Search results for "sively"
showing 10 items of 40 documents
Accelerating bioinformatics applications via emerging parallel computing systems [Guest editorial]
2015
The papers in this issue focus on advanced parallel computing systems for bioinformatics applications. This papers provide a forum to publish recent advances in the improvement of handling bioinformatics problems on emerging parallel computing systems. These systems can be characterized by exploiting different types of parallelism, including fine-grained versus coarse-grained and thread-level parallelism versus datalevel parallelism versus request-level parallelism. Hence, parallel computing systems based on multi- and many-core CPUs, many-core GPUs, vector processors, or FPGAs offer the promise to massively accelerate many bioinformatics algorithms and applications, ranging from computeint…
SIMULATING SPIN MODELS ON GPU: A TOUR
2012
The use of graphics processing units (GPUs) in scientific computing has gathered considerable momentum in the past five years. While GPUs in general promise high performance and excellent performance per Watt ratios, not every class of problems is equally well suitable for exploiting the massively parallel architecture they provide. Lattice spin models appear to be prototypic examples of problems suitable for this architecture, at least as long as local update algorithms are employed. In this review, I summarize our recent experience with the simulation of a wide range of spin models on GPU employing an equally wide range of update algorithms, ranging from Metropolis and heat bath updates,…
Architecture-Driven Level Set Optimization: From Clustering to Sub-pixel Image Segmentation
2016
Thanks to their effectiveness, active contour models (ACMs) are of great interest for computer vision scientists. The level set methods (LSMs) refer to the class of geometric active contours. Comparing with the other ACMs, in addition to subpixel accuracy, it has the intrinsic ability to automatically handle topological changes. Nevertheless, the LSMs are computationally expensive. A solution for their time consumption problem can be hardware acceleration using some massively parallel devices such as graphics processing units (GPUs). But the question is: which accuracy can we reach while still maintaining an adequate algorithm to massively parallel architecture? In this paper, we attempt to…
A decade of research into player communities in online games
2013
The social dynamics of player communities in online games have been the subject of much research during the last decade. Following a systematic review of empirical research publications from 2000–2010, this article synthesizes the key methods and concepts researchers have used to study and characterize player communities. It also synthesizes the key aspects and operationalizations researchers have concentrated on. The analysis shows that qualitative approaches have been more common than quantitative ones. The concepts used to characterize player communities were often not clearly defined or overlapped in meaning. Yet they revealed a prevalence of micro (groups or teams), meso (guilds or org…
Noncovalent force spectroscopy using wide-field optical and diamond-based magnetic imaging
2019
A realization of the force-induced remnant magnetization spectroscopy (FIRMS) technique of specific biomolecular binding is presented where detection is accomplished with wide-field optical and diamond-based magnetometry using an ensemble of nitrogen-vacancy (NV) color centers. The technique may be adapted for massively parallel screening of arrays of nanoscale samples.
Motion analysis using the novelty filter
1991
Abstract An original approach to the motion analysis, based on the novelty filter, is proposed. The novelty filter stresses the novelties occurring in a pattern representing an image of the scene under consideration with respect to patterns representing previous images of the same scene, so that visual information about the motion of the objects is obtained. The novelty filter may be implemented by a neural network architecture, taking advantage of the capabilities of massive parallelism, adaptive learning and noise robustness. The novelty filter may learn the entire trajectory of an object, through an incremental learning of a sequence of images capturing the scene, thus emphasizing if the…
Inductive inference of recursive functions: Complexity bounds
2005
This survey includes principal results on complexity of inductive inference for recursively enumerable classes of total recursive functions. Inductive inference is a process to find an algorithm from sample computations. In the case when the given class of functions is recursively enumerable it is easy to define a natural complexity measure for the inductive inference, namely, the worst-case mindchange number for the first n functions in the given class. Surely, the complexity depends not only on the class, but also on the numbering, i.e. which function is the first, which one is the second, etc. It turns out that, if the result of inference is Goedel number, then complexity of inference ma…
Investigation of protein folding by coarse-grained molecular dynamics with the UNRES force field.
2010
Coarse-grained molecular dynamics simulations offer a dramatic extension of the time-scale of simulations compared to all-atom approaches. In this article, we describe the use of the physics-based united-residue (UNRES) force field, developed in our laboratory, in protein-structure simulations. We demonstrate that this force field offers about a 4000-times extension of the simulation time scale; this feature arises both from averaging out the fast-moving degrees of freedom and reduction of the cost of energy and force calculations compared to all-atom approaches with explicit solvent. With massively parallel computers, microsecond folding simulation times of proteins containing about 1000 r…
cuBool: Bit-Parallel Boolean Matrix Factorization on CUDA-Enabled Accelerators
2018
Boolean Matrix Factorization (BMF) is a commonly used technique in the field of unsupervised data analytics. The goal is to decompose a ground truth matrix C into a product of two matrices A and $B$ being either an exact or approximate rank k factorization of C. Both exact and approximate factorization are time-consuming tasks due to their combinatorial complexity. In this paper, we introduce a massively parallel implementation of BMF - namely cuBool - in order to significantly speed up factorization of huge Boolean matrices. Our approach is based on alternately adjusting rows and columns of A and B using thousands of lightweight CUDA threads. The massively parallel manipulation of entries …
MULTI AXIAL TESTING OF ADHESIVELY BONDEDJOINTS OF FIBER REINFORCED THERMOPLASTIC POLYMERS
2015
International audience; In order to predict the mechanical behaviorof adhesively bonded joints, it is necessary to develop robust numerical models.This robustness is only reached if an extensive experimental database with tensile, shear and complex combined peel and shear loads can beestablished. The purpose of this study is to present a multi axialdevice for testing adhesively bonded joints, using KS2-type specimens traditionally utilized for spot-weld characterization. The tests were conducted on a glass fiber reinforced thermoplastic polymer(PA6-6) composite adhesively bonded with a flexible polyurethane adhesive. This adhesive/substrate combination allowsshort process times and good per…