The purpose of this workshop is to bring together practitioners, researchers, vendors, and scholars from the complementary fields of computational finance and high performance computing, in order to promote an exchange of ideas, discuss future collaborations and develop new research directions. Financial companies increasingly rely on high performance computers to analyze high volumes of financial data, automatically execute trades, and manage risk.
As financial market data continues to grow in volume and complexity, computational capabilities of emerging hardware also increases. Extracting high performance from emerging architectures requires a combination of domain knowledge and specialized technical skills. The workshop will explore how researchers, scholars, vendors and practitioners are collaborating to address high performance computing research challenges.
We seek submissions that cover various aspects of computational finance. In addition to submissions that deal with performance and programmability challenges, theoretical analysis, algorithms, and practical experience in computational finance, we also particularly encourage submissions that demonstrate or result from the collaboration between financial practitioners, and scholars, researchers, or vendors.
For 2014, we are particularly interested in submissions addressing the following emerging topics in high performance computational finance:
· Financial analytics, including Big Data in computational finance
· Software infrastructure for high performance and high productivity
· Use of FPGAs for high frequency trading
Additional topics of interest to this workshop include, but are not restricted to:
· Financial libraries and run-times
· Use of hardware accelerators (FPGA, Cell, GPUs) in computational finance
· Use of heterogeneous hardware in computational finance
· Financial applications of high performance computing: risk algorithms, derivative pricing, algorithmic trading, arbitrage
· High-bandwidth/low-latency streaming of market data
· Cluster computing for computational finance
· Financial data center engineering
· Computational algorithms for finance
· Move from capacity to capability computing in financial applications