Andreas Goetz (agoetz)

agoetz

Geek Repo

Location:La Jolla, CA

Home Page:www.awgoetz.de

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sdsc

Andreas Goetz's repositories

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

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GOMC

GOMC - GPU Optimized Monte Carlo is a parallel molecular simulation code designed for high-performance simulation of large systems

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nsf-proposal-latex-samples

LaTeX samples for NSF Research.gov Proposal Submission. For more information about Research.gov Proposal Submission visit https://www.research.gov/research-web/content/aboutpsm Feedback syee@nsf.gov

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microprocessor-trend-data

Data repository for my blog series on microprocessor trend data.

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nsf-proposal-latex

An NSF proposal template in LaTeX

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sdsc-summer-institute-2021

San Diego Supercomputer Center Summer Institute

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conversion_tofix

Exercise for Advanced git tutorial

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QUICK-GenInt

CUDA capable integral generator for QUICK quantum chemistry code

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ciml-summer-institute-2021

Repository for the CIML 2021 Summer Institute training materials.

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notebooks-sharing

Writing and Sharing Computational Analyses in Jupyter Notebooks

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sdsc-summer-institute-2020

SDSC Summer Institute 2020 material

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sdsc-summer-institute-2019

SDSC Summer Institute 2019 material

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dftbplus

DFTB+ general package for performing fast atomistic simulations

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quick-orig

QUICK, a GPU-enabled ab intio quantum chemistry software

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potential_fitting_old

This repository contains all of our potential fitting codes. 1B, 2B, 3B

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clusters_ultimate

DO NOT CLONE. Currently under development. This code will be able to calculate the energy of a set of systems composed by molecules, each molecule composed by monomers.

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sdsc-summer-institute-2018

SDSC Summer Institute 2018 Teaching Material

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neural-network-demo

An example code for neural network models for predicting the water dimer potential energy

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HVP_software

Installation notes, benchmarks and batch scripts for HVP software

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legacy_mbpol

C++ MBpol implementation used in http://pubs.acs.org/doi/abs/10.1021/ct500079y, new users should use the OpenMM plugin: https://github.com/paesanilab/mbpol_openmm_plugin

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mbpol_openmm_plugin

mbpol is a plugin for the OpenMM toolkit for molecular simulations using the MB-pol, a many-body potential for water.

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sdsc-summer-institute-2017

SDSC Summer Institute 2017 teaching material

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si17.github.io

SDSC Summer Institute 2017 website

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DeepLearningImplementations

Implementation of recent Deep Learning papers

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sandbox-cluster-guide

Guide to creating Raspberry Pi clusters

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