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Video: Shaping the Future of Finance with HPC

In this video, Mao Ye from the University of Illinois describes how his high performance computing computing is shaping the future of Finance. “Ye’s research lies at the intersection of big data, high-performance computing and the economics, and finance realm. Using computing resources, Ye tackles large amounts of data currently being collected by companies and finance institutions. “The high-performance computing is more like a tool,” he said, “because we are basically doing big data research.”

GPUs Address Growing Data Needs for Finance & Insurance Sectors

A new whitepaper from Penguin Computing contends “a new era of supercomputing” has arrived — driven primarily by the emergence of graphics processing units or GPUs. The tools once specific to gaming are now being used by investment and financial services to gain greater insights and generate actionable data. Learn how GPUs are spurring innovation and changing how today’s finance companies address their data processing needs. 

Video: Designing Parallel Financial Analytics Libraries Using a Pattern Oriented Approach

“How can quants or financial engineers write financial analytics libraries that can be systematically efficiently deployed on an Intel Xeon Phi co-processor or an Intel Xeon multi-core processor without specialist knowledge of parallel programming? A tried and tested approach to obtaining efficient deployment on many-core architectures is to exploit the highest level of granularity of parallelism exhibited by an application. However, this approach may require exploiting domain knowledge to efficiently map the workload to all cores. Using representative examples in financial modeling, this talk will show how the use of Our Pattern Language (OPL) can be used to formalize this knowledge and ensure that the domains of concerns for modeling and mapping the computations to the architecture are delineated. We proceed to describe work in progress on an Intel Xeon Phi implementation of Quantlib, a popular open-source quantitative finance library.”