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---
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template: templates/talk_slides_v1.erb
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title: How to Review a Paper
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---
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<section>
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<h2>How to <s>Write</s> Review a Paper</h2>
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</section>
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<section>
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<h3>Why do you care?</h3>
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<ul>
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<li>Your advisor will one day ask you to review a paper.</li>
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<li class="fragment">You will graduate and one day be asked to review a paper.</li>
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<li class="fragment">Your papers will be reviewed like this... get into your reviewer's head!</li>
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</ul>
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</section>
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<section>
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<h3>My Process</h3>
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<dl>
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<dt>Make the paper scribblable</dt>
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<dd>I load the paper into my tablet or print it out. It's important that (a) I'm comfortable, (b) distraction-free, and (c) can make unrestricted markings.</dd>
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<dt>Read-Through</dt>
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<dd>I generally read the paper in a single pass. But I write down <b>everything</b>.</dd>
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<dt>Review notes</dt>
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<dd>Back at a text editor/CMT/etc... I go through the notes and ensure that each note I made is (a) addressed in the paper, and/or (b) appears in my review.</dd>
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</dl>
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</section>
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<section>
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<h3>Criterion</h3>
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<ul>
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<li>Motivation</li>
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<li>Completeness</li>
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<li>Validity</li>
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<li>Readability</li>
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</ul>
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<p class="fragment">A good paper doesn't need to win in all categories.</p>
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</section>
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<section>
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<h3>Motivation</h3>
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<p>Does the paper address a relevant problem or provide useful insights?</p>
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<ul>
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<li>The paper identifies a new problem.</li>
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<li>The paper provides new insights on an old problem.</li>
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<li>The paper identifies new applications of old techniques.</li>
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</ul>
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<p class="fragment">Why would someone want to read this paper?</p>
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</section>
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<section>
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<h3>Completeness</h3>
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<p>Does the paper solve the problem it set out to solve?</p>
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<ul>
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<li>Validate the list of claims (if present).</li>
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<li>Does the paper have a broad/narrow enough scope?</li>
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<li>Is the initial motivation addressed? <ul>
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<li>... or has a sufficient milestone been met?</li>
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</ul></li>
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</ul>
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<p class="fragment">Is the paper clickbait?</p>
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</section>
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<section>
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<h3>Validity</h3>
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<p>Are statements in the paper correct?</p>
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<ul style="font-size: 50%">
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<li>System design/Algorithms <ul>
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<li>Unexpected runtime costs.</li>
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<li>Unhandled corner cases.</li>
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</ul></li>
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<li>Experiments <ul>
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<li>Experimental design doesn't test what the authors claim.</li>
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<li>Results don't agree with author's claims.</li>
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</ul></li>
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<li>Proofs <ul>
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<li>Sanity check</li>
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</ul></li>
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</ul>
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<p class="fragment">How would you solve the problem the authors pose yourself?</p>
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</section>
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<section>
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<h3>Readability</h3>
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<p>Is the paper written clearly</p>
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<ul>
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<li>There is a clearly stated problem / objective.</li>
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<li>All background topics not covered in [grad level class] are outlined.</li>
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<li>System design and formalisms are clear, precise, and complete.</li>
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<li>The paper is free of English bugs, grammar bugs, typos, etc...</li>
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</ul>
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<p class="fragment">Do you understand the paper?</p>
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</section>
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<section>
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<h3>Reading the Paper: Milestones</h3>
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<dl>
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<dt>Introduction</dt>
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<dd>Do I understand the problem the paper is solving?</dd>
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<dd>How would I go about solving the problem the paper outlines?</dd>
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<dd>How would I go about measuring a solution to this problem?</dd>
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<dt>Background</dt>
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<dd>Do I have a reasonable understanding of the techniques the paper plans to use?</dd>
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</dl>
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</section>
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<section>
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<h3>Reading the Paper: Milestones</h3>
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<dl>
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<dt>Algorithm/Data Structures</dt>
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<dd>Do I understand the approach the authors are taking?</dd>
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<dd>If the approach doesn't line up with my own, why?</dd>
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<dt>Experiments</dt>
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<dd>Are all of my expected experiments from earlier addressed?</dd>
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<dd>Do the experiments measure what the authors want to measure?</dd>
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<dd>Are the datasets reasonable/representative of the motivating workloads?</dd>
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<dd>Do the graphs support the paper's claims?</dd>
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</dl>
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</section>
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<section>
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<h3>Feedback</h3>
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<p>Be Specific</p>
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<ul>
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<li>Communicate to the authors at least one way to address your concern.</li>
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<li>Establish a clear metric that can test whether the concern is addressed.</li>
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<li>Include citations where possible.</li>
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<li>Differentiate suggestions from criticism.</li>
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<li>Refer to specific lines of text.</li>
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</ul>
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</section>
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<section>
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<h3>Receiving Feedback</h3>
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<p>Why did the reviewer write it?</p>
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<ul>
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<li>Did the reviewer misunderstand what you wrote?
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<div class="fragment">What can you do to make it clearer?</div></li>
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<li>Did the reviewer ignore an important point?
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<div class="fragment">What can you do to make it more visible?</div></li>
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<li>Did the reviewer not have the right background?
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<div class="fragment">What can you do to make it more accessible?</div></li>
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<li>Did the reviewer disagree with the motivation?
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<div class="fragment">"Pitch" the motivation to your fellow students/faculty.</div></li>
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</ul>
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</section>
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<section>
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<p>The reviewer is a sample of the people who will be reviewing your paper. They may be wrong, but you still need to communicate to others like them to get an accept!</p>
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</section>
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@ -0,0 +1,491 @@
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---
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template: templates/talk_slides_v1.erb
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title: "CSE 501: Microkernel Notebooks"
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---
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<section>
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<h2>Microkernel Notebooks</h2>
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<h4 style="margin-top: 20px;">Oliver Kennedy</h4>
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<p style="font-size: 70%; width: 730px; margin-right: auto; margin-left: auto; margin-top: 100px;" >
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<a href="https://vizierdb.info">
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<img src="graphics/logos/vizier-blue.svg" height="70px" style="float: left; margin-right: 20px; vertical-align: middle;" />
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</a>
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Boris Glavic, Juliana Freire, Michael Brachmann, William Spoth, Poonam Kumari, Ying Yang, Su Feng, Heiko Mueller, Aaron Huber, Nachiket Deo, and many more...</p>
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</section>
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<section>
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<section>
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<h2>But first...</h2>
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</section>
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<section>
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<h3>Databases?</h3>
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<img src="graphics/2022-04-02/er-diagrams.png" height="400px">
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</section>
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<section>
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<img src="graphics/clipart/Female-or-Male-Unisex-Geek-or-Nerd-Light-Skin.svg" height="400px">
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<attribution><a href="https://openclipart.org/">openclipart.org</a></attribution>
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</section>
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<section>
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<h2>Data Structures?</h2>
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<img src="graphics/2022-04-02/250-textbook.png" height="300px">
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</section>
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<section>
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<img src="graphics/2022-04-02/Macintosh_classic_250.jpg" height="400px">
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<attribution>Adapted from <a href="http://creativecommons.org/licenses/by-sa/3.0/" title="Creative Commons Attribution-Share Alike 3.0">CC BY-SA 3.0</a>, <a href="https://commons.wikimedia.org/w/index.php?curid=10101">Wikimedia Commons</a></attribution>
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</section>
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<section>
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<img src="graphics/2022-04-02/nuclear_dino_db.png">
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<attribution>Adapted from <a href="https://www.destroyallsoftware.com/talks/wat">Wat; Gary Bernhardt @ CodeMash 2012</a>
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</section>
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<section>
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<h3>CSE 562; Database Systems</h3>
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<ul>
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<li>A bit of operating systems</li>
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<li>A bit of hardware</li>
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<li>A bit of compilers</li>
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<li>A bit of distributed systems</li>
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</ul>
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<p class="fragment" style="font-weight: bold; margin-top: 50px">Applied Computer Science</p>
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</section>
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<section>
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<img src="graphics/2022-04-02/db-convergence.svg">
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</section>
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</section>
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<section>
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<section>
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<h3>For example...</h3>
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</section>
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<section>
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<pre><code class="sql">
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CREATE VIEW salesSinceLastMonth AS
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SELECT l.*
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FROM lineitem l, orders o
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WHERE l.orderkey = o.orderkey
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AND o.orderdate > DATE(NOW() - '1 Month')
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</code></pre>
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<pre><code class="sql">
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SELECT partkey FROM salesSinceLastMonth
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ORDER BY shipdate DESC LIMIT 10;
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</code></pre>
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<pre><code class="sql">
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SELECT suppkey, COUNT(*)
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FROM salesSinceLastMonth
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GROUP BY suppkey;
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</code></pre>
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<pre><code class="sql">
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SELECT DISTINCT partkey
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FROM salesSinceLastMonth
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</code></pre>
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</section>
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<section>
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<pre><code class="python">
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def really_expensive_computation():
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return [
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expensive_computation(i)
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for i in range(1, 1000000):
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if expensive_test(i)
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]
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</code></pre>
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<pre><code class="python">
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print(sorted(really_expensive_computation())[:10])
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</code></pre>
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<pre><code class="python">
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print(len(really_expensive_computation()))
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</code></pre>
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<pre><code class="python">
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print(set(really_expensive_computation()))
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</code></pre>
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</section>
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<section>
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<pre><code class="python">
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def really_expensive_computation():
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return [
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expensive_computation(i)
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for i in range(1, 1000000):
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if expensive_test(i)
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]
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view = really_expensive_computation()
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</code></pre>
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<pre><code class="python">
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print(sorted(view)[:10])
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</code></pre>
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<pre><code class="python">
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print(len(view))
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</code></pre>
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<pre><code class="python">
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print(set(view))
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</code></pre>
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</section>
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<section>
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<p><b>Opportunity:</b> Views are queried frequently</p>
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<p><b>Idea: </b> Pre-compute and save the view’s contents!</p>
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</section>
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<section>
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<p>Btw... this idea is the essence of CSE 250.</p>
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</section>
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<section>
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<svg data-src="graphics/2022-04-02/DBToQ.svg" />
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<attribution>openclipart.org</attribution>
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</section>
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<section>
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<p>When the base data changes, <br/>the view needs to be updated too!</p>
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</section>
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<section>
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<pre><code class="python">
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def init():
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view = query(database)
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</code></pre>
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<p style="margin-top: 100px;">Our view starts off initialized</p>
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</section>
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<section>
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<p style="margin-top: 100px;"><b>Idea:</b> Recompute the view from scratch when data changes.</p>
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</section>
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<section>
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<pre><code class="python">
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def update(changes):
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database = database + changes
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view = query(database) # includes changes
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</code></pre>
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</section>
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<section>
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<img src="graphics/clipart/Snail.jpg" height="400px">
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<attribution><a href="http://creativecommons.org/licenses/by-sa/3.0/" title="Creative Commons Attribution-Share Alike 3.0">CC BY-SA 3.0</a>, <a href="https://commons.wikimedia.org/w/index.php?curid=95926">Wikimedia Commons</a></attribution>
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</section>
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<section>
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<pre><code class="python">
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def update(changes):
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view = delta(query, database, changes)
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database = database + changes
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</code></pre>
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<table style="margin-top: 50px;">
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<tr class="fragment">
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<td style="font-size: 150%;"><tt>delta</tt></td>
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<td>(ideally) Small & fast query</td>
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</tr>
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<tr class="fragment">
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<td style="font-size: 150%;"><tt>+</tt></td>
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<td>(ideally) Fast "merge" operation</td>
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</tr>
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</table>
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</section>
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<section>
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<h3>Intuition</h3>
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<div>
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$$\mathcal{D} = \{\ 1,\ 2,\ 3,\ 4\ \} \hspace{1in} \Delta\mathcal{D} = \{\ 5\ \}$$
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$$Q(\mathcal D) = \texttt{SUM}(\mathcal D)$$
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</div>
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<div style="margin-top: 50px;">
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<div class="fragment">$$ 1 + 2 + 3 + 4 + 5 $$</div>
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<div class="fragment">$Q(\mathcal D+\Delta\mathcal D)$ <span class="fragment">$\sim O(|\mathcal D| + |\Delta\mathcal D|)$</span></div>
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</div>
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<div style="margin-top: 50px;">
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<div class="fragment">$10$<span class="fragment">$+ 5$</span></div>
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<div class="fragment">$\texttt{VIEW} + SUM(\Delta\mathcal D)$ <span class="fragment">$\sim O(|\Delta\mathcal D|)$</span></div>
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</div>
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</section>
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<section>
|
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<img src="graphics/2022-04-02/morpheus.jpeg">
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|
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<attribution>©1999 Warner Bros. Pictures</attribution>
|
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</section>
|
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|
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</section>
|
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|
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|
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|
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<section>
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<h6 style="font-size: 60%" class="fragment" data-fragment-index="2">Get off my database's lawn, punk kids</h6>
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<h4 class="fragment" data-fragment-index="1"><span class="fragment strike" data-fragment-index="2">Why Jupyter Sucks</span></h4>
|
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<h2 class="fragment strike" data-fragment-index="1">Microkernel Notebooks</h2>
|
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<h4 style="margin-top: 20px;">Oliver Kennedy</h4>
|
||||
<p style="font-size: 70%; width: 730px; margin-right: auto; margin-left: auto; margin-top: 100px;" >
|
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<a href="https://vizierdb.info">
|
||||
<img src="graphics/logos/vizier-blue.svg" height="70px" style="float: left; margin-right: 20px; vertical-align: middle;" />
|
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</a>
|
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Boris Glavic, Juliana Freire, Michael Brachmann, William Spoth, Poonam Kumari, Ying Yang, Su Feng, Heiko Mueller, Aaron Huber, Nachiket Deo, and many more...</p>
|
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</section>
|
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|
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<section>
|
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|
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<section>
|
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<img src="graphics/logos/jupyter.svg" height="500px">
|
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<img src="graphics/2022-04-02/jupyter.png" height="500px">
|
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</section>
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<section>
|
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<pre><code class="python">
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import pandas as pd
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</code></pre>
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<pre class="fragment"><code class="python">
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df = pd.read_csv("AMS-USDA-Directories-FarmersMarkets.csv")
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df
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</code></pre>
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<img class="fragment" src="graphics/2022-04-02/jupyter-table.png" width="800px">
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<pre class="fragment"><code class="python">
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df.groupby("County").count()
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</code></pre>
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<p class="fragment">...</p>
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</section>
|
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|
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<section>
|
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<img src="graphics/2022-04-02/oz.jpeg" height="500px">
|
||||
<attribution>©1939 Metro-Goldwyn-Mayer</attribution>
|
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</section>
|
||||
|
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<section>
|
||||
<img src="graphics/2022-04-02/oz_curtain.jpeg" height="500px">
|
||||
<attribution>©1939 Metro-Goldwyn-Mayer</attribution>
|
||||
</section>
|
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|
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<section>
|
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<console>
|
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Python 3.9.7 (default, Sep 10 2021, 14:59:43)
|
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[GCC 11.2.0] on linux
|
||||
Type "help", "copyright", "credits" or "license" for more information.
|
||||
>>> <span class="fragment">import pandas as pd
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>>> </span><span class="fragment">df = pd.read_csv("AMS-USDA-Directories-FarmersMarkets.csv")
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>>> df<span>
|
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<div class="fragment"> FMID MarketName ... WildHarvested updateTime
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0 1000519 Alexandria Bay Farmers Market ... N 2/1/2021 11:02:22 AM
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1 1021329 Aurora Farmers Market ... Y 1/30/2021 6:24:08 PM
|
||||
2 1002064 Belmont Farmers Market ... N 1/27/2021 9:03:15 PM
|
||||
3 1021262 Broome County Regional Farmers Market ... Y 1/5/2021 10:02:05 AM
|
||||
4 1021202 Canal Village Farmers' Market ... N 9/9/2020 7:55:23 PM
|
||||
.. ... ... ... ... ...
|
||||
82 1020021 Waterloo Rotary Farm Market ... N 8/3/2020 2:28:33 PM
|
||||
83 1000384 Webster's Joe Obbie Farmers' Market, Inc. ... N 1/5/2021 10:18:30 AM
|
||||
84 1002177 West Point-Town of Highlands Farmers Market ... N 8/2/2018 12:58:13 AM
|
||||
85 1019038 Woodstock Farm Festival ... N 4/4/2018 11:27:02 AM
|
||||
86 1007259 Yates County Cooperative Farm and Craft Market... ... N 2/3/2019 12:29:07 PM
|
||||
|
||||
[87 rows x 59 columns]
|
||||
>>> </div>
|
||||
</console>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>Cells are code snippets that get pasted into a long running <b>kernel</b></p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/2022-04-02/joelgrus.png" height="500px">
|
||||
<attribution><a href="https://www.youtube.com/watch?v=7jiPeIFXb6U">I don't like notebooks.- Joel Grus (Allen Institute for Artificial Intelligence)</a></attribution>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/2022-04-02/joelgrus_hiddenstate.png" height="500px">
|
||||
<attribution><a href="https://www.youtube.com/watch?v=7jiPeIFXb6U">I don't like notebooks.- Joel Grus (Allen Institute for Artificial Intelligence)</a></attribution>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/2022-04-02/joelgrus_y_is_5.png" height="300px">
|
||||
<attribution><a href="https://www.youtube.com/watch?v=7jiPeIFXb6U">I don't like notebooks.- Joel Grus (Allen Institute for Artificial Intelligence)</a></attribution>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>Evaluation Order ≠ Notebook Order</p>
|
||||
|
||||
<p style="margin-top: 100px; font-weight: bold;" class="fragment">... but why?</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h3>In a monokernel...</h3>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<pre><code class="python">
|
||||
import pandas as pd
|
||||
</code></pre>
|
||||
<pre class="fragment"><code class="python">
|
||||
df = pd.read_csv("really_big_dataset.csv")
|
||||
</code></pre>
|
||||
<pre class="fragment"><code class="python">
|
||||
test = df.iloc[:800]
|
||||
train = df.iloc[800:]
|
||||
</code></pre>
|
||||
<pre class="fragment"><code class="python">
|
||||
model = train_linear_regression(train, "target")
|
||||
</code></pre>
|
||||
<pre class="fragment"><code class="python">
|
||||
evaluate_linear_regresion(model, test, "target")
|
||||
</code></pre>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<pre><code class="python">
|
||||
import pandas as pd
|
||||
</code></pre>
|
||||
<pre><code class="python">
|
||||
df = pd.read_csv("really_big_dataset.csv")
|
||||
</code></pre>
|
||||
<pre style="box-shadow: 0px 0px 12px red; "><code class="python">
|
||||
test = df.iloc[:500]
|
||||
train = df.iloc[500:]
|
||||
</code></pre>
|
||||
<pre class="fragment red-shadow-current" data-fragment-index="1"><code class="python">
|
||||
model = train_linear_regression(train, "target")
|
||||
</code></pre>
|
||||
<pre class="fragment red-shadow-current" data-fragment-index="1"><code class="python">
|
||||
evaluate_linear_regresion(model, test, "target")
|
||||
</code></pre>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h3>Q1: Which cells need to be re-evaluated?</h3>
|
||||
|
||||
<p style="margin-top: 100px; font-weight: bold;" class="fragment">Idea 1: All of them!</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<pre><code class="python">
|
||||
import pandas as pd
|
||||
|
||||
df = pd.read_csv("really_big_dataset.csv")
|
||||
test = df.iloc[:500]
|
||||
train = df.iloc[500:]
|
||||
|
||||
model = train_linear_regression(train, "target")
|
||||
|
||||
evaluate_linear_regresion(model, test, "target")
|
||||
</code></pre>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/clipart/Snail.jpg" height="400px">
|
||||
<attribution><a href="http://creativecommons.org/licenses/by-sa/3.0/" title="Creative Commons Attribution-Share Alike 3.0">CC BY-SA 3.0</a>, <a href="https://commons.wikimedia.org/w/index.php?curid=95926">Wikimedia Commons</a></attribution>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>... but <tt>df</tt> is still around, and you can "re-use" it.</p>
|
||||
<p>Idea 2: Skip cells that haven't changed.</p>
|
||||
|
||||
<p style="margin-top: 100px; font-weight: bold;" class="fragment">... but <u class="fragment highlight-red">you</u> need to keep track of this.</p>
|
||||
</section>
|
||||
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
||||
<section>
|
||||
<p>Idea 3: Pull out your CSE 443 Textbooks</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/data-flow-simple.svg" height="500px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>Data Flow Graph</h2>
|
||||
|
||||
<p>Cell 3 changed, so re-evaluate only cells 4 and 5</p>
|
||||
|
||||
<p style="margin-top: 100px; font-weight: bold;" class="fragment">... but</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>...</h2>
|
||||
<pre><code class="python">
|
||||
model = train_linear_regression(train, "target")
|
||||
</code></pre>
|
||||
<pre><code class="python">
|
||||
evaluate_linear_regresion(model, test, "target")
|
||||
</code></pre>
|
||||
<pre class="fragment"><code class="python">
|
||||
df = pd.read_csv("another_really_big_dataset.csv")
|
||||
test = df.iloc[:500]
|
||||
train = df.iloc[500:]
|
||||
</code></pre>
|
||||
|
||||
<p style="margin-top: 100px; font-weight: bold;" class="fragment"><tt>df</tt> has changed!</p>
|
||||
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>We want to "snapshot" <tt>df</tt> in between cells.</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/monokernel.svg" height="350px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/microkernel.svg" height="350px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>The kernel runs, snapshots its variables, and quits.</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/microkernel-invalidate.svg" height="500px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>Microkernel Notebooks</h2>
|
||||
|
||||
<ul>
|
||||
<li>Lots of small "micro-kernels"</li>
|
||||
<li>Explicit inter-cell messaging</li>
|
||||
<li>Messsages are snapshotted for re-use</li>
|
||||
</ul>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/microkernel-multiarch.svg" height="500px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/microkernel-parallelism.svg" height="500px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2022-04-02/microkernel-parallelism-2.svg" height="500px" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>Demo</h2>
|
||||
<a href="https://vizierdb.info">
|
||||
<img src="graphics/logos/vizier-blue.svg" height="200px" />
|
||||
</a>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<a href="https://vizierdb.info">
|
||||
<img src="graphics/logos/vizier-blue.svg" height="200px" />
|
||||
</a>
|
||||
<p><a href="https://vizierdb.info">https://vizierdb.info</a></p>
|
||||
<p><a href="https://github.com/VizierDB/vizier-scala">https://github.com/VizierDB/vizier-scala</a></p>
|
||||
|
||||
|
||||
</section>
|
||||
|
||||
</section>
|
||||
|
|
@ -31,6 +31,14 @@ schedule:
|
|||
talks:
|
||||
- speaker: Oliver Kennedy
|
||||
topic: "How to <s>Write</s> Review a Paper"
|
||||
materials:
|
||||
talk: /talks/2022-09-20-501-HowToReview.html
|
||||
- speaker: Oliver Kennedy
|
||||
topic: "Microkernel Notebooks"
|
||||
materials:
|
||||
talk: /talks/2022-09-20-501-Vizier.html
|
||||
- speaker: Erdem Sariyuce
|
||||
topic: "TBD"
|
||||
- date: 09/27/22
|
||||
talks:
|
||||
- speaker: Zhuoyue Zhao
|
||||
|
|
|
|||
Loading…
Reference in New Issue