High Performance C++ Applications in Computational and Quantitative Finance using OpenMP - (code CPP-HPQF)

• State-of-the art financial and software technology integration
•  Migrate existing applications to OpenMP, incrementally
• Integrate OpenMP with your existing designs

Course Contents

Memory Systems

• Shared memory parallel computers (SMPs)
• Shared and cache memory
• Shared memory consistency models
• Distributed memory and shared distributed memory
• Threads

What is a thread?

• Thread attributes
• Thread execution lifecycle
• User threads and kernel threads
• Data Access in Threads

Fork-join (master/slave) model

• Shared and private data
• Thread synchronization
• Synchronisation in Detail

Mutual exclusion (mutex) and condition variables

• Critical sections
• Memory synchronization and fences
• Barriers
• Troubleshooting

Sequential consistency

• Removing data dependencies
• Race conditions
• Deadlock and livelock

A Simple Monte Carlo Application

• Designing the problem using patterns
• Task decomposition and MC paths
• Shared and private data
• Implementing the option pricing using OpenMP

Part 2: Designing Parallel Programs

Decomposition Techniques

• Task and data decomposition
• Grouping and ordering tasks
• Data sharing among tasks
• Evaluation

Examples

• Matrix computations and their applications
• Random number generation
• Monte Carlo simulation
• Finite Difference Method (RNG)

Algorithm Structure

• Task and data parallelism
• Divide and conquer
• Geometric decomposition
• Other decomposition techniques
• Parallel Design Patterns

SPMD pattern

• Master/Worker pattern
• Loop parallelism pattern
• Shared data and shared queues patterns

Loop parallelism in Detail

• Sequential optimisation
• Avoiding race conditions
• Improving performance with loop optimizations
• Loop unrolling
• Using critical sections and locks

Part 3: OpenMP

Overview

• Compiler directives
• Library routines
• Environment variables

My First OpenMP Program

• Writing the serial program
• Determining parallel code
• Adding OpenMP directives
• Debugging and performance measurement

Data Clauses in OpenMP

• Shared and private
• Lastprivate, firstprivate
• Default and nowait clause
• OpenMP Synchronisation Constructs

Barrier

• Ordered
• Critical and Atomic
• Locks, Master construct

Work Sharing in OpenMP

• Loop construct
• Sections and section
• Single construct
• Combined parallel work-sharing constructs

Other Clauses

• Reduction clause
• Copyin clause
• Copyprivate clause
• Ordered clause

Configuration and Run-Time Information

• Setting environment variables' values
• Library functions for thread information
• Scheduling functions
• Lock functions
• Timing functions

Part 4: Financial Applications

Matrix Applications

• Parallel basic linear algebra
• BLAS functionality
• Matrix-vector and matrix-matrix multiplication
• Memory and processing optimization

The Fast Fourier Transform (FFT)

• The discrete Fourier transform; inverse transform
• Parallel program design
• Partitioning and communication
• Applications of FFT

Monte Carlo Framework in C++ and OpenMP

• Design using OpenMP
• Application testing and troubleshooting
• Performance measurement and improvement
• Speedup

The Finite Difference Method

• Explicit methods and domain decomposition
• Load balancing and thread allocation
• One-factor and multi-factor PDEs
• Speedup of the schemes

Prerequisites

A working knowledge of C or C++. It is an advantage if you work with software applications in which performance is important and where advantage can be taken of multi-processor computers. This course has been specially developed for those working in quantitative finance and the focus, approach and applications in the course reflect this fact.

Who should attend?

Quantitative designers, analysts and others who develop advanced applications for derivatives pricing, risk management and related areas. This course is also of interest to software developers and consultants who wish to gain experience in this field.

Duration, price, date, locations