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About

I'm a post-doctoral researcher at the SPeCS lab in the Faculty of Engineering, University of Porto. My area of expertise is source-to-source compilers and code generation, and I have done work both in high-level languages, such as MATLAB and C++, and low-level languages, such as assembly and VHDL.

From 2012 to 2015, my main line of research was MATLAB to C compilation, and I was the creator and main developer of the tool MATISSE (specs.fe.up.pt/tools/matisse). Currently I am working on Clava (specs.fe.up.pt/tools/clava), a C++ source-to-source transformation tool based on Clang, as part of the H2020 project ANTAREX (antarex-project.eu) which focus on strategies for autotunning and energy efficiency in HPC.

Previous work includes translation of Perl-Compatible Regular Expressions (PCRE) to HDL, and automatic runtime migration of loops found in MicroBlaze assembly traces to customized hardware (the subject of the PhD thesis).

I've received a Bachelor's degree in Computer Systems and Informatics from the Univ. of Algarve in July 2006, and in July 2012 received the Ph.D. degree from Instituto Superior Técnico (IST), Lisbon, with the thesis “Mapping Runtime-Detected Loops from Microprocessors to Reconfigurable Processing Units”.

Interest
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Details

Details

Publications

2020

Source-to-source compilation targeting OpenMP-based automatic parallelization of C applications

Authors
Arabnejad, H; Bispo, J; Cardoso, JMP; Barbosa, JG;

Publication
Journal of Supercomputing

Abstract
Directive-driven programming models, such as OpenMP, are one solution for exploring the potential parallelism when targeting multicore architectures. Although these approaches significantly help developers, code parallelization is still a non-trivial and time-consuming process, requiring parallel programming skills. Thus, many efforts have been made toward automatic parallelization of the existing sequential code. This article presents AutoPar-Clava, an OpenMP-based automatic parallelization compiler which: (1) statically detects parallelizable loops in C applications; (2) classifies variables used inside the target loop based on their access pattern; (3) supports reduction clauses on scalar and array variables whenever it is applicable; and (4) generates a C OpenMP parallel code from the input sequential version. The effectiveness of AutoPar-Clava is evaluated by using the NAS and Polyhedral Benchmark suites and targeting a 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 (icc), ROSE, TRACO and CETUS. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

2019

Supporting the Scale-up of High Performance Application to Pre-Exascale Systems: The ANTAREX Approach

Authors
Silvano, C; Agosta, G; Bartolini, A; Beccari, AR; Benini, L; Besnard, L; Bispo, J; Cmar, R; Cardoso, JMP; Cavazzoni, C; Cesarini, D; Cherubin, S; Ficarelli, F; Gadioli, D; Golasowski, M; Lasri, I; Libri, A; Manelfi, C; Martinovic, J; Palermo, G; Pinto, P; Rohou, E; Sanna, N; Slaninova, K; Vitali, E;

Publication
2019 27TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING (PDP)

Abstract
The ANTAREX project developed an approach to the performance tuning of High Performance applications based on an Aspect-oriented Domain Specific Language (DSL), with the goal to simplify the enforcement of extra-functional properties in large scale applications. The project aims at demonstrating its tools and techniques on two relevant use cases, one in the domain of computational drug discovery, the other in the domain of online vehicle navigation. In this paper, we present an overview of the project and of its main achievements, as well as of the large scale experiments that have been planned to validate the approach.

2019

Nonio — modular automatic compiler phase selection and ordering specialization framework for modern compilers

Authors
Nobre, R; Bispo, J; Carvalho, T; Cardoso, JMP;

Publication
SoftwareX

Abstract
This article presents Nonio, a modular, easy-to-use, design space exploration framework focused on exploring custom combinations of compiler flags and compiler sequences. We describe the framework and discuss its use with two of the most popular compiler toolchains, GCC and Clang+LLVM. Particularly, we discuss implementation details in the context of flag selection, when using GCC, and phase selection and ordering, when using Clang+LLVM. The framework software organization allows to easily add new components as plug-ins (e.g., an exploration algorithm, an objective metric, integration with another compiler toolchain). The software architecture provides well-defined interfaces, in order to enable seamless composition and interaction between different components. We present, as an example, a use case where we rely on Nonio to obtain custom compiler flags for reducing the execution time and the energy consumption of a C program, in relation to the best predetermined optimization settings provided by the compiler (e.g., –O3). © 2019

2019

The ANTAREX domain specific language for high performance computing

Authors
Silvano, C; Agosta, G; Bartolini, A; Beccari, AR; Benini, L; Besnard, L; Bispo, J; Cmar, R; Cardoso, JMP; Cavazzoni, C; Cesarini, D; Cherubin, S; Ficarelli, F; Gadioli, D; Golasowski, M; Libri, A; Martinovic, J; Palermo, G; Pinto, P; Rohou, E; Slaninova, K; Vitali, E;

Publication
MICROPROCESSORS AND MICROSYSTEMS

Abstract
The ANTAREX project relies on a Domain Specific Language (DSL) based on Aspect Oriented Programming (AOP) concepts to allow applications to enforce extra functional properties such as energy-efficiency and performance and to optimize Quality of Service (QoS) in an adaptive way. The DSL approach allows the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management. In this paper, we present an overview of the key outcome of the project, the ANTAREX DSL, and some of its capabilities through a number of examples, including how the DSL is applied in the context of the project use cases.

2019

A framework for automatic and parameterizable memoization

Authors
Besnard, L; Pinto, P; Lasri, I; Bispo, J; Rohou, E; Cardoso, JMP;

Publication
SoftwareX

Abstract
Improving execution time and energy efficiency is needed for many applications and usually requires sophisticated code transformations and compiler optimizations. One of the optimization techniques is memoization, which saves the results of computations so that future computations with the same inputs can be avoided. In this article we present a framework that automatically applies memoization techniques to C/C++ applications. The framework is based on automatic code transformations using a source-to-source compiler and on a memoization library. With the framework users can select functions to memoize as long as they obey to certain restrictions imposed by our current memoization library. We show the use of the framework and associated memoization technique and the impact on reducing the execution time and energy consumption of four representative benchmarks. © 2019

Supervised
thesis

2019

Aspect-Oriented Programming for Javascript Using the LARA Language

Author
Ricardo de Sá Loureiro Ferreira da Silva

Institution
UP-FEUP

2019

Scalable and Configurable Event Processing Engine

Author
Edgar de Lemos Passos

Institution
UP-FEUP