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 have peer-reviewed paper 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 have focussed on submissions that demonstrate or result from the collaboration between financial practitioners, and academics, researchers, or vendors.
For 2015, we selected submissions addressing the following emerging topics in high performance computational finance:
·
Use of accelerator platforms for stream processing of tick-by-tick order book data
·
Fast algorithms for algorithmic trading and high frequency risk management
·
Scalable in-memory data processing platforms for large-scale financial computations
·
Software infrastructure for high performance and high productivity
·
Use of parallel design patterns for more efficient mapping of applications to the parallel hardware
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