23 Works

The nanoporous gold data set

Emanuel Larsson, Malte Storm, Fabian Wilde, Markus Ziehmer, Kaixiong Hu, Doga Gursoy, Francesco De Carlo, Erica Lilleodden, Martin Muller & Imke Greving

GEOPHIRES v2.0

Koenraad Beckers & Kevin McCabe
GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for "GEOthermal energy for Production of Heat and electricity (“IR”) Economically Simulated". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications...

IdahoLabCuttingBoard/ADREM

Ian Hobbs & Joey Charboneau
Analytical Data Reduction Excel Macro

Holotomography Phase-Retrieval

Jean Forier
Holotomography is a non-destructive x-ray imaging technique which allows to visualize the interior morphology of object without damaging them. It is similar to x-ray computed tomography (CT), but unlike conventional CT, which is based on the attenuation of x-rays passing through the object, holotomography exploits the phase shift caused by the sample. This phase-contrast imaging allows to increase image contrast by recovering refractive index of materials and is proven to be more sensitive to density...

Single Episode Policy Transfer

Brenden Petersen & Daniel Faissol
Reinforcement learning (RL) aims to learn optimal strategies for control problems with complex, stochastic dynamics. Standard RL formulations assume that transition dynamics are the same across episodes. However, this is not the case for many real-world environments, e.g. a disease process in which each patient is unique. Transfer learning in RL aims to solve this problem; however, existing methods allow for multiple trials on a test episode. We consider the "single episode transfer" setting in...

Bindee

Jason Kimkno
Bindee is a clang tool that outputs a simple pybind11 template given a C++ file for efficient generation of C++-Python bindings. Bindee is intended to be a helper tool for minimizing initial user effort and safeguarding against common runtime errors. Bindee relies on two open-source software to produce bindings. Clang's LibTooling enables bindee to traverse a C++ file's AST to pick out bindable variables and functions, or "bindees." PyBind11 is templated, header-only library for generating...

Multispecies Hypersonic Flow Simulator

Debojyoti Ghosh
MHYSA is a conservative finite-difference code to solve the 1D, 2D, and 3D multispecies Navier-Stokes equations for hypersonic flow applications. It supports Cartesian grids only and has the option of including immersed boundaries. - Solves 1D Euler and 2D and 3D Navier-Stokes equations. - Solves the PDEs over Cartesian grids. - Written entirely in C and uses the MPICH library. It also uses OpenMP threads but this is a work-inprogress. - Can be compiled with...

Magpie

Al Chu, Brian Penneton, Brian Sammuli, Félix-Antoine Fortin, Ian Lee, Josh Asplund, Milinda Pathirage & Neale Petrillo
Magpie contains a number of scripts for running Big Data software in HPC environments, including Hadoop and Spark. There is support for Lustre, Slurm, Moab, Torque. and LSF.

Copson Expansion Solution

Robert Managan
Evaluate Copson's solution for the free expansion of an ideal gas into vacuum. The solution for streamlines and characteristics are given along with a way to evaluate the solution for any (x,t) location.

Detection Framework Testbed and Toolkit

Douglas Dodge
The Detection Framework Testbed and Toolkit (DFTT) is a signal detection system that uses automatically generated subspace and correlation detectors. DFTT is intended to facilitate the development and testing of algorithms for operating suites of such detectors. The software is a generalization of the system described in Harris and Dodge (2011) and has been applied in contexts ranging from local borehole induced seismicity to large-scale teleseismic observations. The software includes interactive applications for creating detection...

Active Learning for NLP Systems

Andre Goncalves, Ana Sales, Hiranmayi Ranganathan, Braden Soper & Priyadip Ray
This software implements an active learning framework for Natural Language Processing (NLP) systems. It is intended to be applied on scenarios where limited amount of labeled data is available to train a machine learning-based NLP classification system, but a large set of unlabeled documents exist. This software will point, from the set of unlabeled documents, which ones we should label next so that the overall performance of the classifier is improved.

Remote Mirror Security

Thomas Mendoza
The Remote Mirror Security project is a git hook used to evaluate a remote repository from which changes are mirrored and enforce a security policy before accepting changes.

ICITools v1.0

Benjamin Cole
Identification of cell state based on objective metrics is a fundamental problem in developmental biology. With the advent of fluorescent activated cell sorting (FACS), transcriptomics, and (more recently) single-cell RNA sequencing, it has become possible to profile mRNA abundance of all genes in individual cells or cell types. This transcriptomic information for cell types is often characteristic, and can be used to classify cell types for cells with unknown identity. Previously, an algorithm was developed...

cuOrbit

Garrett Wright
CUDA C Orbit Model Numerical guiding center code for toroidally confined plasma.

CryptoConfig (ITS Data Management)

David Martin
Python class for handling encrypted elements in a config file. Extension of ConfigParser. This class overides the 'get' method of ConfigParser replacing it with Fernet symmetric encryption so that you can safely store encrypted passwords in an ini file.

PSD GMM Trainer

Brenton Blair & Andrew Glenn
Code takes a data file of input features of a set of digitized pulses and converts the file to three vectors describing a two-component Gaussian mixture model of the input pulses. These three vectors can then be applied mathematically to a set of input feature data of digitized pulses to generate soft-scores describing the likelihood of each pulse's membership in each of the two Gaussian modeled components. The operation of the code also displays graphics...

cubacpp

Marc Paterno, Chris Green, Jackson O'Donnell & James Amundson
cubacpp provides a C++ binding for the excellent CUBA library, and to a lesser extent, to the GSL integration library GSL. cubacpp provides no new integration facilities. It merely provides a more convenient syntax for use of the CUBA (and GSL) integration routines, made possible by the features of the C++ programming language.

MHKiT (Marine and Hydrokinetic Toolkit) - Python

Chitra Sivaraman, Fredrick Driscoll, Budi Gunawan, Carina Lansing, Matt macduff, Tonya Martin, Katherine Klise, Kelley Ruehl, Sterling Olson, Timothy Shippert, Zachary Morrel & Sarah Bredin
The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality,...

MHKiT (Marine and Hydrokinetic Toolkit) - MATLAB

Carina Lansing, Chitra Sivaraman, Matt Macduff, Kelley Ruehl, Katherine Klise, Frederick Driscoll, Rebecca Pauly, Timothy Shippert, Sterling Olson, Budi Gunawan, Zachary Morrell & Sarah Bredin
The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality,...

Solar System Initial Abundnace Reader

Reto Trappitsch
This code is a simply python module that allows the user to read in the solar system value from a provided database. It simply reads in the database, and calculates ratios with various values. Currently, the solar system values from Lodders et al. (2009) are solely included. The tool is designed to assist a astrophysics / cosmochemist user in their daily life of calculating those ratios for programs and was written by the author to...

Varity

Ignacio Peralta
Brief Description for Public Release: Varity is a framework to identify variations in floating-point programs through randomized differential testing. Varity generates random tests that include floating-point operations and compile these tests with different compilers in a system. It also generates random floating-point inputs for the tests. When tests are executed, the results are compared to identify variations in the results. Varity helps users of a system to identify the compilers that produce the most similar...

Modelica Buildings Library Extension for AC and DC Building Comparison (Modelica DC Buildings) v1

Daniel Gerber
This software simulates and compares the losses in AC and DC buildings. It uses formatted load profile data from EnergyPlus, PV generation data from PVWatts, realistic converter efficiency curves based on product data, a battery controller based on excess PV, and a realistic wire model. The software includes Modelica code, which is an extension of the Buildings Library Electrical models. It also includes Python code, which manages the Modelica parametric simulations and plots results.

DiHydrogen

Naoya Maruyama, Brian Essen, Nikoli Dryden, Thomas Benson, Timothy Moon & Yosuke Oyama
DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. DiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. DiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.

Registration Year

  • 2020
    23

Resource Types

  • Software
    22
  • Dataset
    1