Second-order cone programming (SOCP) is convex optimization which extends linear programming (LP) with second-order (Lorentz or the ice cream) cones.

Designed from the outset for modern hardware, the nZetta Toolkit achieves a
10x performance improvement over reference 2D-PDE calculations on real finance problems.

With Monte Carlo, it is crucial to leverage the full potential of hardware parallelism to achieve optimal performance and accuracy.

Trading Desks can hedge auspiciously and gain a competitive edge in the market as our mathematical algorithm technology, dco/c++, gives them rich, cheap and accurate intra-day risk. This fast and accurate risk data at lower cost means more profits for traders and for the business.

An approximate correlation matrix is one that is not positive semidefinite.
In this document we consider an application from finance.

nAG has developed a CVA demonstration code to show how the nAG Library and the Algorithmic Differentiation (AD) tool dco/c++ can be combined with Origami to solve large scale CVA computations.

An important problem in finance is to compute the implied volatility. Typically volatilities are computed for large vectors of input data.

Calculating XVA in a timely manner poses a big performance challenge
for financial institutions.

GS2 [1] is an open source gyrokinetic simulation code used to study turbulence in plasma, one application is for fusion experiments. It is a gyrokinetic flux tube initial value and eigenvalue solv-er and is written in Fortran and parallelised with MPI.

This poster describes work performed on OpenFOAM focussing on
performance as well as OpenFOAM in the Cloud.

Adjoints are sophisticated numerical techniques for computing a large
number of gradients quickly. To compute an adjoint, your computer
program must be run backwards.

The C++ language is so complex that no AD compilers can handle it.
To get an adjoint, we must write it by hand or use an operator overloading
AAD tool.