With the emergence of Internet of Things (IoT) devices collecting large amounts of data at the edges of the network, a new generation of hyper-distributed applications is emerging, spanning cloud, fog, and edge computing resources.The automated deployment and management of such applications requires orchestration tools that take a deployment descriptor (e.g.Kubernetes manifest, Helm chart or TOSCA) as input, and deploy and manage the execution of applications at run-time.While most deployment descriptors are prepared by a single person or organisation at one specific time, there are notable scenarios where such descriptors need to be created collaboratively by different roles or organisations, and at different times of the application's life cycle.An example of this scenario is the modular development of digital twins, composed of the basic building blocks of data, model and algorithm.Each of these building blocks can be created independently from each other, by different individuals or companies, at different times.The challenge here is to compose and build a deployment descriptor from these individual components automatically.This paper presents a novel solution to automate the collaborative composition and generation of deployment descriptors for distributed applications within the cloud-to-edge continuum.The implemented solution has been prototyped in over 25 industrial use cases within the DIGITbrain project, one of which is described in the paper as a representative example.

Abstract Interactive deformation via control handles is essential in computer graphics for the modeling of 3D geometry. Deformation control structures include lattices for free‐form deformation and skeletons for character articulation, but this report focuses on cage‐based deformation. Cages for deformation control are coarse polygonal meshes that encase the to‐be‐deformed geometry, enabling high‐resolution deformation. Cage‐based deformation enables users to quickly manipulate 3D geometry by deforming the cage. Due to their utility, cage‐based deformation techniques increasingly appear in many geometry modeling applications. For this reason, the computer graphics community has invested a great deal of effort in the past decade and beyond into improving automatic cage generation and cage‐based deformation. Recent advances have significantly extended the practical capabilities of cage‐based deformation methods. As a result, there is a large body of research on cage‐based deformation. In this report, we provide a comprehensive overview of the current state of the art in cage‐based deformation of 3D geometry. We discuss current methods in terms of deformation quality, practicality, and precomputation demands. In addition, we highlight potential future research directions that overcome current issues and extend the set of practical applications. In conjunction with this survey, we publish an application to unify the most relevant deformation methods. Our report is intended for computer graphics researchers, developers of interactive geometry modeling applications, and 3D modeling and character animation artists.

Abstract Large sparse matrices with compound entries, i.e. complex and quaternionic matrices as well as matrices with dense blocks, are a core component of many algorithms in geometry processing, physically based animation and other areas of computer graphics. We generalize several matrix layouts and apply joint schedule and layout autotuning to improve the performance of the sparse matrix‐vector product on massively parallel graphics processing units. Compared to schedule tuning without layout tuning, we achieve speedups of up to 5.5 × . In comparison to cuSPARSE, we achieve speedups of up to 4.7 × .

Abstract We present a novel bounding volume hierarchy for GPU-accelerated direct volume rendering (DVR) as well as volumetric mesh slicing and inside-outside intersection testing. Our novel octree-based data structure is laid out linearly in memory using space filling Morton curves. As our new data structure results in tightly fitting bounding volumes, boundary markers can be associated with nodes in the hierarchy. These markers can be used to speed up all three use cases that we examine. In addition, our data structure is memory-efficient, reducing memory consumption by up to 75%. Tree depth and memory consumption can be controlled using a parameterized heuristic during construction. This allows for significantly shorter construction times compared to the state of the art. For GPU-accelerated DVR, we achieve performance gain of 8.4 $$\times $$ × –13 $$\times $$ × . For 3D printing, we present an efficient conservative slicing method that results in a 3 $$\times $$ × –25 $$\times $$ × speedup when using our data structure. Furthermore, we improve volumetric mesh intersection testing speed by 5 $$\times $$ × –52 $$\times $$ × .

Abstract In this paper, we present a matrix assembly technique for arbitrary polynomial order finite element simulations on simplex meshes for graphics processing units (GPU). Compared to the current state of the art in GPU‐based matrix assembly, we avoid the need for an intermediate sparse matrix and perform assembly directly into the final, GPU‐optimized data structure. Thereby, we avoid the resulting 180% to 600% memory overhead, depending on polynomial order, and associated allocation time, while simplifying the assembly code and using a more compact mesh representation. We compare our method with existing algorithms and demonstrate significant speedups.

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In this paper, we present a novel approach for a tighter integration of 3D modeling and physically-based simulation. Instead of modeling 3D objects as surface models, we use a volumetric subdivision representation. Volumetric modeling operations allow designing 3D objects in similar ways as with surface-based modeling tools, while automatic checks and modifications of inner control points ensure consistency during the design process. Encoding the volumetric information already in the design mesh drastically simplifies and speeds up the mesh generation process for simulation. The transition between design, simulation and back to design is consistent and computationally cheap. Since the subdivision and mesh generation can be expressed as a precomputable matrix-vector multiplication, iteration times can be greatly reduced compared to common modeling and simulation setups. Therefore, this approach is especially well suited for early-stage modeling or optimization use cases, where many geometric changes are made in a short time and their physical effect on the model has to be evaluated frequently. To test our approach, we created, simulated and adapted several 3D models. We measured and evaluated the timings for generating and applying the matrices for different subdivision levels. Additionally, we computed several characteristic factors for mesh quality and mesh consistency. For comparison, we analyzed the tetrahedral meshing functionality offered by CGAL for similar numbers of elements. For changing topology, our implicit meshing approach proves to be up to 70 times faster than creating the tetrahedral mesh only based on the outer surface. Without changing the topology and by precomputing the matrices, we achieve a speed-up of up to 2800, as all the required information is already available.

Abstract In this paper, we present a novel volumetric mesh representation suited for parallel computing on modern GPU architectures. The data structure is based on a compact, ternary sparse matrix storage of boundary operators. Boundary operators correspond to the first‐order top‐down relations of k‐faces to their (k − 1)‐face facets. The compact, ternary matrix storage format is based on compressed sparse row matrices with signed indices and allows for efficient parallel computation of indirect and bottom‐up relations. This representation is then used in the implementation of several parallel volumetric mesh algorithms including Laplacian smoothing and volumetric Catmull‐Clark subdivision. We compare these algorithms with their counterparts based on OpenVolumeMesh and achieve speedups from 3× to 531×, for sufficiently large meshes, while reducing memory consumption by up to 36%.

Abstract We present a novel multigrid scheme based on a cut‐cell formulation on regular staggered grids which generates compatible systems of linear equations on all levels of the multigrid hierarchy. This geometrically motivated formulation is derived from a finite volume approach and exhibits an improved rate of convergence compared to previous methods. Existing fluid solvers with voxelized domains can directly benefit from this approach by only modifying the representation of the non‐fluid domain. The necessary building blocks are fully parallelizable and can therefore benefit from multi‐ and many‐core architectures.

Abstract We present graphics processing unit (GPU) data structures and algorithms to efficiently solve sparse linear systems that are typically required in simulations of multi‐body systems and deformable bodies. Thereby, we introduce an efficient sparse matrix data structure that can handle arbitrary sparsity patterns and outperforms current state‐of‐the‐art implementations for sparse matrix vector multiplication. Moreover, an efficient method to construct global matrices on the GPU is presented where hundreds of thousands of individual element contributions are assembled in a few milliseconds. A finite‐element‐based method for the simulation of deformable solids as well as an impulse‐based method for rigid bodies are introduced in order to demonstrate the advantages of the novel data structures and algorithms. These applications share the characteristic that a major computational effort consists of building and solving systems of linear equations in every time step. Our solving method results in a speed‐up factor of up to 13 in comparison to other GPU methods.

A personal computer can be considered as a one-node heterogeneous cluster that simultaneously processes several application tasks. It can be composed by, for example, asymmetric CPU and GPUs. This way, a high-performance heterogeneous platform is built on a desktop for data intensive engineering calculations. In our perspective, a workload distribution over the Processing Units (PUs) plays a key role in such systems. This issue presents challenges since the cost of a task at a PU is non-deterministic and can be affected by parameters not known a priori. This paper presents a context-aware runtime and tuning system based on a compromise between reducing the execution time of engineering applications - due to appropriate dynamic scheduling - and the cost of computing such scheduling applied on a platform composed of CPU and GPUs. Results obtained in experimental case studies are encouraging and a performance gain of 21.77% was achieved in comparison to the static assignment of all tasks to the GPU.

GPUs (Graphics Processing Units) have become one of the main co-processors that contributed to desktops towards high performance computing. Together with multi-core CPUs, a powerful heterogeneous execution platform is built for massive calculations. To improve application performance and explore this heterogeneity, a distribution of workload in a balanced way over the PUs (Processing Units) plays an important role for the system. However, this problem faces challenges since the cost of a task at a PU is non-deterministic and can be influenced by several parameters not known a priori, like the problem size domain. We present a comparison of iterative SLE (Systems of Linear Equations) solvers, used in many scientific and engineering applications, over a heterogeneous CPU-GPUs platform and characterize scenarios where the solvers obtain better performances. A new technique to improve memory access on matrix-vector multiplication used by SLEs on GPUs is described and compared to standard implementations for CPU and GPUs. Such timing profiling is analyzed and break-even points based on the problem sizes are identified for this implementation, pointing whether our technique is faster to use GPU instead of CPU. Preliminary results show the importance of this study applied to a real-time CFD (Computational Fluid Dynamics) application with geometry modification.

Many modern applications require high-performance platforms to deal with a variety of algorithms requiring massive calculations. Moreover, low-cost powerful hardware (e.g., GPU, PPU) and CPUs with multiple cores have become abundant, and can be combined in heterogeneous architectures. To cope with this, reconfigurable computing is a potential paradigm as it can provide flexibility to explore the computational resources on hybrid and multi-core desktop architectures. The workload can optimally be (re)distributed over heterogeneous cores along the lifecycle of an application, aiming for best performance. As the first step towards a run-time reconfigurable load-balancing framework, application requirements and crosscutting concerns related to timing play an important role for task allocation decisions. In this paper, we present the use of aspect-oriented paradigms to address non-functional application timing constraints in the design phase. The DERAF aspectspsila framework is extended to support reconfiguration requirements; and a strategy for load-balancing is described. In addition, we present preliminary evaluation using an Unmanned Aerial Vehicle (UAV) based surveillance system as case study.

Sensor networks are being applied in several emerging sophisticated applications due to the use of powerful and high-quality sensor nodes, such as radars and visible light cameras. However, these nodes need additional features to optimally benefit from heterogeneous modern computing platforms. Therefore, reconfigurable computing is a potential paradigm for those scenarios as it can provide flexibility to explore the computational resources on that kind of high performance computing system. This paper presents a reconfigurable sensor node allocation support, based on application requirements, provided by a middleware focused on heterogeneous sensor networks. In order to address this concern, an aspect-orientation paradigm and intelligent agents approach is proposed followed by an UAV case study.

In this paper we introduce Simulated Reality (SR) as a new concept for the interplay between simulation, optimization and interactive visualization. We see SR as a new metaphor for the interactive visual exploration of simulation and optimization results. The vision of Simulated Reality implies interactive behavior of simulations. Fact is today that simulations might still need hours of computation time, especially in crash worthiness. This paper shows approaches to come closer to the vision of SR. Combining design of experiments methods, metamodeling, new interpolation schemes and innovative graphics methods, we enable to user to interact with simulation parameters, optimization criteria and come to a new interpolated crash result within seconds. The approaches have been successfully applied for solution of real life car design optimization problems.

to present a challenge in terms of performance, robustness and accuracy. In particular mobile augmented reality applications are in need of tracking systems which can be wearable and do not cause a high processing load. In this paper we introduce a novel iterative geometric method for pose estimation from four co-planar points and we present the current status of PTrack, a marker-based single camera tracking system benefiting from this approach. The system uses an IDS uEye [1] camera, equipped with infrared flash strobes and infrared pass filter, which acquires grayscale images and sends them to a computer where an image pre-processing algorithm identifies potential projections of retro-reflective markers. Our novel pose estimation algorithm identifies possible labels composed of markers in a 2D post-processing using a divide-and-conquer strategy to segment the camera's image space and attempts an iterative geometric 3D reconstruction of position and orientation in camera space. In the end successfully reconstructed labels are compared to a database for identification. Their 6 DoF data as well as their ID is made available to applications through OpenTracker [2] framework. To assess the performance of our approach we compared PTrack to ARToolKit [3] - which has been adapted to work with the same camera - and final results show that pose estimation is more accurate and precise, in both translation and rotation.

Intuitive access to information in real environments is a challenge for information society technologies. Having this in mind, a new device for mixed reality applications called Virtual Showcase has been developed. It has been conceived to be used in museums and exhibitions, due to its compatibility with traditional museum showcases, offering additional information to the public by means of a simple, direct and intuitive interface. We present the real implementation of a Virtual Showcase passive-stereo prototype exhibited in a museum for three months. Some preliminary results concerning the evaluation process have also been included. Although the technology seems to be promising, implementation aspects such as size should be improved.

This paper introduces an immersive styling environment, which aims at closing the gap between 2D drawing and 3D modeling in the design process. The main goal of the styling system is to provide the user an easy to use interface hiding the inherent mathematic nature of CAD. Creating rough 3D sketches should literally be as intuitive as 2D sketching with pen and paper. To achieve this, the tools developed in our system benefit from the stylists' skills, acquired through training over time. This paper focuses on the stroke-input methods of our styling system. We present different techniques for creating and modifying 3D curves: stroke splitting, oversketching and taping. In addition we report on the viability of using input constraints in immersive environments to overcome inherent weaknesses.

Spacedesign is an innovative mixed reality (MR) application addressed to aesthetic design of free form curves and surfaces. It is a unique and comprehensive approach which uses task-specific configurations to support the design workflow from concept to mock-up evaluation and review. The first-phase conceptual design benefits from a workbench-like 3-D display for free hand sketching, surfacing and engineering visualization. Semitransparent stereo glasses augment the pre-production physical prototype by additional shapes, textures and annotations. Both workspaces share a common interface and allow collaboration and cooperation between different experts, who can configure the system for the specific task. A faster design workflow and CAD data consistency can be thus naturally achieved. Tests and collaborations with designers, mainly from automotive industry, are providing systematic feedback for this ongoing research. As far as the authors are concerned, there is no known similar approach that integrates the creation and editing phase of 3D curves and surfaces in virtual and augmented reality (VR/AR). Herein we see the major contribution of our new application.