Search Results for "performance"

Vispy is an open-source, high-performance interactive visualization library in Python, designed for creating scientific visualizations and interactive plots. It leverages the power of modern Graphics Processing Units (GPUs) through OpenGL to render large datasets efficiently. Vispy supports a wide range of visualization types, including 2D plots, 3D visualizations, volume rendering, and more, making it suitable for scientific research, data analysis, and educational purposes.

PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective. Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. The details of these algorithms are described in the PySR paper. Symbolic regression works best on low-dimensional datasets, but one can also extend these approaches to higher-dimensional spaces by using "Symbolic Distillation" of Neural Networks, as explained in 2006.11287, where we apply it to N-body problems. ...

...Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools.

...Citing TexGen We would be grateful if you could acknowledge use of TexGen where appropriate and suggest using one of the following references: L P Brown and A C Long. "Modelling the geometry of textile reinforcements for composites: TexGen", Chapter 8 in "Composite reinforcements for optimum performance (Second Edition)", ed. P Boisse, Woodhead Publishing Ltd, 2021, ISBN: 978-0-12-819005-0. https://doi.org/10.1016/B978-0-12-819005-0.00008-3 Lin, H., Brown, L. P. & Long, A. C. 2011. Modelling and Simulating Textile Structures using TexGen. Advanced Materials Research, 331, 44-47. To reference version 3.13.0 please use: Louise Brown, mike-matveev, & georgespackman. (2023). louisepb/TexGen: TexGen v3.13.1 (v3.13.1). ...

PanelCheck is an easy-to-use software tool for visualization of sensory profiling data using different types of plots. The joint information from the implemented plots provide detailed insight into assessor and panel performance.

This is a Fortran Module that merges the performance of the computation of the Fortran with the power of a Python Package called Matplotlib plot the data computed by your fortran code. It allows you to divide you data into groups of datafiles and each group is stored on its own directory. It allows you to create different types of plotting files such as, PNG file for each datafile and PDF and MPEG files for each group of datafiles.

Cca-forum unifies the Common Component Architecture tools and tutorial. It includes the CCA specifications, the Ccaffeine framework for HPC, and related tools. These support multilanguage scientific and parallel computing.

QuickFlash is a C++-based analysis library for data files generated by the Flash hydrodynamics code. It provides high-performance access to large datasets in low memory situations and other restrictive environments.

*Project home now moved to Google Code.* Numerical computing and plotting tools for IronPython.

PyVisi is the Python visualisation interface: a generic Python-based interface to many different scientific visualisation packages. PyVisi is intended for use in both standard and high-performance computing environments, and with the escript package.

pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...