Contact Information

Computer Science Department
Colgate University
McGregory Hall, 3rd Floor
13 Oak Drive
Hamilton, NY 13346
(tel) 315.228.7719
(fax) 315.228.7009

Upcoming events

  • 4



    Please join us for our next department tea, November 4, at 11:20. Our tea will be a friendly and casual discussion, including discussion of 400-level courses offered in Spring '15. Lunch will be provided.

Past events

  • 28



    At our next department tea, Jack Sneeringer '16 and Martin Liu '16 will talk about research they did at Colgate over the past summer. Lunch will be served following their talk.

    Abstract: Large data centers are often looking for ways to improve performance, however it is difficult to estimate how potential upgrades will affect performance. A network simulator should be able to provide an estimate. However, existing network simulators are extremely accurate and unscalable or scalable but wildly inaccurate. Our research was focused on developing an accurate and highly scalable network simulator.

    Data is sent over the Internet in small pieces called packets. The best way to visualize this is to think of a table you might order from IKEA. The table isn’t shipped to you in one piece, but instead is shipped in small pieces and is assembled once all of the pieces have arrived. A file is transmitted across a network in the same way. This is an important notion for network simulation because sending a single file across a network is thousands of simulation events.

    Our simulator aims to improve scalability through the use of “flowlets.” Flowlets are designed to reduce packet level computation while still realistically simulating traffic. A flowlet is a “super packet” that is handled by the network as a single packet but is the size of 10 or 20 packets. Using flowlets reduces the number of simulation events significantly while still representing traffic flow fairly well. A nice feature of flowlets is that they are completely adjustable. The user can decide how large to make a single flowlet depending on his or her personal preference for accuracy or efficiency.

    Our simulator also aims to improve scalability through the use of XCP instead of TCP. The use of XCP was motivated by the difficulty of implementing flowlets in TCP. For instance, TCP requires packet loss to tell the sender to reduce traffic but figuring out how to drop a flowlet is difficult. A nice feature of XCP is that it does not allow for packet loss. In addition, XCP is more scalable from a simulation standpoint than TCP. XCP calculations are done on switches, not at the end user. This means that the number of calculations scales with the number of switches and not the number of end users.

  • 21



    The speaker for our next department tea will be Farah Fouladi '15, who will talk about the internship she did this past summer. Lunch will be available after her talk.

    By mathematically modeling biological systems we can predict the effect of small changes in the system that are difficult to measure experimentally. This analysis requires multiple simulations of the model for every parameter variation. While this type of analysis is feasible for isolated cells, running many simulations of large systems of cells is extremely time consuming. To decrease the execution time of these model simulations, I have developed a parallelized environment, which utilizes the architecture of a graphics processing unit.

    The GPU has many processor cores and the ability for thousands of threads to run concurrently on those cores. For my research, a mathematical model of the human ventricular myocyte (ten Tusscher & Panfilov, Am J Physiol 291: H1088–H1100, 2006) was programmed in CUDA. Taking advantage of the parallel hardware, cell computations along with different simulations of the model are completed on the GPU by many threads running simultaneously. To validate this computational design, cell membrane voltage values were compared with an already existing model implementation in MATLAB. Results showed that the added parallelization has no effect on the computational aspect of the model and that the execution time of the CUDA program decreases by orders of magnitude compared to the previously used MATLAB program.

    Using this new computational environment, I analyzed one cause of reentry in cardiac myocytes. Reentry occurs when an electric propagation loops back on itself, abnormally re-exciting cells. There is a short window of time during which a stimulus can excite cardiac tissue and cause a reentry effect due to refractory tissue blocking action potential propagation in only one direction. My program is able to efficiently identify the stimulus-timing interval when reentry occurs in a loop of 1,000 cells.

    This parallelized simulation environment minimizes computational execution time and provides a framework for further analysis of more complex and physiologically relevant systems of cells

Events history