The Cheriton School of Computer Science will hold its annual Cheriton Symposium September 21st in the Davis Centre.
This year's symposium will consist of talks by Prof. David R. Cheriton of Stanford University, and Faculty Fellowship recipients, Gladimir Baranoski and Peter Forsyth from 2:00 pm to 5 pm in DC 1302.
Posters by Cheriton Graduate Student Scholarship recipients will be on display in the Great Hall, Davis Centre from 10:00 am to 4 pm.
10:00am - 4:00pm
DC Great Hall - Poster Session
Lunch in DC 1301
DC 1302 - David Taylor - Welcome and opening remarks
DC 1302 - David R. Cheriton - Abort Rates and Degree of Concurrency with Transactional Memory
Hardware transactional memory has been proposed as a means to allow the highly concurrent programming that is required with multi-core systems to achieve high throughput, without all the complication and overhead of locking. However, a higher degree of concurrency can lead to a higher transaction abort rate, reducing the throughput and thus the benefit of the concurrency. In this talk, I describe our investigation of the abort rate of two different approaches to hardware transactional memory, namely the conventional in-place update as well as the snapshot isolation model provided by the HICAMP architecture. Our results show that the latter approach together with a merge-update extension to conflict resolution leads to lower or comparable abort rates while allowing higher degrees of concurrency and thus higher throughput, at the cost of the relaxed form of consistency provided by snapshot isolation.
DC 1302 - Peter Forsyth - Optimal Order Execution: Do You Know What Your Broker is Doing?
Algorithmic trade execution has become a standard technique for institutional market players in recent years, particularly in the equity market where electronic trading is most prevalent. A trade execution algorithm typically seeks to execute a trade decision optimally upon receiving inputs from a human trader. A common form of optimality criterion seeks to strike a balance between minimizing pricing impact and minimizing timing risk. For example, in the case of selling a large number of shares, a fast liquidation will cause the share price to drop, whereas a slow liquidation will expose the seller to timing risk due to the stochastic nature of the share price.
A desirable strategy can be defined in terms of a Pareto optimal solution. We seek to determine the strategy which, for a given expected revenue from selling a block of shares, minimizes the risk (i.e. the variance of the revenue).
We compare optimal liquidation policies in continuous time in the presence of trading impact using numerical solutions of Hamilton Jacobi Bellman (HJB) partial differential equations (PDE). The industry standard approach (the Almgren and Chriss strategy) is based on an approximate solution to the HJB equation. In terms of the mean variance efficient frontier, the original Almgren/Chriss strategy is significantly sub-optimal compared to the solution obtained by solving the HJB equation numerically.
DC 1302 -Gladimir Baranoski - Benefits and Pitfalls of Interdisciplinary Research on Light and Matter Interactions
Models of light and matter interactions employ computer simulations to describe how different materials absorb and scatter light. These models
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