Source transformation

About: Source transformation is a research topic. Over the lifetime, 103 publications have been published within this topic receiving 2244 citations.

Programming language features, usage patterns, and the efficiency of generated adjoint code

Abstract: The computation of gradients via the reverse mode of algorithmic differentiation is a valuable technique in modelling many science and engineering applications. This technique is particularly efficient when implemented as a source transformation, as it may use static data-flow analysis. However, some features of the major programming languages are detrimental to the efficiency of the transformed source code. This paper provides an overview of the most common problem scenarios and estimates the cost overhead incurred by using the respective language feature or employing certain common patterns. An understanding of these topics is crucial for the efficiency or even feasibility of adjoint computations, particularly for large-scale numerical simulations, for example, in geosciences. While one cannot hope to cover all effects observable with a given programming language in a given run time environment, the paper aims at providing a reasonable guide for the users of C/C++ and Fortran source transformation tools for algorithmic differentiation.

Second-order algorithmic differentiation by source transformation of MPI code

Abstract: A source transformation tool for algorithmic differentiation is introduced, capable of transforming MPI-enabled code into secondorder adjoint code. Our derivative code compiler (dcc) is used for the source transformation while a runtime library handles the adjoining of the MPI routines. This paper describes in detail the link between these two components in order to compute second derivatives. This process is illustrated by a simplified parallel implementation of Burgers' equation in a second-order optimization setting, for example, Newton's method.

From OpenMP to MPI: first experiments of the STEP source-to-source transformation tool.

Abstract: The STEP tool allows source-to-source transformation of programs, from OpenMP to MPI, for execution on distributed-memory platforms. This paper describes tests of STEP on popular benchmarks, and analyses the results. These experiments provide both encouraging feedback and directions for improvement of the tool.

Adjoining Hybrid Parallel Code

Abstract: OpenMP and MPI are typically used in combination to implement distributed shared memory parallelization schemes for numerical simulations on hybrid systems. The performance of said numerical simulations is frequently linked to the efficient and accurate computation of derivatives. One method of acquiring this derivative information for a given code is algorithmic differentiation (AD). AD implementations are subdivided into either source transformation or overloading tools. We investigate a generic approach of applying AD tools on hybrid parallel codes. A dense matrixmatrix multiplication serves as a case study.