16 papers · ranked by Valyu relevance
Ludovico Rella
This paper investigates the role of the materiality of computation in two domains: blockchain technologies and artificial intelligence (AI). Although historically designed as parallel computing accelerators for image rendering and videogames, graphics processing units (GPUs) have been instrumental in the explosion of…
Ivan Komarov, Ali Dashti, Roshan M. D'Souza, Moncho Gomez-Gesteira
In this paper, we describe a new brute force algorithm for building the -Nearest Neighbor Graph (k-NNG). The k-NNG algorithm has many applications in areas such as machine learning, bio-informatics, and clustering analysis. While there are very efficient algorithms for data of low dimensions, for high dimensional data…
Heeseung Jo, Jinkyu Jeong, Myoungho Lee, Dong Hoon Choi
Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environment to enhance their…
Alejandro C. Crespo, Jose M. Dominguez, Anxo Barreiro, Moncho Gómez-Gesteira + 2 more
'Moncho Gómez-Gesteira' 'Benedict D. Rogers' 'Jörg Langowski'] Smoothed Particle Hydrodynamics (SPH) is a numerical method commonly used in Computational Fluid Dynamics (CFD) to simulate complex free-surface flows. Simulations with this mesh-free particle method far exceed the capacity of a single processor. In this…
Guillermo Vigueras, Ishani Roy, Andrew Cookson, Jack Lee + 2 more
'Nicolas Smith' 'David Nordsletten'] In this paper, we look at the acceleration of weakly coupled electromechanics using the graphics processing unit (GPU). Specifically, we port to the GPU a number of components of Heart-a CPU-based finite element code developed for simulating multi-physics problems. On the basis of a…
Wei Wang, Lifan Xu, John Cavazos, Howie H. Huang + 2 more
'Tobias Preis'] Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires…
Hao Li, Yi-Cheng Tu, Bo Zeng, Rashid Mehmood
The unrivaled computing capabilities of modern GPUs meet the demand of processing massive amounts of data seen in many application domains. While traditional HPC systems support applications as standalone entities that occupy entire GPUs, there are GPU-based DBMSs where multiple tasks are meant to be run at the same…
Jing He, Zhou Zhou, Michael Reed, Andrea Califano
Background The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE) represents one of the most effective tools to reconstruct gene regulatory networks from large-scale molecular profile datasets. However, previous implementations require intensive computing resources and, in some cases, restrict the…
Yanyan Sheng, William S. Welling, Michelle M. Zhu
Item response theory (IRT) is a popular approach used for addressing large-scale statistical problems in psychometrics as well as in other fields. The fully Bayesian approach for estimating IRT models is usually memory and computationally expensive due to the large number of iterations. This limits the use of the…
Yong Xia, Kuanquan Wang, Henggui Zhang
Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs.…
Ginés D. Guerrero, Baldomero Imbernón, Horacio Pérez-Sánchez, Francisco Sanz + 2 more
'Francisco Sanz' 'José M. García' 'José M. Cecilia'] Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest…
Guoqing Lei, Yong Dou, Wen Wan, Fei Xia + 3 more
'Dan Zou'] Background Prediction of ribonucleic acid (RNA) secondary structure remains one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. Thus far, few studies have been reported on the…
Esin Yavuz, James Turner, Thomas Nowotny
Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal…
Wei-Jen Wang, I-Fan Hsieh, Chun-Chuan Chen, Maurice J. Chacron
This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the…
Che-Lun Hung, Guan-Jie Hua
With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing…
José M. Cecilia, Juan-Carlos Cano, Juan Morales-García, Antonio Llanes + 1 more
'Antonio Llanes' 'Baldomero Imbernón'] Internet of Things (IoT) is becoming a new socioeconomic revolution in which data and immediacy are the main ingredients. IoT generates large datasets on a daily basis but it is currently considered as “dark data”, i.e., data generated but never analyzed. The efficient analysis of…