Seminar: High Performance Analytics
The Power of Sybase RAP and REvolution R

 

Presented:	Wednesday, March 18, 2009
Location:	Sybase Global Financial Solutions Center Grace Building 1114 Ave. of Americas, 32nd floor New York, New York 10036 (Midtown Manhattan, near 42nd and 6th)
Cost:	Complementary

Meeting the challenges associated with high performance computing is both difficult and expensive. We can no longer rely on computer vendors to regularly produce new computers with ever increasing clock speed that run our legacy software faster.

 

Scientists and engineers have been successfully utilizing a new strategy of parallel computing on commodity multiprocessors. These systems utilize inexpensive commodity hardware, but the development of suitable—scale out—parallel application software can be difficult for most programmers. As the cost per computer cycle decreases, the cost of the necessary software is on the rise.

 

REvolution Computing's high performance distribution of the R language is a popular open-source data analysis, statistics, and visualization system with a large and rapidly-growing following in the quantitative finance and risk analysis communities. Across the industry, the R language is at the cutting edge of financial analysis research. Models built in C, C++, Fortran, Java, and even F# are often slow to deploy, costly to produce, and more error-prone than algorithms developed in high-level environments like R.

 

During the seminar, Yale University's Dr. Jay Emerson will provide an introduction to the power of the R language by reference to examples of use and characteristics that make the open source R language the lingua franca of statistical computing, both in academia and increasingly in finance. Dr. Emerson, an assistant professor of Statistics at Yale University and a developer of the "bigmemory" package in R, is an advisor to REvolution Computing.

 

Dr. Bryan Lewis from REvolution Computing will present an overview of risk analysis methods with the R language backed by the Sybase data management platform. Concise examples of value at risk measures, Monte Carlo simulation, and backtesting for market and credit risk illustrate the power and ease of use of the REvolution R system for financial risk analysis. The discussion will focus on interoperability between back-end Sybase data sources and analysis in the R language, and highlight high performance multithreaded/multiprocessor computing enhancements available in REvolution R.

 

Coupled with Sybase RAP — The Trading Edition, REvolution Computing's R language with Sybase data management technology enables financial analysts and others to derive meaning from large sets of mission-critical data in record time and to create predictive models that help answer your most difficult questions. Sybase RAP can enhance sophisticated quantitative analytics on days, months, or decades of market analytic data with a high-performance in-memory database and historic data store.

 

Please join Sybase and REvolution Computing for a complete solution centered around high-performance processing of large data sets integrated with a robust data storage architecture.