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ShareScore release 0.9.0
Dataset results
9 results for “Computer Architecture”
Data and scripts for: Bayesian Phylogenetic Analysis on multi-core Compute Architectures: Implementation and evaluation of BEAGLE in RevBayes with MPI
<p>Phylogenies are central to many research areas in biology and commonly estimated using likelihood-based methods. Unfortunately, any likelihood-based method, including Bayesian inference, can be restrictively slow for large datasets–with many taxa and/or many sites in the sequence alignment–or complex substitution models. The primary limiting factor when using large datasets and/or complex models in probabilistic phylogenetic analyses is the likelihood calculation, which dominates the total computation time. To address this bottleneck, we incorporated the high-performance phylogenetic library BEAGLE into RevBayes, which enables multi-threading on multi-core CPUs and GPUs, as well as hardware-specific vectorized instructions for faster likelihood calculations. Our new implementation of RevBayes+BEAGLE retains the flexibility and dynamic nature that users expect from vanilla RevBayes. Additionally, we implemented a native parallelization within RevBayes without an external library using the message passing interface (MPI); RevBayes+MPI. We evaluated our new implementation of RevBayes+BEAGLE using multi-threading on CPUs and a powerful NVidia Titan V GPU against our native implementation of RevBayes+MPI. We found good improvements in speedup when multiple cores were used with up to 20-fold speedup when using multiple CPUs and over 90-fold speedup when using multiple GPU cores. The improvement depended on the data type used, DNA or amino acids, and the size of the alignment, but less on the size of the tree. We additionally investigated the cost of rescaling partial likelihoods to avoid numerical underflow and showed that unnecessarily frequent rescaling can increase runtimes 2.5 to 3-fold. Finally, we presented and compared a new approach to store partial likelihoods on branches instead of nodes which can speed up computations but comes at twice the memory requirements.</p> <p>Availability: The software described in the paper is available at https://github.com/revbayes/revbayes with documentation and tutorials found at https://revbayes.github.io.</p>
Dataset: Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled Cluster Theory for GPU-accelerated Computer Architectures
<p>This dataset collects the data (outputs, coordinate files) for the calculations presented in the manuscript "Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled<br> Cluster Theory for GPU-accelerated Computer Architectures".</p>
Data and scripts for: Bayesian Phylogenetic Analysis on multi-core Compute Architectures: Implementation and evaluation of BEAGLE in RevBayes with MPI
Open the record for dataset details and reuse information.
The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility
<p>Contains all the data:</p> <p>Bentsen, T., T.May, A. A. Kresnner, and T. Dau. The benefit of combining<br> a deep neural network architecture with ideal ratio mask estimation<br> in computational speech segregation to improve speech intelligibility.<br> PLOS ONE., in review.</p> <p>There are two folders:</p> <ol> <li><strong>WRSs:</strong> the Word Recognition Scores (WRSs) from the listener study. The matrix has dimensions 9 conditions x 20 subjects. Data is ordered corresponding to the following condition order:<br> 'UP', 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)', 'DNN (IBM)'; 'DNN (IBM, 40 ms)'; 'DNN (IRM)'; 'DNN (IRM, 40 ms)'</li> <li><strong>Masks:</strong> <ul> <li><strong>GMM-IBMs: </strong>IBMs and estimated IBMs for the models 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)'</li> <li><strong>DNN-IBMs:</strong> IBMs and estimated IBMs for the models 'DNN (IBM)'; 'DNN (IBM, 40 ms)'</li> <li><strong>DNN-IRMs</strong>: IRMs and estimated IRMs for the models 'DNN (IRM)'; 'DNN (IRM, 40 ms)'</li> </ul> </li> </ol>
In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks - Dataset
<p>This is the dataset of "<em>In materia</em> reservoir computing with a fully memristive architecture based on self-organizing nanowire networks"</p>
Computational Modeling Of Human Multisensory Spatial Representation By A Neural Architecture
<p>Dataset including both performance of human observers and the neural architecture, related to the manuscript:</p> <p>Computational Modeling Of Human Multisensory Spatial Representation By A Neural Architecture</p>
Data and Codes of Characterizing Uncertainties of Earth System Modeling with Heterogeneous Many-core Architecture Computing
<p>These are the supporting information to verify the results in the paper, including input data, model outputs, the postprocessing scripts and the source codes.</p>
Conveyor-mode single-electron shuttling in Si/SiGe for a scalable quantum computing architecture
<p>Dataset and Code for the Paper: Conveyor-mode single-electron shuttling in Si/SiGe for a scalable quantum computing architecture</p>
Computational modeling of human multisensory spatial representation by a neural architecture
<p>Architecture and processed dataset used to train it, referring to the manuscript:</p> <p>Computational modeling of human multisensory spatial representation by a neural architecture</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.