The Monte Carlo (MC) library facilitates the development and porting of MC simulations. Users need only provide the code which generates a single path in the MC simulation, and choose among several sampling, statistics consolidation and termination policies. The MC library supports antithetic variables, quasi Monte Carlo simulation, American options, saving of paths, etc. In most MC applications, linear scaling can be achieved.
The Finite Difference (FD) library facilitates the development and porting of finite difference codes for solving initial value problems of linear homogeneous partial differential equations (PDEs). Users only need to specify the PDE terms, free from the hassles of manipulating matrix elements, like declarative rather than imperative programming. The FD library supports Implicit, Explicit, Crank-Nicholson and 4 variants of Alternating Direction Implicit (ADI) schemes. Standard boundary conditions and standard discretisation schemes are provided besides supporting customised ones. The implementation supports parallel computing.