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This repository was archived by the owner on Nov 8, 2024. It is now read-only.

Commit 8b951d5

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‎src/app/nav/Nav.css‎

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padding-top: 25px;
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}
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#info {
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display:inline-block;
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float:right;
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position: absolute;
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height: 100px;
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font-size: 1em;
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padding-top: 75px;
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padding-left: 93vw;
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}
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#overlay {
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position: fixed;
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display: none;
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width: 100%;
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height: 100%;
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top: 0;
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left: 0;
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right: 0;
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bottom: 0;
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background-color: rgba(0,0,0,0.5);
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z-index: 2;
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cursor: pointer;
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}
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#information {
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position: absolute;
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padding: 10px;
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top: 50%;
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left: 50%;
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transform: translate(-50%, -50%);
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background-color: white;
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text-align: left;
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height: 75vh;
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font-family: "Roboto Mono", monospace;
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font-weight: 300;
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width: 50vw;
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}
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#logo-text {
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width: 20%;
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display: inline;

‎src/app/nav/Nav.js‎

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import React, {Component} from 'react';
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import './Nav.css'
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import FontAwesome from 'react-fontawesome' ;
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class Nav extends Component {
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showInstructions() {
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document.getElementById("overlay").style.display = "block";
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}
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off() {
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document.getElementById("overlay").style.display = "none";
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}
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render() {
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return (
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<div className="top-bar nav">
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<h3 id="title-text">GPU CLUSTER</h3>
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</div>
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</a>
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<a id="info" onClick={this.showInstructions}>
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<FontAwesome name='info-circle' size="2x" className="help logo" id="github" aria-hidden="true"/>
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</a>
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</div>
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</div>
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<div id="overlay" onClick={this.off}>
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<div id="information">
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<h3> ACM@UIUC GPU Cluster </h3>
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<p>
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An easy way to get access to a GPU. Select a framework to get started. Further instructions will be provided after you launch your container.
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</p>
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<h4> Rules</h4>
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<ul>
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<li> Store all data in your vault workspace (/vault/[username]) as this will be the only persistant storage on the system </li>
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<li> We can only support two concurrent GPU users, look above to see if there is a free GPU otherwise comeback later </li>
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<li> Don't hog time on the cluster </li>
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</ul>
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<h4> System Specs </h4>
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<ul>
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<li> Intel(R) Xeon(R) CPU E5-2643 0 @ 3.30GHz </li>
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<li> 16 GB of RAM </li>
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<li> 120 GB of SSD Storage </li>
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<li> 16 TB of RAID0 HDD Storage </li>
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<li> GTX 980 Graphics Card </li>
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<li> GTX 1070 Graphics Card </li>
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</ul>
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<h4> Common Datasets Available</h4>
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<ul>
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<li>MNIST</li>
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<li>CIFAR-10</li>
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<li>CIFAR-100</li>
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<li>IMAGNET2017-DEC</li>
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<li>IMAGENET2017-CLS</li>
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<li>NYU-DEPTH-V2</li>
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</ul>
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<p> If you intend to use a common dataset not on this list, instead of downloading into your workspace, place it in /vault/data </p>
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</div>
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</div>
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</div>

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