Program Optimization in the Domain of High-Performance Parallelism

Artificial Intelligence and Applications / 794: Modelling, Identification and Control / 795: Parallel and Distributed Computing

2013

Internal Domain-Specific Languages (DSL) provide an elegant mechanism to reduce the code complexity of complex systems simulations programming. Many complex systems problems manifest themselves as networks. Graph analysis techniques can be employed to count the number of: separate components; circuits; paths; or distances in the network. Several other properties such as: mean and peak degree; component or community size; adjacency eigen-spectra, and so forth can also be calculated. Calculation of these properties gives a signature that can help classify a network as belonging to a particular category with known behaviours. In practice however, importing applications data into graph analysis software and managing these calculations can be complex. Domainspecific language techniques allow a high-level graph calculations language to be developed that invokes software components in a graph manipulations framework. We describe a prototype graph generation and analysis domainspecific language built using fluent interface techniques and the Java programming language. We report on: attainable code complexity reduction, framework computational performance, and software engineering directions for internals DSLs for this sort of applications problem.

Section: Discussionmentioning

confidence: 99%

Fluent Interfaces to a Java-based Internal Domain-Specific Languages for Graph Generation and Analysis

Artificial Intelligence and Applications / 794: Modelling, Identification and Control / 795: Parallel and Distributed Computing

2013

“…Nevertheless it may be worthwhile to experiment with an external DSL that can drive a parser generator to generate code in other high-level language aside from Java. This is a potentially powerful route to incorporate automatic parallelism into the implementations [22]. data parallel or multi-threading parallelism ideas can be implemented according to a strict pattern that will work well for this class of regular lattice simulation model.…”

Section: Discussionmentioning

confidence: 99%

Engineering Internal Domain-Specific Language Software for Lattice-based Simulations

Parallel and Distributed Computing and Systems / 790: Software Engineering and Applications

2012

Modern high-level programming languages are making it practical to develop internal domain-specific languages (DSL) for even computationally intensive applications such as complex systems simulations. We present a prototype DSL to implement lattice-based operations for a whole family of simulation models on different lattices and with different neighbourhood localities. We use closure techniques to switch between lattice geometries and neighbourhoods at run-time. We show how a framework can be implemented in both C++ and Java and that a fluent interface DSL command-line layer and a graphical interface layer can both use this same framework. We find that we can drastically speed up the development and testing of a new simulation model that fits our DSL pattern and demonstrate this with significantly reduced lines of code needed for an incrementally added new model. We present results based on two-dimensional lattice models with discrete cell states for topologically square, hexagonal and triangular geometries and describe how these ideas generalise to higher dimensional problems. We also discuss how the use of internal domain specific languages and tools can facilitate further rapid development of other simulation codes and models.

“…There is also scope for adding further parallel-specific optimisations and heuristics to our code generator [32]. We also anticipate further developing the library of solvers and the support available for higher order calculus operations such as the bi and tri-harmonic operators.…”

Section: Discussionmentioning

confidence: 99%

Auto-generation of Parallel Finite-Differencing Code for MPI, TBB and CUDA

Playne

2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PHD Forum

2011

Abstract-Finite-difference methods can be useful for solving certain partial differential equations (PDEs) in the time domain. Compiler technologies can be used to parse an application domain specific representation of these PDEs and build an abstract representation of both the equation and the desired solver. This abstract representation can be used to generate a language-specific implementation. We show how this framework can be used to generate software for several parallel platforms: Message Passing Interface (MPI), Threading Building Blocks(TBB) and Compute Unified Device Architecture(CUDA). We present performance data of the automatically-generated parallel code and discuss the implications of the generator in terms of code portability, development time and maintainability.