Recent Developments in Parallel Computing in Finance

June 5 and 6, 2014

The Stevanovich Center
5727 S. University Avenue
Chicago, IL 60637

Check-in and breakfast begin at 9:00 AM both days.

Parallel computing has become a very important tool in modern quantitative finance.  The ability to analyze massive amounts of data in parallel in almost real time exceeds the capabilities of even the fastest single core processor (CPU).  Many of the computations in quantitative finance lend themselves to parallelization where many computations are made simultaneously and at the end the individual results are aggregated into a single result.  The speed of such a parallel computation scales, sometimes linearly, with the number of processor cores.

A normal off-the-shelf processor usually has 2 – 8 computing units.  However a graphics processor (GPU) i.e. a processor whose main task is to compute the pixels that form a digital image, may have a thousand or more small cores.  A digital image on a large computer screen contains upwards of 2 million pixels that have to be computed about 50 times a second so there is a large computational asset in a GPU.  Since recently, practitioners, mathematicians and engineers have been working on harvesting this GPU resource for numerical computations in other fields, including finance.

Researchers from academia and from industry will report on work on finding parallel algorithms to do financial computations and engineers will report on implementation issues and new and improved hardware solutions.

On the software implementation side there are two main platforms: CUDA and OpenCL.

In addition to CUDA, OpenCL is gaining popularity as an industry standard for doing parallel computing.  Microsoft last year introduced a proprietary technology, Accelerated Massive Parallelism (AMP) as a way to exploit the GPGPU computing technology in C++ programs.

Goal 

Professionals in the financial services industry have already started exploring and experimenting with some of these technologies and in many cases using them on a daily basis in areas such as pricing financial instruments, risk management, simulations, order execution and data analysis.    

The aims of this conference are:

  1. Providing a platform for the industry practitioners and the solution providers to share their experiences in recent developments in parallel computing with students and finance industry professionals
  2. Facilitating discussions on future directions and create opportunities for further research and collaborations among the participants
  3. Give students a hands-on experience with GPU parallel computing through tutorials and workshops

Scheduled Speakers

 

Thursday, June 5

 

Check-in and Breakfast
9:00 AM


John Reppy   The University of Chicago
10:00 AM
High-level programming models for GPUs


John Ashley   NVIDIA
11:00 AM
Latest Research on GPU implementation of explicit and implicit Finite Difference methods in Finance


Lunch
12:00 - 1:30 PM


Thomas Luu   University College London
1:30 PM
Parallel non-uniform random number generation


Trevor Misfeldt   Centerspace LLC
Andy Gray   Black Crater Software Solutions
2:30 PM


Raman Sharma    Microsoft Corporation
4:30 PM
How to obtain superior performance for computational finance workloads using APM (Accelerated Massive Parallelism)


Friday, June 6

 

Check-in and Breakfast
9:00 AM


John Ashley   NVDIA
10:00 AM
Implementing correlated FX baskets on GPUs


Lunch
12:00 - 1:30 PM


Jerry Hanweck   Hanweck Associates
1:30 PM
NVIDIA GPU - Accelerated Stochastic Volatility Modeling for Derivatives Pricing


Peter M. Phillips   Aon Benfield
Aamir Mohammad   Aon Benfield
2:30 PM
Visual DSL for Actuarial Models - An Industrial Experience Report


Michael D'Mello   Intel
3:30 PM

Part 1: Empowering Financial Services Applications for Intel® Xeon® and Intel® Xeon Phi™ architectures using the Intel® Software Tools

Part 2: Workshop on empowering Financial Services Applications for Intel® Xeon® and Intel® Xeon Phi™ architectures using the Intel® Software Tools


 

Organizing Committee

Niels Nygaard  University of Chicago
John Reppy  University of Chicago
Chanaka Liyanaarachchi  University of Chicago
John Ashley  Senior Solutions Architect
                      Financial Services, NVIDIA Corporation

 

The Stevanovich Center is supported by the generous philanthropy of University of Chicago Trustee Steve G. Stevanovich, AB '85, MBA '90.