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George Kantasis, Christos G Xanthis, Kostas Haris, Einar Heiberg, Anthony H Aletras
Quantitative Magnetic Resonance Imaging (MRI) is a research tool, used more and more in clinical practice, as it provides objective information with respect to the tissues being imaged. Pixel-wise T1 quantification (T1 mapping) of the myocardium is one such application with diagnostic significance. A number of mapping sequences have been developed for myocardial T1 mapping with a wide range in terms of measurement accuracy and precision. Furthermore, measurement results obtained with these pulse sequences are affected by errors introduced by the particular acquisition parameters used...
November 17, 2016: Journal of Magnetic Resonance
Dari Kimanius, Björn O Forsberg, Sjors Hw Scheres, Erik Lindahl
By reaching near-atomic resolution for a wide range of specimens, single-particle cryo-EM structure determination is transforming structural biology. However, the necessary calculations come at increased computational costs, introducing a bottleneck that is currently limiting throughput and the development of new methods. Here, we present an implementation of the RELION image processing software that uses graphics processors (GPUs) to address the most computationally intensive steps of its cryo-EM structure determination workflow...
November 15, 2016: ELife
Jessica A Nash, Albert L Kwansa, James Samuel Peerless, Ho Shin Kim, Yaroslava G Yingling
Nanoparticles (NPs) play increasingly important roles in nanotechnology and nanomedicine where nanoparticle surface chemistry allows for control over interactions with other nanoparticles and biomolecules. In particular, for applications in drug and gene delivery, a fundamental understanding of the NP-nucleic acid interface allows for development of more efficient and effective nanoparticle carriers. Computational modeling can provide insights of processes occurring at the inorganic NP-nucleic interface, in detail which is difficult to access by experimental methods...
October 24, 2016: Bioconjugate Chemistry
Nan Qin, Pablo Botas, Drosoula Giantsoudi, Jan Schuemann, Zhen Tian, Steve B Jiang, Harald Paganetti, Xun Jia
Monte Carlo (MC) simulation is commonly considered as the most accurate dose calculation method for proton therapy. Aiming at achieving fast MC dose calculations for clinical applications, we have previously developed a graphics-processing unit (GPU)-based MC tool, gPMC. In this paper, we report our recent updates on gPMC in terms of its accuracy, portability, and functionality, as well as comprehensive tests on this tool. The new version, gPMC v2.0, was developed under the OpenCL environment to enable portability across different computational platforms...
October 3, 2016: Physics in Medicine and Biology
Jia Zhao, Paisa Seeluangsawat, Qi Wang
A multiphasic, hydrodynamic model for spatially heterogeneous biofilms based on the phase field formulation is developed and applied to analyze antimicrobial tolerance of biofilms by acknowledging the existence of persistent and susceptible cells in the total population of bacteria. The model implements a new conversion rate between persistent and susceptible cells and its homogeneous dynamics is bench-marked against a known experiment quantitatively. It is then discretized and solved on graphic processing units (GPUs) in 3-D space and time...
December 2016: Mathematical Biosciences
Christian Hundt, Andreas Hildebrandt, Bertil Schmidt
BACKGROUND: Gene Set Enrichment Analysis (GSEA) is a popular method to reveal significant dependencies between predefined sets of gene symbols and observed phenotypes by evaluating the deviation of gene expression values between cases and controls. An established measure of inter-class deviation, the enrichment score, is usually computed using a weighted running sum statistic over the whole set of gene symbols. Due to the lack of analytic expressions the significance of enrichment scores is determined using a non-parametric estimation of their null distribution by permuting the phenotype labels of the probed patients...
2016: BMC Bioinformatics
Preston J MacDougall, Christopher E Henze, Anatoliy Volkov
We present a unique platform for molecular visualization and design that uses novel subatomic feature detection software in tandem with 3D hyperwall visualization technology. We demonstrate the fleshing-out of pharmacophores in drug molecules, as well as reactive sites in catalysts, focusing on subatomic features. Topological analysis with picometer resolution, in conjunction with interactive volume-rendering of the Laplacian of the electronic charge density, leads to new insight into docking and catalysis...
September 5, 2016: Journal of Molecular Graphics & Modelling
Michio Katouda, Akira Naruse, Yukihiko Hirano, Takahito Nakajima
A new parallel algorithm and its implementation for the RI-MP2 energy calculation utilizing peta-flop-class many-core supercomputers are presented. Some improvements from the previous algorithm (J. Chem. Theory Comput. 2013, 9, 5373) have been performed: (1) a dual-level hierarchical parallelization scheme that enables the use of more than 10,000 Message Passing Interface (MPI) processes and (2) a new data communication scheme that reduces network communication overhead. A multi-node and multi-GPU implementation of the present algorithm is presented for calculations on a central processing unit (CPU)/graphics processing unit (GPU) hybrid supercomputer...
November 15, 2016: Journal of Computational Chemistry
Jaewoon Jung, Akira Naurse, Chigusa Kobayashi, Yuji Sugita
The graphics processing unit (GPU) has become a popular computational platform for molecular dynamics (MD) simulations of biomolecules. A significant speedup in the simulations of small- or medium-size systems using only a few computer nodes with a single or multiple GPUs has been reported. Because of GPU memory limitation and slow communication between GPUs on different computer nodes, it is not straightforward to accelerate MD simulations of large biological systems that contain a few million or more atoms on massively parallel supercomputers with GPUs...
October 11, 2016: Journal of Chemical Theory and Computation
Alexander E Doran, So Hirata
In the Monte Carlo second-order many-body perturbation (MC-MP2) method, the long sum-of-product matrix expression of the MP2 energy, whose literal evaluation may be poorly scalable, is recast into a single high-dimensional integral of functions of electron pair coordinates, which is evaluated by the scalable method of Monte Carlo integration. The sampling efficiency is further accelerated by the redundant-walker algorithm, which allows a maximal reuse of electron pairs. Here, a multitude of graphical processing units (GPUs) offers a uniquely ideal platform to expose multilevel parallelism: fine-grain data-parallelism for the redundant-walker algorithm in which millions of threads compute and share orbital amplitudes on each GPU; coarse-grain instruction-parallelism for near-independent Monte Carlo integrations on many GPUs with few and infrequent interprocessor communications...
October 11, 2016: Journal of Chemical Theory and Computation
Mark E Adamo, Scott A Gerber
MS/MS database search algorithms derive a set of candidate peptide sequences from in silico digest of a protein sequence database, and compute theoretical fragmentation patterns to match these candidates against observed MS/MS spectra. The original Tempest publication described these operations mapped to a CPU-GPU model, in which the CPU (central processing unit) generates peptide candidates that are asynchronously sent to a discrete GPU (graphics processing unit) to be scored against experimental spectra in parallel...
2016: Current Protocols in Bioinformatics
J Neylon, Y Min, P Kupelian, D A Low, A Santhanam
PURPOSE: In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. METHODS: An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network...
August 25, 2016: International Journal of Computer Assisted Radiology and Surgery
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 based on the concept of nonlinear reaction diffusion models for various image restoration problems. By embodying recent improvements in nonlinear diffusion models, we propose a dynamic nonlinear reaction diffusion model with time-dependent parameters (i.e., linear filters and influence functions). In contrast to previous nonlinear diffusion models, all the parameters, including the filters and the influence functions, are simultaneously learned from training data through a loss based approach...
August 1, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
John E Stone, Michael J Hallock, James C Phillips, Joseph R Peterson, Zaida Luthey-Schulten, Klaus Schulten
Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance...
May 2016: IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum: [proceedings]
Alex Albaugh, Henry A Boateng, Richard T Bradshaw, Omar N Demerdash, Jacek Dziedzic, Yuezhi Mao, Daniel T Margul, Jason Swails, Qiao Zeng, David A Case, Peter Eastman, Lee-Ping Wang, Jonathan W Essex, Martin Head-Gordon, Vijay S Pande, Jay W Ponder, Yihan Shao, Chris-Kriton Skylaris, Ilian T Todorov, Mark E Tuckerman, Teresa Head-Gordon
Advanced potential energy surfaces are defined as theoretical models that explicitly include many-body effects that transcend the standard fixed-charge, pairwise-additive paradigm typically used in molecular simulation. However, several factors relating to their software implementation have precluded their widespread use in condensed-phase simulations: the computational cost of the theoretical models, a paucity of approximate models and algorithmic improvements that can ameliorate their cost, underdeveloped interfaces and limited dissemination in computational code bases that are widely used in the computational chemistry community, and software implementations that have not kept pace with modern high-performance computing (HPC) architectures, such as multicore CPUs and modern graphics processing units (GPUs)...
September 22, 2016: Journal of Physical Chemistry. B
Haiyong Wu, Geng Chen, Yan Jin, Dinggang Shen, Pew-Thian Yap
Global tractography estimates brain connectivity by organizing signal-generating fiber segments in an optimal configuration that best describes the measured diffusion-weighted data, promising better stability than local greedy methods with respect to imaging noise. However, global tractography is computationally very demanding and requires computation times that are often prohibitive for clinical applications. We present here a reformulation of the global tractography algorithm for fast parallel implementation amendable to acceleration using multi-core CPUs and general-purpose GPUs...
2016: Frontiers in Neuroinformatics
Sunghwan Choi, Oh-Kyoung Kwon, Jaewook Kim, Woo Youn Kim
We investigated the performance of heterogeneous computing with graphics processing units (GPUs) and many integrated core (MIC) with 20 CPU cores (20×CPU). As a practical example toward large scale electronic structure calculations using grid-based methods, we evaluated the Hartree potentials of silver nanoparticles with various sizes (3.1, 3.7, 4.9, 6.1, and 6.9 nm) via a direct integral method supported by the sinc basis set. The so-called work stealing scheduler was used for efficient heterogeneous computing via the balanced dynamic distribution of workloads between all processors on a given architecture without any prior information on their individual performances...
September 15, 2016: Journal of Computational Chemistry
Joongseok Song, Changseob Kim, Hanhoon Park, Jong-Il Park
We propose a practical system that can effectively mix the depth data of real and virtual objects by using a Z buffer and can quickly generate digital mixed reality video holograms by using multiple graphic processing units (GPUs). In an experiment, we verify that real objects and virtual objects can be merged naturally in free viewing angles, and the occlusion problem is well handled. Furthermore, we demonstrate that the proposed system can generate mixed reality video holograms at 7.6 frames per second. Finally, the system performance is objectively verified by users' subjective evaluations...
July 10, 2016: Applied Optics
Marco S Nobile, Paolo Cazzaniga, Andrea Tangherloni, Daniela Besozzi
Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances...
July 8, 2016: Briefings in Bioinformatics
G C P van Zundert, A M J J Bonvin
Cryo-electron microscopy provides fascinating structural insight into large macromolecular machines at increasing detail. Despite significant advances in the field, the resolution of the resulting three-dimensional images is still typically insufficient for de novo model building. To bridge the resolution gap and give an atomic interpretation to the data, high-resolution models are typically placed into the density as rigid bodies. Unfortunately, this is often done manually using graphics software, a subjective method that can lead to over-interpretation of the data...
August 2016: Journal of Structural Biology
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