralen Index unter plausiblen, aber stark vereinfachenden, Annahmen durchgefĂŒhrt. In Rahmen dieser Dissertation wurde eine Analysemethode entwickelt, die es zum ersten Mal erlaubt, gleichzeitig die Struktur der Scheibe und die Eigenschaften des Staubs durch eine Anpassung eines selbstkonsistenten, physikalischen Modells an die Beobachtungen in mehreren WellenlĂ€ngenbereichen zu ermitteln. Außerdem wird eine neue Version eines Computercodes prĂ€sentiert, die durch die Verwendung moderner Grafikkarten viel schneller ist. Das stellt einen Durchbruch in der Rechenleistung dar, der erforderlich ist, um die riesigen, aktuell verfĂŒgbaren Datenmengen zu bewĂ€ltigen. In der Anwendung der MultiwellenlĂ€ngen-Analyse auf Beobachtungen dreier Scheiben in Sternentstehungsregionen der Sternbilder Stier (Taurus) und SchlangentrĂ€ger (Ophiuchus) zeigt sich ein radialer Gradient in der Verteilung der KorngrĂ¶ĂŸe. Dabei sind große Körner von bis zu einem Zentimeter GrĂ¶ĂŸe auf die innere Scheibe beschrĂ€nkt. Dagegen sind Körner, die viel kleiner sind als ein Millimeter, in der gesamten Scheibe zu finden. Ähnliche Ergebnisse betreffen eine andere analysierte Scheibe in HD 163296. Dort gilt zusĂ€tzlich, dass das Radialprofil der KorngrĂ¶ĂŸe ein Szenario unterstĂŒtzt, in dem verstĂ€rktes Kornwachstum genau dort auftritt, wo der zweithĂ€ufigste, flĂŒchtige Stoff in Scheiben, nĂ€mlich Kohlenmonoxid (CO), gefriert. Das Computerprogramm, das im Rahmen der Dissertation entwickelt wurde, dient auch zur Beschleunigung der zwölf Analysen von hochaufgelösten Beobachtungen in Studien ganzer Populationen von Sternen mit protoplanetaren Scheiben. Konkret wurde das Programm auf mit ALMA beobachtete Scheiben in einer Sternentstehungsregion im Sternbild Wolf (Lupus) angewendet. Daraus wurde die physikalische Struktur von mehr als zwanzig Scheiben abgeleitet. Neben anderen physikalischen Parametern wurden ihre GrĂ¶ĂŸen und Staubmassen bestimmt. Bis jetzt ist dies die grĂ¶ĂŸte Anzahl von Scheiben aus der gleichen Sternentstehungsregion, die je einheitlich mit einem selbstkonsistenten Modell betrachtet wurde. Es ist bemerkenswert, dass dieser Satz an Scheiben im Massenbereich von 0,7 bis 1 Sonnenmassen und im Strahlungsfluss --- integriert ĂŒber den Submillimeterbereich --- vollstĂ€ndig ist. Die Ergebnisse sind im Einklang mit vorherigen Arbeiten, die auf einfacheren Analysen beruhten. Allerdings zeigen sie auch einen klaren Unterschied in der Korrelation zwischen der Leuchtkraft und der GrĂ¶ĂŸe der Scheiben aus der Ă€lteren, ca. drei Millionen Jahre alten Region im Sternbild Wolf und der jĂŒngeren, ca. 1-2 Millionen Jahre alten Population aus dem Grenzgebiet zwischen Stier und Fuhrmann (Auriga). Die Anwendung der Analyse dieser Dissertation auf MultiwellenlĂ€ngen\--Be\-ob\-achtungen einer großen Zahl von Scheiben, die mit ALMA beobachtet wurden, wird es erlauben, das Wachstum fester Körper im frĂŒhen Stadium vieler protoplanetarer Scheiben rĂ€umlich aufzulösen. Diese Messungen werden von zentraler Bedeutung sein, um theoretische Modelle der Planetenentstehung aufzustellen, zu testen und sie weiter zu verbessern

    Tree tensor networks for high-dimensional quantum systems and beyond

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    This thesis presents the development of a numerical simulation technique, the Tree Tensor Network, aiming to overcome current limitations in the simulation of two- and higher-dimensional quantum many-body systems. The development and application of methods based on Tensor Networks (TNs) for such systems are one of the most relevant challenges of the current decade with the potential to promote research and technologies in a broad range of fields ranging from condensed matter physics, high-energy physics, and quantum chemistry to quantum computation and quantum simulation. The particular challenge for TNs is the combination of accuracy and scalability which to date are only met for one-dimensional systems by other established TN techniques. This thesis first describes the interdisciplinary field of TN by combining mathematical modelling, computational science, and quantum information before it illustrates the limitations of standard TN techniques in higher-dimensional cases. Following a description of the newly developed Tree Tensor Network (TTN), the thesis then presents its application to study a lattice gauge theory approximating the low-energy behaviour of quantum electrodynamics, demonstrating the successful applicability of TTNs for high-dimensional gauge theories. Subsequently, a novel TN is introduced augmenting the TTN for efficient simulations of high-dimensional systems. Along the way, the TTN is applied to problems from various fields ranging from low-energy to high-energy up to medical physics.In dieser Arbeit wird die Entwicklung einer numerischen Simulationstechnik, dem Tree Tensor Network (TTN), vorgestellt, die darauf abzielt, die derzeitigen Limitationen bei der Simulation von zwei- und höherdimensionalen Quanten-Vielteilchensystemen zu ĂŒberwinden. Die Weiterentwicklung von auf Tensor-Netzwerken (TN) basierenden Methoden fĂŒr solche Systeme ist eine der aktuellsten und relevantesten Herausforderungen. Sie birgt das Potential, Forschung und Technologien in einem breiten Spektrum zu fördern, welches sich von der Physik der kondensierten Materie, der Hochenergiephysik und der Quantenchemie bis hin zur Quantenberechnung und Quantensimulation erstreckt. Die besondere Herausforderung fĂŒr TN ist die Kombination von Genauigkeit und Skalierbarkeit, die bisher nur fĂŒr eindimensionale Systeme erfĂŒllt wird. Diese Arbeit beschreibt zunĂ€chst das interdisziplinĂ€re Gebiet der TN als eine Kombination von mathematischer Modellierung, Computational Science und Quanteninformation, um dann die Grenzen der Standard-TN-Techniken in höherdimensionalen FĂ€llen aufzuzeigen. Nach einer Beschreibung des neu entwickelten TTN stellt die Arbeit dessen Anwendung zur Untersuchung einer Gittereichtheorie vor, die das Niederenergieverhalten der Quantenelektrodynamik approximiert und somit die erfolgreiche Anwendbarkeit von TTNs fĂŒr hochdimensionale Eichtheorien demonstriert. Anschließend wird ein neuartiges TN eingefĂŒhrt, welches das TTN fĂŒr effiziente Simulationen hochdimensionaler Systeme erweitert. ZusĂ€tzlich wird das TTN auf diverse Probleme angewandt, die von Niederenergie- ĂŒber Hochenergie- bis hin zur medizinischen Physik reichen

    Inkjet printing digital image generation and compensation for surface chemistry effects

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    Additive manufacturing (AM) of electronic materials using digital inkjet printing (DIJP) is of research interests nowadays because of its potential benefits in the semiconductor industry. Current trends in manufacturing electronics feature DIJP as a key technology to enable the production of customised and microscale functional devices. However, the fabrication of microelectronic components at large scale demands fast printing of tight features with high dimensional accuracy on substrates with varied surface topography which push inkjet printing process to its limits. To understand the DIJP droplet deposition on such substrates, generally requires computational fluid dynamics modelling which is limited in its physics approximation of surface interactions. Otherwise, a kind of “trial and error” approach to determining how the ink spreads, coalesce and solidifies over the substrate is used, often a very time-consuming process. Consequently, this thesis aims to develop new modelling techniques to predict fast and accurately the surface morphology of inkjet-printed features, enabling the optimisation of DIJP control parameters and the compensation of images for better dimensional accuracy of printed electronics devices. This investigation explored three categories of modelling techniques to predict the surface morphology of inkjet-printed features: physics-based, data-driven and hybrid physics-based and data-driven. Two physics-based numerical models were developed to reproduce the inkjet printing droplet deposition and solidification processes using a lattice Boltzmann (LB) multiphase flow model and a finite element (FE) chemo-mechanical model, respectively. The LB model was limited to the simulation of single tracks and small square films and the FE model was mainly employed for the distortion prediction of multilayer objects. Alternatively, two data-driven models were implemented to reconstruct the surface morphology of single tracks and free-form films using images from experiments: image analysis (IA) and shape from shading (SFS). IA assumed volume conservation and minimal energy drop shape to reconstruct the surface while SFS resolved the height of the image using a reflection model. Finally, a hybrid physics-based and data-driven approach was generated which incorporates the uncertainty of droplet landing position and footprint, hydrostatic analytical models, empirical correlations derived from experiments, and relationships derived from physics-based models to predict fast and accurately any free-form layer pattern as a function of physical properties, printing parameters and wetting characteristics. Depending on the selection of the modelling technique to predict the deformed geometry, further considerations were required. For the purely physics-based and data-driven models, a surrogate model using response surface equations was employed to create a transfer function between printing parameters, substrate wetting characteristics and the resulting surface morphology. The development of a transfer function significantly decreased the computational time required by purely physics-based models and enabled the parameter optimisation using a multi-objective genetic algorithm approach to attain the best film dimensional accuracy. Additionally, for multilayer printing applications, a layer compensation approach was achieved utilizing a convolutional neural network trained by the predicted (deformed) geometry to reduce the out of plane error to target shape. The optimal combination of printing parameters and input image compensation helped with the generation of fine features that are traditionally difficult for inkjet, improved resolution of edges and corners by reducing the amount of overflow from material, accounted for varied topography and capillary effects thereof on the substrate surface and considered the effect of multiple layers built up on each other. This study revealed for the first time to the best of our knowledge the role of the droplet location and footprint diameter uncertainty in the stability and uniformity of printed features. Using a droplet overlap map which was proposed as a universal technique to assess the effect of printing parameters on pattern geometry, it was shown that reliable limits for break-up and bulging of printed features were obtained. Considering droplet position and diameter size uncertainties, predicted optimal printing parameters improved the quality of printed films on substrates with different wettability. Finally, a stability diagram illustrating the onset of bulging and separation for lines and films as well as the optimal drop spacing, printing frequency and stand-off distance was generated to inform visually the results. This investigation has developed a predictive physics-based model of the surface morphology of DIJP features on heterogeneous substrates and a methodology to find the printing parameters and compensate the layer geometry required for optimum part dimensional accuracy. The simplicity of the proposed technique makes it a promising tool for model driven inkjet printing process optimization, including real time process control and paves the way for better quality devices in the printed electronics industry

    Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

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    Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

    Inkjet printing digital image generation and compensation for surface chemistry effects

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    Additive manufacturing (AM) of electronic materials using digital inkjet printing (DIJP) is of research interests nowadays because of its potential benefits in the semiconductor industry. Current trends in manufacturing electronics feature DIJP as a key technology to enable the production of customised and microscale functional devices. However, the fabrication of microelectronic components at large scale demands fast printing of tight features with high dimensional accuracy on substrates with varied surface topography which push inkjet printing process to its limits. To understand the DIJP droplet deposition on such substrates, generally requires computational fluid dynamics modelling which is limited in its physics approximation of surface interactions. Otherwise, a kind of “trial and error” approach to determining how the ink spreads, coalesce and solidifies over the substrate is used, often a very time-consuming process. Consequently, this thesis aims to develop new modelling techniques to predict fast and accurately the surface morphology of inkjet-printed features, enabling the optimisation of DIJP control parameters and the compensation of images for better dimensional accuracy of printed electronics devices. This investigation explored three categories of modelling techniques to predict the surface morphology of inkjet-printed features: physics-based, data-driven and hybrid physics-based and data-driven. Two physics-based numerical models were developed to reproduce the inkjet printing droplet deposition and solidification processes using a lattice Boltzmann (LB) multiphase flow model and a finite element (FE) chemo-mechanical model, respectively. The LB model was limited to the simulation of single tracks and small square films and the FE model was mainly employed for the distortion prediction of multilayer objects. Alternatively, two data-driven models were implemented to reconstruct the surface morphology of single tracks and free-form films using images from experiments: image analysis (IA) and shape from shading (SFS). IA assumed volume conservation and minimal energy drop shape to reconstruct the surface while SFS resolved the height of the image using a reflection model. Finally, a hybrid physics-based and data-driven approach was generated which incorporates the uncertainty of droplet landing position and footprint, hydrostatic analytical models, empirical correlations derived from experiments, and relationships derived from physics-based models to predict fast and accurately any free-form layer pattern as a function of physical properties, printing parameters and wetting characteristics. Depending on the selection of the modelling technique to predict the deformed geometry, further considerations were required. For the purely physics-based and data-driven models, a surrogate model using response surface equations was employed to create a transfer function between printing parameters, substrate wetting characteristics and the resulting surface morphology. The development of a transfer function significantly decreased the computational time required by purely physics-based models and enabled the parameter optimisation using a multi-objective genetic algorithm approach to attain the best film dimensional accuracy. Additionally, for multilayer printing applications, a layer compensation approach was achieved utilizing a convolutional neural network trained by the predicted (deformed) geometry to reduce the out of plane error to target shape. The optimal combination of printing parameters and input image compensation helped with the generation of fine features that are traditionally difficult for inkjet, improved resolution of edges and corners by reducing the amount of overflow from material, accounted for varied topography and capillary effects thereof on the substrate surface and considered the effect of multiple layers built up on each other. This study revealed for the first time to the best of our knowledge the role of the droplet location and footprint diameter uncertainty in the stability and uniformity of printed features. Using a droplet overlap map which was proposed as a universal technique to assess the effect of printing parameters on pattern geometry, it was shown that reliable limits for break-up and bulging of printed features were obtained. Considering droplet position and diameter size uncertainties, predicted optimal printing parameters improved the quality of printed films on substrates with different wettability. Finally, a stability diagram illustrating the onset of bulging and separation for lines and films as well as the optimal drop spacing, printing frequency and stand-off distance was generated to inform visually the results. This investigation has developed a predictive physics-based model of the surface morphology of DIJP features on heterogeneous substrates and a methodology to find the printing parameters and compensate the layer geometry required for optimum part dimensional accuracy. The simplicity of the proposed technique makes it a promising tool for model driven inkjet printing process optimization, including real time process control and paves the way for better quality devices in the printed electronics industry

    Proceedings of the Mobile Satellite Conference

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    A satellite-based mobile communications system provides voice and data communications to mobile users over a vast geographic area. The technical and service characteristics of mobile satellite systems (MSSs) are presented and form an in-depth view of the current MSS status at the system and subsystem levels. Major emphasis is placed on developments, current and future, in the following critical MSS technology areas: vehicle antennas, networking, modulation and coding, speech compression, channel characterization, space segment technology and MSS experiments. Also, the mobile satellite communications needs of government agencies are addressed, as is the MSS potential to fulfill them

    Combining SOA and BPM Technologies for Cross-System Process Automation

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    This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

    Numerical modelling of additive manufacturing process for stainless steel tension testing samples

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    Nowadays additive manufacturing (AM) technologies including 3D printing grow rapidly and they are expected to replace conventional subtractive manufacturing technologies to some extents. During a selective laser melting (SLM) process as one of popular AM technologies for metals, large amount of heats is required to melt metal powders, and this leads to distortions and/or shrinkages of additively manufactured parts. It is useful to predict the 3D printed parts to control unwanted distortions and shrinkages before their 3D printing. This study develops a two-phase numerical modelling and simulation process of AM process for 17-4PH stainless steel and it considers the importance of post-processing and the need for calibration to achieve a high-quality printing at the end. By using this proposed AM modelling and simulation process, optimal process parameters, material properties, and topology can be obtained to ensure a part 3D printed successfully

    InKS, a Programming Model to Decouple Performance from Algorithm in HPC Codes

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    International audienceExisting programming models tend to tightly interleave algorithm and optimization in HPC simulation codes. This requires scientists to become experts in both the simulated domain and the optimization process and makes the code difficult to maintain and port to new architectures. This paper proposes the InKS programming model that decouples these two concerns with distinct languages for each. The simulation algorithm is expressed in the InKS pia language with no concern for machine-specific optimizations. Optimizations are expressed using both a family of dedicated optimizations DSLs (InKS O) and plain C++. InKS O relies on the InKS pia source to assist developers with common optimizations while C++ is used for less common ones. Our evaluation demonstrates the soundness of the approach by using it on synthetic benchmarks and the Vlasov-Poisson equation. It shows that InKS offers separation of concerns at no performance cost
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