• Title/Summary/Keyword: Retargetable C Compiler

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Construction of a Retargetable Compiler Generation System from Machine Behavioral Description (머쉰 행위기술로부터 Retargetable 컴파일러 생성시스템 구축)

  • Lee, Sung-Rae;Hwang, Sun-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5B
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    • pp.286-294
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    • 2007
  • In ASIP design, compiler is required for performance evaluation of processors being designed. The design of machine specific compiler is time consuming. This paper presents the system which generates C compiler from MDL descriptions. Compiler generation using MDL can support user retargetability and concurrency between compiler design and processor design. However, it must overcome semantics gap between compiler and machine. To handle this problem, the proposed system maps behavioral descriptions to library which contains abstract behavior for each tree pattern. Using mapped instructions and information on register file usage, the proposed system generates back-end interface function of the compiler. Generated compilers, for MIPS R3000, ARM9 cores, have been proved by application programs written in C code.

A Study of LCC Retargetable Compiler for Embedded Systems (임베디드 시스템 지원을 위한 LCC Retargetable Compiler 에 관한 연구)

  • Hong, Il-Kyeong;Kim, Ki-Chang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.11a
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    • pp.431-434
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    • 2003
  • 과거 임베디드 시스템은 산업용 같은 특수한 경우와 여러 전자 제품에서 눈에 뛰지 않는 형태로 사용이 되어 왔지만 최근 들어 정보통신 분야가 발전하고 가격 대 성능비가 우수한 Microcontroller 와 CPU 들이 등장하면서 더욱 더 각광을 받기 시작했다. 이들의 개발환경은 C 언어와 어셈블리어가 주를 차지하고 있는데 개발상의 많은 장점 때문에 C 언어를 선택하여 사용하고 있지만 target machine 의 C 컴파일러가 전부 제공되지 않고 일부 machine 만 제공되고 있기 때문에 C 언어의 사용은 아직 제한적이다. 이에 본 논문에서는 Retargetable Compiler 인 LCC 를 이용하여 임베디드용 machine 에 대해 retargeting 이 가능하도록 LCC 를 개선시키고자 한다.

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Test Suit Generation System for Retargetable C Compilers (재겨냥성 C 컴파일러를 위한 테스트 집합 생성 시스템)

  • Woo, Gyun;Bae, Jung-Ho;Jang, Han-Il;Lee, Yun-Jung;Chae, Heung-Seok
    • The KIPS Transactions:PartA
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    • v.16A no.4
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    • pp.245-254
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    • 2009
  • With the increasing adoption of embedded processors, the need of developing compilers for the embedded processors with timely manner is also growing. Retargeting has been adopted as a viable approach to constructing new compilers by modifying the back-end of an existing compiler. This paper proposes a test suite generation system for testing retargetable C compilers. The proposed system generates the test suite using the grammar coverage concept. Generally, the size of the test suite satisfying the grammar coverage of the source language is very large. Hence, the proposed system also provides the facility to reduce the size of the test suite. According to the experimental result, the reduced test suite can detect 75% of the compiler faults detected by the original test suite though the size of the reduced test suite is only 10% of that of the original test suite in average. This result indicates that the reduction technique proposed in this paper can be effectively used in the prior phase of the development procedure of the embedded compilers.

An Efficient Architecture Exploration Method for Optimal ASIP Design (Application에 최적의 ASIP 설계를 위한 효율적인 Architecture Exploration 방법)

  • Lee, Sung-Rae;Hwang, Sun-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.9C
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    • pp.913-921
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    • 2007
  • Retargetable compiler which generates executable code for a target processor and performance profiler are required to design a processor optimized for a specific application. This paper presents an architecture exploration methodology based on ADL (Architecture Description Language). We synthesized instruction set and optimized processor structure using information extracted from application program. The information of operation sequences executed frequently and register usage are used for processor optimization. Architecture exploration has been performed for JPEG encoder to show the effectiveness of the system. The ASIP designed using the proposed method shows 1.97 times better performance.