The Manticore Project is a parallel programming language project at the University of Chicago. All of the source code is freely available via SVN, and the project's page provides detailed explanation. If you're interested in learning more, I strongly recommend starting with This Paper, which describes Parallel ML, Manticore's source language, and its possible applications.

In Winter of 2010-2011, after taking the University of Chicago's Operating Systems course, I had an interest in scheduling algorithms. I asked Professor Reppy about the possibility of working on similar problems in the Manticore project, and got started in a few months on working, under the supervision of Lars Bergstrom, on modifying thread scheduling in Manticore. I worked in Manticore's primcode, an SML dialect used to express some low-level details of the run-time system, modifying Manticore to use a scheduling algorithm developed by Professor Reppy for CML. The scheduler, with these modifications, now classifies threads as computationally intensive or IO bound, and prioritizes processor time given to computational threads.

From 2011 to 2013, I worked with Adam Shaw on implementing a fully fledged form of his dissertation research on data structure flattening. We did not deeply investigate the field of arbitrary data structure flattening, but worked primarily on nested array flattening. We generalized segmented summations into segmented reductions, and hooked segmented reduce into the compiler to show that under Adam Shaw's flattening transform, dense matrix operations -- a typical failing point for array flattening -- did not suffer a significant performance loss. The paper produced from this work, Data-Only Flattening, demonstrates the results of running the flattening transform on data structures without any transformations on the code manipulating those structures. I keep a small GitHub repository, Proto_FT in which I attempted to formalize flattening on arbitrarily nested arrays and tuples, one of the sticking points in the existing Manticore flattening transforms.

The CSIL is the Computer Science department's computer laboratory at the University of Chicago, located in the John Crerar Science Library. In the Spring of 2010, I began working in the (almost) entirely student-run laboratory, manning the lab's help desk. Over time, as most CSIL employees do, I took on more system administration responsibilities, helping run virtual machines on hardware using Parallels and, later, VMWare. In my time there, I took part in major improvements to the CSIL's inventory system, internal web services, and documentation efforts, and aided the lab through two migrations: one in virtualization infrastructure from Parallels to VMWare, and the other in location from it's prior space in the Joseph Regenstein Library.

In 2012, having worked on a variety of systems within the laboratory, my focus shifted more towards Dev Ops, specifically automation and monitoring of our user-facing workstations. The lab is now largely administered through the (unfortunately closed source) toolkit that I developed on top of Fabric. Due to design flaws with Fabric, I have advocated the eventual replacement of this system.

After I graduated from the university in Spring 2013, I retained a fairly close connection with the laboratory. I have given advice on any issues or projects that I had expertise in, and have since helped reform the lab's interview procedures. In the recent past, I have not had much time to help the lab.

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