An automatic tool flow for the combined implementation of multi-mode circuits

A multi-mode circuit implements the functionality of a limited number of circuits, called modes, of which at any given time only one needs to be realised. Using run-time reconfiguration of an FPGA, all the modes can be implemented on the same reconfigurable region, requiring only an area that can contain the biggest mode. Typically, conventional run-time reconfiguration techniques generate a configuration for every mode separately. To switch between modes the complete reconfigurable region is rewritten, which often leads to very long reconfiguration times. In this paper we present a novel, fully automated tool flow that exploits similarities between the modes and uses Dynamic Circuit Specialization to drastically reduce reconfiguration time. Experimental results show that the number of bits that is rewritten in the configuration memory reduces with a factor from 4.6X to 5.1X without significant performance penalties

A Methodology to Design FPGA-based PID Controllers

This paper presents a methodology to implement PID (Proportional, Integral, Derivative) controllers in FPGAs (Field-Programmable Gate Arrays) using fixed-point numerical representation. The Matlab/Simulink environment is used for modeling, simulation and evaluation the performance provided by different fixed-point representations using a given control process. A static bit-width analyzer is used to give a specialized fixed-point representation for each operand/operator in the controller system. After bit-width analysis, a VHDL represen-tation of the system is generated. Results show that the proposed methodology leads to shorten design cycles achieving important resource savings by employing specialized fixed-point repre-sentations

Enriching MATLAB with aspect-oriented features for developing embedded systems

This article presents an approach to enrich the MATLAB language with aspect-oriented modularity features, enabling developers to experiment different implementation characteristics and to acquire runtime data and traces without polluting their base MATLAB code. We propose a language through which programmers configure the low-level data representation of variables and expressions. Examples include specifically-tailored fixed-point data representations leading to more efficient support for the underlying hardware, e.g., digital signal processors and application-specific architectures, without built-in floating point units. This approach assists developers in adding handlers and monitoring features in a non-invasive way as well as configuring MATLAB functions with optimized implementations. Different aspect modules can be used to retarget common MATLAB code bases for different purposes and implementations. We validate the proposed approach with a set of representative examples where we attain a simple way to explore a number of properties. Experiment results and collected aspect-oriented software metrics lend support to the claims on its usefulness.This work was partially supported by FCT (Portuguese Science Foundation) under the project AMADEUS (POCTI, PTDC/EIA/70271/2006)

Paleolítico médio em Galapos (Arrábida)

Descrevem-se artefactos líticos de quartzo (e sílex) recolhidos em Galapos (Creiro), na vertente meridional da Serra da Arrábida. São característicos do Paleolítico médio (Mustierense) e reforçam a evidência da importante ocupação humana da região, já salientada pelo estudo da gruta da Figueira Brava.info:eu-repo/semantics/publishedVersio

LARA as a language-independent aspect-oriented programming approach

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

Aspect composition for multiple target languages using LARA

Usually, Aspect-Oriented Programming (AOP) languages are an extension of a specific target programming language (e.g., Aspect J for JAVA and Aspect C++ for C++). Although providing AOP support with target language extensions may ease the adoption of an approach, it may impose constraints related with constructs and semantics. Furthermore, by tightly coupling the AOP language to the target language the reuse potential of many aspects, especially the ones regarding non-functional requirements, is lost. LARA is a domain-specific language inspired by AOP concepts, having the specification of source-to-source transformations as one of its main goals. LARA has been designed to be, as much as possible, independent of the target language and to provide constructs and semantics that ease the definition of concerns, especially related to non-functional requirements. In this paper, we propose techniques to overcome some of the challenges presented by a multilanguage approach to AOP of cross-cutting concerns focused on non-functional requirements and applied through the use of a weaving process. The techniques mainly focus on providing well-defined library interfaces that can have concrete implementations for each supported target language. The developer uses an agnostic interface and the weaver provides a specific implementation for the target language. We evaluate our approach using 8 concerns with varying levels of language agnosticism that support 4 target languages (C, C++, JAVA and MATLAB) and show that the proposed techniques contribute to more concise LARA aspects, high reuse of aspects, and to significant effort reductions when developing weavers for new imperative, object-oriented programming languages

An OpenMP based Parallelization Compiler for C Applications

Directive-drive programming models, such as OpenMP, are one solution for exploiting the potential of multi-core architectures, and enable developers to accelerate software applications by adding annotations on for-type loops and other code regions. However, manual parallelization of applications is known to be a non trivial and time consuming process, requiring parallel programming skills. Automatic parallelization approaches can reduce the burden on the application development side. This paper presents an OpenMP based automatic parallelization compiler, named AutoPar-Clava, for automatic identification and annotation of loops in C code. By using static analysis, parallelizable regions are detected, and a compilable OpenMP parallel code from the sequential version is produced. In order to reduce the accesses to shared memory by each thread, each variable is categorized into the proper OpenMP scoping. Also, AutoPar-Clava is able to support reduction on arrays, which is available since OpenMP 4.5. The effectiveness of AutoPar-Clava is evaluated by means of the Polyhedral Benchmark suite, and targeting a N-cores x86-based computing platform. The achieved results are very promising and compare favorably with closely related auto-parallelization compilers such as Intel C/C++ Compiler (i.e., icc), ROSE, TRACO, and Cetus