Abstract
MATLAB is a high-level language used in various scientific and engineering fields. Deployment of well-Tested MATLAB code to production would be highly desirable, but in practice a number of obstacles prevent this, notably performance and portability. Although MATLAB-To-C compilers exist, the performance of the generated C code may not be sufficient and thus it is important to research alternatives, such as CPU parallelism, GPGPU computing and FPGAS. OpenCL is an API and programming language that allows targeting these devices, hence the motivation for MATLAB-To-OpenCL compilation. In this paper, we describe our recent efforts on offloading code to OpenCL devices in the context of our MATLAB to C/OpenCL compiler. © 2017 ACM.

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A summary of contributions made by significant papers from the first 25 years of the Field-Programmable Logic and Applications conference (FPL) is presented. The 27 papers chosen represent those which have most strongly influenced theory and practice in the field.

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Usually, Aspect-Oriented Programming (AOP) languages are an extension of a specific target language (e.g., AspectJ for Java and AspectC++ for C++). This coupling can impose drawbacks such as arbitrary limitations to the aspect language. LARA is a DSL for source-to-source transformations inspired by AOP concepts, and has been designed to be independent of the target language. In this paper we propose techniques to overcome some of the challenges presented by a language-independent approach to source code transformations, and present and discuss possible solutions and their impact. Additionally, we present some of the benefits and opportunities of this approach. We present an evaluation of our approach, show that we can significantly reduce the effort to develop weavers for new target languages and that the proposed techniques contribute to more concise LARA aspects and safer semantics. Copyright 2017 ACM.

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