A Multi-GPU Programming Library for Real-Time Applications

We present MGPU, a C++ programming library targeted at single-node multi-GPU systems. Such systems combine disproportionate floating point performance with high data locality and are thus well suited to implement real-time algorithms. We describe the library design, programming interface and implementation details in light of this specific problem domain. The core concepts of this work are a novel kind of container abstraction and MPI-like communication methods for intra-system communication. We further demonstrate how MGPU is used as a framework for porting existing GPU libraries to multi-device architectures. Putting our library to the test, we accelerate an iterative non-linear image reconstruction algorithm for real-time magnetic resonance imaging using multiple GPUs. We achieve a speed-up of about 1.7 using 2 GPUs and reach a final speed-up of 2.1 with 4 GPUs. These promising results lead us to conclude that multi-GPU systems are a viable solution for real-time MRI reconstruction as well as signal-processing applications in general.Comment: 15 pages, 10 figure

Plane-Based Optimization of Geometry and Texture for RGB-D Reconstruction of Indoor Scenes

We present a novel approach to reconstruct RGB-D indoor scene with plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed by some 3D reconstruction method on the sequence, and generate a lightweight, low-polygonal mesh with clear face textures and sharp features without losing geometry details from the original scene. To achieve this, we firstly partition the input mesh with plane primitives, simplify it into a lightweight mesh next, then optimize plane parameters, camera poses and texture colors to maximize the photometric consistency across frames, and finally optimize mesh geometry to maximize consistency between geometry and planes. Compared to existing planar reconstruction methods which only cover large planar regions in the scene, our method builds the entire scene by adaptive planes without losing geometry details and preserves sharp features in the final mesh. We demonstrate the effectiveness of our approach by applying it onto several RGB-D scans and comparing it to other state-of-the-art reconstruction methods.Comment: in International Conference on 3D Vision 2018; Models and Code: see https://github.com/chaowang15/plane-opt-rgbd. arXiv admin note: text overlap with arXiv:1905.0885

A fast framework construction and visualization method for particle-based fluid

© 2017, The Author(s). Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those issues, we present a fast framework for 3D fluid fast constructing and visualization which parallelizes the fluid algorithm based on the GPU computing framework and designs a direct surface visualization method for particle-based fluid data such as WCSPH, IISPH, and PCISPH. Considering on conventional polygonization or adaptive mesh methods may incur high computing costs and detail losses, an improved particle-based method is provided for real-time fluid surface rendering with the screen-space technology and the utilities of the modern graphics hardware to achieve the high performance rendering; meanwhile, it effectively protects fluid details. Furthermore, to realize the fast construction of scenes, an optimized design of parallel framework and interface is also discussed in our paper. Our method is convenient to enforce, and the results demonstrate a significant improvement in the performance and efficiency by being compared with several examples

PRZYSPIESZANIE PROCESU REKONSTRUKCJI OBRAZU W ELEKTRYCZNEJ TOMOGRAFII POJEMNOŚCIOWEJ 3D Z WYKORZYSTANIEM HETEROGENICZNEGO SYSTEMU MULTI-GPU

Electrical capacitance tomography is an innovative method for visualization of industrial processes. One of its main advantages is it’s high time resolution that allows to the usage of ECT in systems with high volatility. In recent years there has been significant development of electrical capacitance tomography 3D, which however, has significantly reduced industrial it’s applications due to the complicated process of image reconstruction. The authors propose the use of multi-node, multi-GPU system to accelerate the process of image reconstruction in ECT 3D.Elektryczna tomografia pojemnościowa jest innowacyjną metodą wizualizacji procesów przemysłowych. Jedną z jej głównych zalet jest duża rozdzielczość czasowa pozwalająca na zastosowanie ECT w instalacjach o dużej zmienności. W ostatnich latach nastąpił znaczący rozwój elektrycznej tomografii pojemnościowej 3D, która jednakże ma znacznie ograniczone zastosowanie przemysłowe ze względu na skomplikowany proces rekonstrukcji obrazu. Autorzy artykułu proponują zastosowanie wielowęzłowego systemu Multi-GPU do przyspieszenia procesu rekonstrukcji obrazu w ECT 3D