Avtech Scientific
Advanced Simulation Library is a free and open source multiphysics simulation software package and a tool for solving Partial Differential Equations. It has significant user base across many areas of engineering and science, from both industrial and academic organizations. ASL utilizes only the methods that allow efficient parallelization: Lattice Boltzmann Methods, Explicit Finite Difference, Matrix […]
Jens Glaser, Andrew S. Karas, Sharon C. Glotzer
We present an algorithm to simulate the many-body depletion interaction between anisotropic colloids in an implicit way, integrating out the degrees of freedom of the depletants, which we treat as an ideal gas. Because the depletant particles are statistically independent and the depletion interaction is short-ranged, depletants are randomly inserted in parallel into the excluded […]
Luke Campagnola, Almar Kleink, Eric Larson, Cyrille Rossant, Nicolas Rougier
The growing availability of large, multidimensional data sets has created demand for high-performance, interactive visualization tools. VisPy leverages the GPU to provide fast, interactive, and beautiful visualizations in a high-level API. Here we introduce the main features, architecture, and techniques used in VisPy.
Tayler H. Hetherington, Mike O'Connor, Tor M. Aamodt
This paper tackles the challenges of obtaining more efficient data center computing while maintaining low latency, low cost, programmability, and the potential for workload consolidation. We introduce GNoM, a software framework enabling energy-efficient, latency bandwidth optimized UDP network and application processing on GPUs. GNoM handles the data movement and task management to facilitate the development […]
Max Danielsson, Thomas Sievert
CONTEXT: Embedded platforms GPUs are reaching a level of performance comparable to desktop hardware. Therefore it becomes interesting to apply Computer Vision techniques to modern smartphones.The platform holds different challenges, as energy use and heat generation can be an issue depending on load distribution on the device. OBJECTIVES: We evaluate the viability of a feature […]
Ursula Iturraran-Viveros, Miguel Molero-Armenta
Graphics processing units (GPUs) have become increasingly powerful in recent years. Programs exploring the advantages of this architecture could achieve large performance gains and this is the aim of new initiatives in high performance computing. The objective of this work is to develop an efficient tool to model 2D elastic wave propagation on parallel computing […]
Yunjin Chen, Thomas Pock
Image restoration is a long-standing problem in low-level computer vision with many interesting applications. We describe a flexible learning framework to obtain simple but effective models for various image restoration problems. The proposed approach is based on the concept of nonlinear reaction diffusion, but we extend conventional nonlinear reaction diffusion models by highly parametrized linear […]
Wei Wang, Gang Chen, Tien Tuan Anh Dinh, Jinyang Gao, Beng Chin Ooi, Kian-Lee Tan, Sheng Wang
Recently, deep learning techniques have enjoyed success in various multimedia applications, such as image classification and multimodal data analysis. Two key factors behind deep learning’s remarkable achievement are the immense computing power and the availability of massive training datasets, which enable us to train large models to capture complex regularities of the data. There are […]
Gavin Davidson
The self organising map is a machine learning algorithm used to produce low dimensional representations of high dimensional data. While the process is becoming more and more useful with the rise of big data, it is hindered by the sheer amount of time the algorithm takes to run serially. This project produces a parallel version […]
Limin Wang, Sheng Guo, Weilin Huang, Yu Qiao
VGGNets have turned out to be effective for object recognition in still images. However, it is unable to yield good performance by directly adapting the VGGNet models trained on the ImageNet dataset for scene recognition. This report describes our implementation of training the VGGNets on the large-scale Places205 dataset. Specifically, we train three VGGNet models, […]
Martin Marinov, Nicholas Nash, David Gregg
The minimal sets within a collection of sets are defined as the ones which do not have a proper subset within the collection, and the maximal sets are the ones which do not have a proper superset within the collection. Identifying extremal sets is a fundamental problem with a wide-range of applications in SAT solvers, […]
M. M. Cheng, V. A. Prisacariu, S. Zheng, P. H. S. Torr, C. Rother
Figure-ground segmentation from bounding box input, provided either automatically or manually, has been extremely popular in the last decade and influenced various applications. A lot of research has focused on highquality segmentation, using complex formulations which often lead to slow techniques, and often hamper practical usage. In this paper we demonstrate a very fast segmentation […]
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