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Details

  • Name

    Luís Cubal Reis
  • Cluster

    Computer Science
  • Role

    Research Assistant
  • Since

    01st October 2016
Publications

2017

Compiler Techniques for Efficient MATLAB to OpenCL Code Generation

Authors
Reis, L; Bispo, J; Cardoso, JMP;

Publication
Proceedings of the 5th International Workshop on OpenCL - IWOCL 2017

Abstract

2016

SSA-based MATLAB-to-C compilation and optimization

Authors
Reis, L; Bispo, J; Cardoso, JMP;

Publication
Proceedings of the 3rd ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming, ARRAY@PLDI 2016, Santa Barbara, CA, USA, June 14, 2016

Abstract
Many fields of engineering, science and finance use models that are developed and validated in high-level languages such as MATLAB. However, when moving to environments with resource constraints or portability challenges, these models often have to be rewritten in lower-level languages such as C. Doing so manually is costly and error-prone, but automated approaches tend to generate code that can be substantially less efficient than the handwritten equivalents. Additionally, it is usually difficult to read and improve code generated by these tools. In this paper, we describe how we improved our MATLAB-to-C compiler, based on the MATISSE framework, to be able to compete with handwritten C code. We describe our new IR and the most important optimizations that we use in order to obtain acceptable performance. We also analyze multiple C code versions to identify where the generated code is slower than the handwritten code and identify a few key improvements to generate code capable of outperforming handwritten C. We evaluate the new version of our compiler using a set of benchmarks, including the Disparity benchmark, from the San Diego Vision Benchmark Suite, on a desktop computer and on an embedded device. The achieved results clearly show the efficiency of the current version of the compiler. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

2015

Techniques for efficient MATLAB-to-C compilation

Authors
Bispo, J; Reis, L; Cardoso, JMP;

Publication
Proceedings of the 2nd ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming, ARRAY@PLDI, Portland, OR, USA, June 15 - 17, 2015

Abstract
MATLAB to C translation is foreseen to raise the overall abstraction level when mapping computations to embedded systems (possibly consisting of software and hardware components), and thus for increasing productivity and for providing an automated modeldriven design-flow. This paper describes recent work developed in the context of MATISSE, a MATLAB to C compiler targeting embedded systems. We introduce several techniques to allow the efficient generation of C code, such as weak types, primitives and matrix views. We evaluate the compiler with a set of 9 publicly available benchmarks, targeting both embedded systems and a desktop system. We compare the execution time of the generated C code with the original code running on MATLAB, achieving a geometric mean speedup of 8.1 ×, and qualitatively compare our results with the performance of related approaches. The use of the new techniques allowed the compiler to achieve performance improvements of 46% on average.

2015

C and OpenCL Generation from MATLAB

Authors
Bispo, J; Reis, L; Cardoso, JMP;

Publication
30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, VOLS I AND II

Abstract
In many engineering and science areas, models are developed and validated using high-level programing languages and environments as is the case with MATLAB. In order to target the multicore heterogeneous architectures being used on embedded systems to provide high performance computing with acceptable energy/power envelops, developers manually migrate critical code sections to lower-level languages such as C and OpenCL, a time consuming and error prone process. Thus, automatic source-to-source approaches are highly desirable. We present an approach to compile MATLAB and output equivalent C/OpenCL code to target architectures, such as GPU based hardware accelerators. We evaluate our approach on an existing MATLAB compiler framework named MATISSE. The OpenCL generation relies on the manual insertion of directives to guide the compilation and is also capable of generating C wrapper code to interface and synchronize with the OpenCL code. We evaluated the compiler with a number of benchmarks from different domains and the results are very encouraging.

2014

Multi-target c code generation from MATLAB

Authors
Bispo, J; Reis, L; Cardoso, JMP;

Publication
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)

Abstract
This paper describes our recent work on MATISSE, a framework for MATLAB to C compilation. We focus on the new optimizations and transformations, as well as on OpenCL generation. MATISSE is controlled with LARA, an aspect-oriented language, able to specify transformations to the input MATLAB code (e.g., insertion of code for variable initialization and for monitoring) and to express information concerning types and shapes of variables. We evaluate the compiler with a set of benchmarks when targeting both an embedded system and a desktop system. The results show that we were able to achieve a speedup up to 1.8× by employing information provided by LARA aspects. We also compare the execution time of the generated C code with the original code running on MATLAB, and we achieve a geometric mean speedup of 19×. The geometric mean speedup reduces to 12× when optimizing the MATLAB code with LARA aspects. Finally, we present a preliminary version of a fully-functioning pragma-based OpenCL generator, built over the MATISSE framework..