Software offers HPC to financial services organizations.

Press Release Summary:



Allowing analysts to work with desktop financial modeling tools, Star-P(TM) v2.5 for Financial Services enables forecasting, risk analysis, and trading by creating complex financial algorithms and working with large data sets. Users can code algorithms and models on their desktops using MATLAB®, Python, and R, and run them on parallel HPCs. It features Python client interface, integration with workload managers such as PBS Pro, performance profiling, and collocated install configuration.



Original Press Release:



New Star-P for Financial Services Brings Supercomputing to Wall Street



WALTHAM, Mass., Aug. 7 - Interactive Supercomputing Inc. (ISC) today announced a new version of its Star-P(TM) software designed to make high performance computing (HPC) easier and more accessible to financial services organizations.

Star-P 2.5 for Financial Services enables analysts to work with their familiar desktop financial modeling tools while gaining quantum leaps in computational performance and programming productivity. They can do better forecasting, risk analysis and trading by creating more complex financial algorithms and working with much larger data sets than current desktop computers allow. And they can do it faster: Star-P's interactive environment allows continual feedback and refinement of algorithms and models, resulting in applications developed in days, not months or years.

Until now, banks, investment firms and insurance companies have had to live with the performance limitations of desktop systems, or engage teams of expert programmers to re-code their algorithms in C and MPI (message passing interface). Star-P 2.5 for Financial Services solves this problem by enabling users to code algorithms and models on their desktops using popular tools - like MATLAB®, Python, and R - but run them instantly and interactively on parallel HPCs. It eliminates the need to re-program the applications to run on parallel systems - which typically takes months to complete for large, complex problems.

Star-P 2.5 for Financial Services is designed to accelerate and improve decision making in applications such as portfolio optimization, financial derivatives valuation, credit fraud detection, hedge fund trading, Monte Carlo simulations and risk analysis. For example, Julius Finance develops next generation credit derivative models using MATLAB and Star-P. "Researchers have struggled to create a consistent mathematical framework for valuation, market risk and opportunities in corporate credit," said Peter Cotton, CEO of Julius Finance. "With Star-P, not only can we create accurate, realistic models and compute the answers we need quickly, we can continually experiment with new algorithms and models with real-time interactivity."

Star-P 2.5 for Financial Services features a number of performance improvements important to financial analysis, including task- and data-parallel processing, extensive plug-in tools and libraries, and scalability to terabyte size datasets across hundreds of processors.

Other enhancements include:

o A new Python client interface that lets users take advantage of Python-
specific numerical libraries and functions. Python support is important
to financial services due to the growing array of open source Python
modules available for analysis. With Star-P, these Python modules can
now be automatically parallelized, yielding significant productivity
gains for users.

o More seamless integration with workload managers, such as PBS Pro,
which is critical for fitting into the large, standardized computing
infrastructures that most financial organizations employ.

o Performance profiling, which enables users to interactively explore
their algorithms and models to fine-tune computational performance.

o Through its collocated install configuration, Star-P can also turn
multi-processor workstations into parallel application development
systems. Collocated install enables analysts to run the client and
server on the same workstation. This allows them to develop models on
multiple processors and refine them interactively; and then easily
scale the models to bigger processor counts and data sets on larger
servers and clusters.

"Computing requirements on Wall Street are growing exponentially as algorithms and models become more complex and tap much larger data sets. Star- P 2.5 for Financial Services accelerates the productivity of financial analysts by bridging the gap between interactive desktops and the computational muscle of HPCs," said Ilya Mirman, ISC's vice president of marketing. "Analysts can focus on delivering the most accurate, comprehensive intelligence without delays or constraints, responding to market conditions more effectively."

Pricing and availability

Star-P 2.5 for Financial Services is available immediately and starts at $15,995.

About Interactive Supercomputing

Interactive Supercomputing (ISC) launched in 2004 to commercialize Star-P, an interactive parallel computing platform. With automatic parallelization and interactive execution of existing desktop technical applications, Star-P merges two previously distinct environments - desktop computers and high performance servers - into one. Based in Waltham, Mass., the privately held company markets Star-P for a range of biomedical, financial, and government laboratory research applications. Additional information is available at www.interactivesupercomputing.com.

Source: Interactive Supercomputing Inc.

CONTACT: Ilya Mirman of Interactive Supercomputing, +1-781-419-5088

Web site: www.interactivesupercomputing.com/

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