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<!DOCTYPE html>
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<title>Jack Kosaian</title>
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<img src="files/jack_picture.JPG" width=180 alt="Jack Kosaian" align=center>
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<h2>Jack Kosaian</h2>
[<a href="https://www.linkedin.com/in/jack-kosaian-5baa629a/">LinkedIn</a>]
<p>I began working at NVIDIA on <a href="https://github.com/NVIDIA/cutlass">CUTLASS</a> in October of 2022.</p>
<p>I completed a Ph.D. in the Computer Science Department at Carnegie Mellon University, where I was fortunate to work with <a class="people" href="http://www.cs.cmu.edu/~rvinayak/">Rashmi Vinayak</a> as part of the <a class="people" href="http://www.pdl.cmu.edu">Parallel Data Lab</a>.
<br/>My <a href="http://reports-archive.adm.cs.cmu.edu/anon/2023/abstracts/23-110.html">thesis</a> research investigated the interplay between computer systems, machine learning, and coding-theoretic tools.</p>
<p>Prior to graduate school, I was an undergraduate at the University of Michigan, where I worked with <a class="people" href="http://www.mosharaf.com">Mosharaf Chowdhury</a>.</p>
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<h3>Conference Publications</h3>
<ul>
<li><a href="files/papers/vldb2023ecrec.pdf">Efficient Fault Tolerance for Recommendation Model Training via Erasure Coding</a>
<br/>Tianyu Zhang, Kaige Liu, Jack Kosaian, Juncheng Yang, K. V. Rashmi
<br/><a href="https://vldb.org/2023/", class="venue">International Conference on Very Large Data Base (VLDB), 2023</a>
<br/>[<a href="https://github.com/Thesys-lab/ECRec">code</a>]
</li><br />
<li><a href="https://dl.acm.org/doi/abs/10.1145/3458817.3476184">Arithmetic-Intensity-Guided Fault Tolerance for Neural Network Inference on GPUs</a>
<br/>Jack Kosaian, K. V. Rashmi
<br/><a href="https://sc21.supercomputing.org/", class="venue">International Conference on High Performance Computing, Networking, Storage and Analysis (SC), 2021</a>
<br/>[<a href="https://github.com/Thesys-lab/arithmetic-intensity-guided-abft">code</a>] [<a href="files/slides/sc21_abft.pdf">slides</a>]
</li><br />
<li><a href="files/papers/icml2021folded-cnns.pdf">Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size</a>
<br/>Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, K. V. Rashmi
<br/><a href="https://icml.cc/", class="venue">International Conference on Machine Learning (ICML), 2021
</a>
<br/>[<a href="https://github.com/msr-fiddle/folded-cnns">code</a>]
</li><br />
<li><a href="files/papers/sosp2019parity-models.pdf">Parity Models: Erasure-Coded Resilience for Prediction Serving Systems</a>
<br/>Jack Kosaian, K. V. Rashmi, Shivaram Venkataraman
<br/><a href="https://sosp19.rcs.uwaterloo.ca/", class="venue">ACM Symposium on Operating Systems Principles (SOSP), 2019
</a>
<br>[<a href="https://github.com/thesys-lab/parity-models">code</a>] [<a href="files/slides/sosp19_parity-models.pdf">slides</a>] [<a href="https://sosp19.rcs.uwaterloo.ca/videos/D1-S1-P3.mp4">video</a>]
</li><br />
<li><a href="files/papers/sigcomm2019vantage.pdf">Vantage: Optimizing Video Upload for Time-shifted Viewing of Social Live Streams</a>
<br/>Devdeep Ray, Jack Kosaian, K. V. Rashmi, Srinivasan Seshan
<br/><a href="https://conferences.sigcomm.org/sigcomm/2019/", class="venue">ACM SIGCOMM 2019</a>
</li><br />
<li><a href="https://www.usenix.org/system/files/conference/osdi16/osdi16-rashmi.pdf">EC-Cache: Load-Balanced, Low-Latency Cluster Caching with Online Erasure Coding</a>
<br/>K. V. Rashmi, Mosharaf Chowdhury, Jack Kosaian, Ion Stoica, Kannan Ramchandran
<br/><a href="https://www.usenix.org/conference/osdi16", class="venue">USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2016</a>
</li>
</ul>
<h3>Journal Publications</h3>
<ul>
<li><a href="https://ieeexplore.ieee.org/document/9047948/">Learning-Based Coded Computation</a>
<br/>Jack Kosaian, K. V. Rashmi, Shivaram Venkataraman
<br/><a href="https://www.itsoc.org/jsait", class="venue">IEEE Journal on Selected Areas in Information Theory, 2020</a>
<br>[<a href="https://github.com/thesys-lab/parity-models">code</a>] [<a href="https://deepcomm.github.io/jekyll/pixyll/2020/06/22/learned-coded-computation-part1/">blog</a>]
</li>
</ul>
<h3>Teaching</h3>
<p>I have been fortunate to be a teaching assistant for the following courses:</p>
<ul>
<li>
15-712: Advanced Operating Systems and Distributed Systems (Spring 2021)
</li>
<li>
15-440: Distributed Systems (Spring 2020)
</li>
<li>
EECS 370: Introduction to Computer Organization (Fall 2015, Winter 2016)
</li>
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