pnnl/DeepDataProfiler
Python library for analyzing the internal structure of deep neural networks.
Praggastis, Brenda↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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HIPPO Software
HIPPO software is a Python implementation of the HIPPO technology. The HIPPO technology provides the computational and modeling capabilities for managing electricity market operations and for designing and prototyping future markets. The current software can solve the day-ahead unit commitment problem and perform simultaneous feasibility test. It can be used to handle industry scale electricity market.
Peng, Fan↗
pnnl/diet-parselantro
A data annotation tool that integrates with the python Jupyter notebook environment.
Central, PNNL Developer↗
NWQ-sim
NWQSim is a quantum circuit simulation environment developed at PNNL. It currently includes two major components: a state-vector simulator (SV-Sim) and a density matrix simulator (DM-Sim) and we may add more components, such as a Clifford simulator, in the future effort. NWQSim has two language interface: C/C++ and Python. It supports Q#/QDK frontend through QIR and QIR-runtime. It supports Qiskit and Cirq frontends through OpenQASM. NWQSim runs on several backends: Intel-CPU, Intel-Xeon-Phi, AMD-CPU, AMD-GPU, NVIDIA-GPU, and IBM-CPU. It supports three modes: (1) single processor, such as a single CPU (with and without AVX2 and AVX512 acceleration), a single NVIDIA GPU or a single AMD GPU; (2) single-node-multi-processors, such as multi-CPUs/Xeon-Phis, multi-NVIDA/AMD GPUs; (3) multi-nodes, such as a CPU cluster, a Xeon-Phi cluster (e.g., ANL Theta, NERSC Cori), an NVIDIA cluster (e.g., ORNL Summit, NERSC Perlmutter).
Li, Ang↗
y0-causal-inference/y0
❓y0 (pronounced "why not?") is for causal inference in Python: a software library intended to support the scientific discovery process.
Hoyt, Charles Tapley↗
JGCRI/stitches
Amalgamate existing climate data to create monthly climate variable fields. The STITCHES python library provides a user-friendly interface to top-down climate emulation.
Snyder, Abigail↗
pnnl/interflow
A Python package for organizing and calculating cross-sectoral interdependency flow values. The interflow package collects known resource flow values (e.g., water demand) between sectors provided by the user and calculates new sector flows for a secondary resource type (e.g., energy demand) based on provided resource intensity estimates, source sector fractions, and downstream sector discharge fractions.
Mongird, Kendall↗
pnnl/copper
Performance curve generator for building energy simulation. Copper is a tool in the form of Python package that can be used to generate metric specific performance curves for building energy simulations.
L., Jeremy↗
High-throughput electronic structure package
We introduce HTESP (High-Throughput Electronic Structure Package), an automated tool designed for high-throughput ab initio calculations. HTESP simplifies the entire workflow, including data extraction, input files generation, calculation submission, result collection, and plotting. The package is implemented in Python and Bash languages. In this paper, we provide detailed information about the package, its installation process and some illustrative examples to demonstrate its usage. Additionally, the package includes comprehensive online documentation on input parameters and tutorials to assist users.
Nepal, NirajK↗
ExaDigiT/RAPS
ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. RAPS either simulates workloads or replays historical workloads from system telemetry, and is able to predict dynamic energy consumption, as well as interact with the cooling model to predict cooling system behavior. Such a tool can be used together with reinforcement learning algorithms to provide an end-to-end optimization tool for data centers.
Brewer, Wesley [Oak Ridge National Laboratory (ORN↗
datacenterCoolingModel
ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. The Modelica-based cooling model is primarily built-on the open-source Transient Simulation Framework of Reconfigurable Models (TRANSFORM) library and the open-source autocsm library. The library follows the templating architecture developed in the TRANSFORM and the autocsm libraries. This tool can be easily extended to model other Frontier-like liquid cooled supercomputers.
Kumar, Vineet [Oak Ridge National Laboratory (ORNL↗
TwinMe4AD: WGAN-based Digital Twins for Anomaly Detection
SAND2024-08373O TwinMe4AD is a Python-based software tool designed for anomaly detection using digital twins that closely mimic real, wearable healthcare datasets. The tool is invaluable for scenarios where collecting data is either expensive or impractical, serving as a privacy-preserving solution. Sensitive information is protected by training deep learning models on synthetic data derived from real datasets. One of TwinMe4AD's key features is its anomaly detection capability, which is based on fourth-order moments of parameters. This versatile approach can be applied across a range of datasets, from univariate to multivariate, making it compatible with various types of data. It also generates synthetic twins using Wasserstein Generative Adversarial Networks (WGANs), allowing users to create a small cohort of a population similar to that of a village population. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Poorey, Kunal↗
Automated ToF-SIMS PCA Analysis Tool
Python software package for PCA analysis of ToF-SIMS spectra data
Welch, Cole↗
CEDS Differential Privacy (CEDSDP) v0.1
A Python package that provides differentially private queries optimized for energy systems' data. It may be used to publish queries such as clustering, averaging, metadata inference, etc. that are useful for a variety of grid-related analytics, including cyberattack detection.
Peisert, Sean↗
Neural Network Export Package (nexport) v0.1.0
nexport is a lightweight python 3 package which enables neural network developers to export the weights and biases of trained networks to useful file types. It provides I/O support for applications which require specific data types for instantiating neural networks in various inference environments. It was initially developed to support exporting to the data structure used by 'inference-engine', a Fortran inference package.
Welsman, Jordan↗
lasy v0.1
Lasy is a Python library that facilitates numerical simulations of the interaction of complex laser pulses with plasmas. More specifically, lasy offers many ways to define complex laser pulses (e.g. from commonly-known analytical formulas, from experimental measurements, etc.) and then computes and saves the corresponding laser field in a standardized file. This file can then be read by external plasma simulation codes, that will then simulate the interaction between the complex laser pulse and a plasma. Lasy is useful for instance for numerical simulations of plasma-based particle accelerators, plasma-based laser amplification, etc. Lasy avoids having to duplicate the code that defines complex laser pulses in each plasma simulation codes, and instead provides a trusted, centralized implementation.
Lehe, Remi↗
Maritime Battery Electrification Simulator (MariBES) v1
MariBES is a Python-based software designed for calculating emissions and energy consumption in maritime transportation. This software is capable of performing calculations for multiple vessels, facilitating emission analysis at regional, national, and international scales. It also allows for the examination of energy consumption under various resource such as heavy fuel oil, diesel, and battery-electric, enabling the assessment of different decarbonization strategies in the maritime sector. MariBES utilizes public data on ship activities combined with detailed vessel specifications, significantly enhancing the accuracy of its simulations. This approach marks a considerable advancement over previous models that were constrained by limited spatial and temporal resolution. It features a temporal resolution based on 5-minute intervals and a spatial resolution using precise coordinates.
Moon, HeeSeung↗