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Parallel Methods in Financial Services for Intel Xeon Phi

Basic optimization techniques that include an understanding of math functions and how to simplify can go a long way towards better performance. “When optimizing for a parallel SIMD system such as the Intel Xeon Phi coprocessor, it is also important to make sure that the results match the scalar system. Using vector data may cause parts of the computer program to be re-written, so that the compiler can generate vector code.”

Heterogeneous MPI Application Optimization

“Two components of ITAC, the Intel Trace Collector and the Intel Trace Analyzer can be used to understand the performance and bottlenecks of a Monte Carlo simulation. When each of the strike prices are distributed to both the Intel Xeon cores the Intel Xeon Phi coprocessor, the efficiency was about 79%, as the coprocessors can calculate the results much faster than the main CPU cores.”

Black-Scholes Pricing on Intel Xeon Phi

“An expanding area of work both on the hardware front and the software side is to modify and optimize applications to run on both the host processor and a coprocessor. Many techniques to transform applications to reduce runtime have been discussed and implemented across a wide variety of applications.”

Mizuho Securities Speeds Derivatives 30x with Intel Xeon Phi

Mizuho Securities reports that they are the first financial institution to deploy the Intel Xeon Phi coprocessor in a production environment.

Interview: Xcelerit Partners with Intel to Accelerate Code in Supercomputing

“Our core product is the Xcelerit SDK, a Software Development Kit that makes it easy for domain specialists (i.e. mathematicians in banks or geophysicists in energy exploration firms) to convert their existing code to take advantage of multi-core, GPU and other hardware accelerators.”