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https://www.readbyqxmd.com/read/28436877/packing-vertex-data-into-hardware-decompressible-textures
#1
Kin Chung Kwan, Xuemiao Xu, Liang Wan, Tien-Tsin Wong, Wai-Man Pang
Most graphics hardware features memory to store textures and vertex data for rendering. However, because of the irreversible trend of increasing complexity of scenes, rendering a scene can easily reach the limit of memory resources. Thus, vertex data are preferably compressed, with a requirement that they can be decompressed during rendering. In this paper, we present a novel method to exploit existing hardware texture compression circuits to facilitate the decompression of vertex data in graphics processing unit (GPUs)...
April 18, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28413955/drug-discovery-and-molecular-dynamics-methods-applications-and-perspective-beyond-the-second-timescale
#2
Gerard Martínez-Rosell, Toni Giorgino, Matt J Harvey, Gianni de Fabritiis
Bio-molecular dynamics (MD) simulations based on graphical processing units (GPUs) were first released to the public in the early 2009 with the code ACEMD. Almost 8 years after, applications now encompass a broad range of molecular studies, while throughput improvements have opened the way to millisecond sampling timescales. Based on an extrapolation of the amount of sampling in published literature, the second timescale will be reached by the year 2022, and therefore we predict that molecular dynamics is going to become one of the main tools in drug discovery in both academia and industry...
April 14, 2017: Current Topics in Medicinal Chemistry
https://www.readbyqxmd.com/read/28411611/screening-methods-for-linear-scaling-short-range-hybrid-calculations-on-cpu-and-gpu-architectures
#3
Matthias Beuerle, Jörg Kussmann, Christian Ochsenfeld
We present screening schemes that allow for efficient, linear-scaling short-range exchange calculations employing Gaussian basis sets for both CPU and GPU architectures. They are based on the LinK [C. Ochsenfeld et al., J. Chem. Phys. 109, 1663 (1998)] and PreLinK [J. Kussmann and C. Ochsenfeld, J. Chem. Phys. 138, 134114 (2013)] methods, but account for the decay introduced by the attenuated Coulomb operator in short-range hybrid density functionals. Furthermore, we discuss the implementation of short-range electron repulsion integrals on GPUs...
April 14, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/28393937/accelerating-direct-quantum-dynamics-using-graphical-processing-units
#4
T J Penfold
Methods using a swarm of Gaussian basis functions to represent the nuclear wavefunction are a very appealing way to solve the time-dependent Schrödinger equation (TDSE) as they avoid the conventional scaling bottleneck of grid-based methods and provide a grid-free trajectory representation of the dynamics understudy. When coupled with direct (on-the-fly) dynamics, these methods offer the ability to simulate quantum dynamics of larger systems in full nuclear configuration space and avoid the requirement of a priori fitting of a potential energy surface...
April 10, 2017: Physical Chemistry Chemical Physics: PCCP
https://www.readbyqxmd.com/read/28373894/gerbil-a-fast-and-memory-efficient%C3%A2-k-mer-counter-with-gpu-support
#5
Marius Erbert, Steffen Rechner, Matthias Müller-Hannemann
BACKGROUND: A basic task in bioinformatics is the counting of k-mers in genome sequences. Existing k-mer counting tools are most often optimized for small k < 32 and suffer from excessive memory resource consumption or degrading performance for large k. However, given the technology trend towards long reads of next-generation sequencers, support for large k becomes increasingly important. RESULTS: We present the open source k-mer counting software Gerbil that has been designed for the efficient counting of k-mers for k ≥ 32...
2017: Algorithms for Molecular Biology: AMB
https://www.readbyqxmd.com/read/28344638/the-feasibility-of-genome-scale-biological-network-inference-using-graphics-processing-units
#6
Raghuram Thiagarajan, Amir Alavi, Jagdeep T Podichetty, Jason N Bazil, Daniel A Beard
Systems research spanning fields from biology to finance involves the identification of models to represent the underpinnings of complex systems. Formal approaches for data-driven identification of network interactions include statistical inference-based approaches and methods to identify dynamical systems models that are capable of fitting multivariate data. Availability of large data sets and so-called 'big data' applications in biology present great opportunities as well as major challenges for systems identification/reverse engineering applications...
2017: Algorithms for Molecular Biology: AMB
https://www.readbyqxmd.com/read/28269151/efficient-rendering-of-digitally-reconstructed-radiographs-on-heterogeneous-computing-architectures-using-central-slice-theorem
#7
Marwan Abdellah, Mohamed Abdallah, Mohamed Alzanati, Ayman Eldeib
Digitally reconstructed radiographs (DRRs) play a significant role in modern clinical radiation therapy. They are used to verify patient alignments during image guided therapies with 2D-3D image registration. The generation of DRRs can be implemented intuitively in O(N3) relying on direct volume rendering (DVR) methods, such as ray marching. This complexity imposes certain limitations on the rendering performance if high quality DRR images are needed. Those DRRs can be alternatively generated in the k-space using the central slice theorem in O(N2logN)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28254085/a-novel-end-to-end-classifier-using-domain-transferred-deep-convolutional-neural-networks-for-biomedical-images
#8
Shuchao Pang, Zhezhou Yu, Mehmet A Orgun
BACKGROUND AND OBJECTIVES: Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset...
March 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28251682/new-algorithm-for-tensor-contractions-on-multi-core-cpus-gpus-and-accelerators-enables-ccsd-and-eom-ccsd-calculations-with-over-1000-basis-functions-on-a-single-compute-node
#9
Ilya A Kaliman, Anna I Krylov
A new hardware-agnostic contraction algorithm for tensors of arbitrary symmetry and sparsity is presented. The algorithm is implemented as a stand-alone open-source code libxm. This code is also integrated with general tensor library libtensor and with the Q-Chem quantum-chemistry package. An overview of the algorithm, its implementation, and benchmarks are presented. Similarly to other tensor software, the algorithm exploits efficient matrix multiplication libraries and assumes that tensors are stored in a block-tensor form...
April 30, 2017: Journal of Computational Chemistry
https://www.readbyqxmd.com/read/28241511/a-weighted-spatial-spectral-kernel-rx-algorithm-and-efficient-implementation-on-gpus
#10
Chunhui Zhao, Jiawei Li, Meiling Meng, Xifeng Yao
The kernel RX (KRX) detector proposed by Kwon and Nasrabadi exploits a kernel function to obtain a better detection performance. However, it still has two limits that can be improved. On the one hand, reasonable integration of spatial-spectral information can be used to further improve its detection accuracy. On the other hand, parallel computing can be used to reduce the processing time in available KRX detectors. Accordingly, this paper presents a novel weighted spatial-spectral kernel RX (WSSKRX) detector and its parallel implementation on graphics processing units (GPUs)...
February 23, 2017: Sensors
https://www.readbyqxmd.com/read/28239253/application-performance-analysis-and-efficient-execution-on-systems-with-multi-core-cpus-gpus-and-mics-a-case-study-with-microscopy-image-analysis
#11
George Teodoro, Tahsin Kurc, Guilherme Andrade, Jun Kong, Renato Ferreira, Joel Saltz
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core-MIC) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core operations of the application. We correlate the observed performance with the characteristics of computing devices and data access patterns, computation complexities, and parallelization forms of the operations. The results show a significant variability in the performance of operations with respect to the device used...
January 2017: International Journal of High Performance Computing Applications
https://www.readbyqxmd.com/read/28227380/efficient-rendering-of-digitally-reconstructed-radiographs-on-heterogeneous-computing-architectures-using-central-slice-theorem
#12
Marwan Abdellah, Mohamed Abdallah, Mohamed Alzanati, Ayman Eldeib, Marwan Abdellah, Mohamed Abdallah, Mohamed Alzanati, Ayman Eldeib, Ayman Eldeib, Mohamed Abdallah, Mohamed Alzanati, Marwan Abdellah
Digitally reconstructed radiographs (DRRs) play a significant role in modern clinical radiation therapy. They are used to verify patient alignments during image guided therapies with 2D-3D image registration. The generation of DRRs can be implemented intuitively in O(N(3)) relying on direct volume rendering (DVR) methods, such as ray marching. This complexity imposes certain limitations on the rendering performance if high quality DRR images are needed. Those DRRs can be alternatively generated in the k-space using the central slice theorem in O(N(2)logN)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28208684/a-real-time-high-performance-computation-architecture-for-multiple-moving-target-tracking-based-on-wide-area-motion-imagery-via-cloud-and-graphic-processing-units
#13
Kui Liu, Sixiao Wei, Zhijiang Chen, Bin Jia, Genshe Chen, Haibin Ling, Carolyn Sheaff, Erik Blasch
This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©)...
February 12, 2017: Sensors
https://www.readbyqxmd.com/read/28198568/compressed-sensing-mri-reconstruction-from-3d-multichannel-data-using-gpus
#14
Ching-Hua Chang, Xiangdong Yu, Jim X Ji
PURPOSE: To accelerate iterative reconstructions of compressed sensing (CS) MRI from 3D multichannel data using graphics processing units (GPUs). METHODS: The sparsity of MRI signals and parallel array receivers can reduce the data acquisition requirements. However, iterative CS reconstructions from data acquired using an array system may take a significantly long time, especially for a large number of parallel channels. This paper presents an efficient method for CS-MRI reconstruction from 3D multichannel data using GPUs...
February 15, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/28160511/efficient-gaussian-density-formulation-of-volume-and-surface-areas-of-macromolecules-on-graphical-processing-units
#15
Baofeng Zhang, Denise Kilburg, Peter Eastman, Vijay S Pande, Emilio Gallicchio
We present an algorithm to efficiently compute accurate volumes and surface areas of macromolecules on graphical processing unit (GPU) devices using an analytic model which represents atomic volumes by continuous Gaussian densities. The volume of the molecule is expressed by means of the inclusion-exclusion formula, which is based on the summation of overlap integrals among multiple atomic densities. The surface area of the molecule is obtained by differentiation of the molecular volume with respect to atomic radii...
February 4, 2017: Journal of Computational Chemistry
https://www.readbyqxmd.com/read/28141583/towards-real-time-photon-monte-carlo-dose-calculation-in-the-cloud
#16
Peter Ziegenhein, Igor Kozin, Cornelis Philippus Kamerling, Uwe Oelfke
Near real-time application of Monte Carlo (MC) dose calculation in clinic and research is hindered by long computational runtimes of established software. Currently, fast MC software solutions are available utilising accelerators such as GPUs or clusters of central processing units (CPU)-based system. Both platforms are expensive in terms of purchase costs and maintenance and, in case of the GPU, provide only limited scalability. In this work we propose a cloud-based MC solution, which offers high scalability of accurate photon dose calculations...
January 31, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28140352/initial-development-of-gocmc-a-gpu-oriented-fast-cross-platform-monte-carlo-engine-for-carbon-ion-therapy
#17
Nan Qin, Marco Pinto, Zhen Tian, Georgios Dedes, Arnold Pompos, Steve B Jiang, Katia Parodi, Xun Jia
Monte Carlo (MC) simulation is considered as the most accurate method for calculation of absorbed dose and fundamental physics quantities related to biological effects in carbon ion therapy. To improve its computational efficiency, we have developed a GPU-oriented fast MC package named goCMC, for carbon therapy. goCMC simulates particle transport in voxelized geometry with kinetic energy up to 450 MeV u(-1). Class II condensed history simulation scheme with a continuous slowing down approximation was employed...
January 31, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28129194/securemed-secure-medical-computation-using-gpu-accelerated-homomorphic-encryption-scheme
#18
Alhassan Khedr, Glenn Gulak
Sharing the medical records of individuals among healthcare providers and researchers around the world can accelerate advances in medical research. While the idea seems increasingly practical due to cloud data services, maintaining patient privacy is of paramount importance. Standard encryption algorithms help protect sensitive data from outside attackers but they cannot be used to compute on this sensitive data while being encrypted. Homomorphic Encryption (HE) presents a very useful tool that can compute on encrypted data without the need to decrypt it...
January 23, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28109237/atomic-orbital-based-sos-mp2-with-tensor-hypercontraction-ii-local-tensor-hypercontraction
#19
Chenchen Song, Todd J Martínez
In the first paper of the series [Paper I, C. Song and T. J. Martinez, J. Chem. Phys. 144, 174111 (2016)], we showed how tensor-hypercontracted (THC) SOS-MP2 could be accelerated by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs). This reduced the formal scaling of the SOS-MP2 energy calculation to cubic with respect to system size. The computational bottleneck then becomes the THC metric matrix inversion, which scales cubically with a large prefactor. In this work, the local THC approximation is proposed to reduce the computational cost of inverting the THC metric matrix to linear scaling with respect to molecular size...
January 21, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/28087515/h-blast-a-fast-protein-sequence-alignment-toolkit-on-heterogeneous-computers-with-gpus
#20
Weicai Ye, Ying Chen, Yongdong Zhang, Yuesheng Xu
Motivation: The sequence alignment is a fundamental problem in bioinformatics. BLAST is a routinely used tool for this purpose with over 118 000 citations in the past two decades. As the size of bio-sequence databases grows exponentially, the computational speed of alignment softwares must be improved. Results: We develop the heterogeneous BLAST (H-BLAST), a fast parallel search tool for a heterogeneous computer that couples CPUs and GPUs, to accelerate BLASTX and BLASTP-basic tools of NCBI-BLAST...
April 15, 2017: Bioinformatics
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