Automatic Target Description File Generation

IF 1.2 3区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Journal of Computer Science and Technology Pub Date : 2023-12-01 DOI:10.1007/s11390-022-1919-x
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Abstract

Agile hardware design is gaining increasing momentum and bringing new chips in larger quantities to the market faster. However, it also takes new challenges for compiler developers to retarget existing compilers to these new chips in shorter time than ever before. Currently, retargeting a compiler backend, e.g., an LLVM backend to a new target, requires compiler developers to write manually a set of target description files (totalling 10 300+ lines of code (LOC) for RISC-V in LLVM), which is error-prone and time-consuming. In this paper, we introduce a new approach, Automatic Target Description File Generation (ATG), which accelerates the generation of a compiler backend for a new target by generating its target description files automatically. Given a new target, ATG proceeds in two stages. First, ATG synthesizes a small list of target-specific properties and a list of code-layout templates from the target description files of a set of existing targets with similar instruction set architectures (ISAs). Second, ATG requests compiler developers to fill in the information for each instruction in the new target in tabular form according to the list of target-specific properties synthesized and then generates its target description files automatically according to the list of code-layout templates synthesized. The first stage can often be reused by different new targets sharing similar ISAs. We evaluate ATG using nine RISC-V instruction sets drawn from a total of 1 029 instructions in LLVM 12.0. ATG enables compiler developers to generate compiler backends for these ISAs that emit the same assembly code as the existing compiler backends for RISC-V but with significantly less development effort (by specifying each instruction in terms of up to 61 target-specific properties only).

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自动生成目标描述文件
摘要 敏捷硬件设计的发展势头日益强劲,并能更快地将更多新芯片推向市场。然而,这也给编译器开发人员带来了新的挑战,他们需要在比以往更短的时间内将现有编译器重定向到这些新芯片。目前,将编译器后端(如 LLVM 后端)重定向到新目标需要编译器开发人员手动编写一组目标描述文件(LLVM 中 RISC-V 的代码行数超过 10 300 行),既容易出错又耗时。在本文中,我们介绍了一种新方法--自动目标描述文件生成(ATG),它通过自动生成目标描述文件来加速新目标编译器后端的生成。给定一个新目标,ATG 分两个阶段进行。首先,ATG 从一组具有类似指令集架构(ISA)的现有目标机的目标机描述文件中合成一小部分目标机特定属性列表和代码布局模板列表。其次,ATG 要求编译器开发人员根据合成的目标特定属性列表,以表格形式填写新目标中每条指令的信息,然后根据合成的代码布局模板列表自动生成目标描述文件。共享类似 ISA 的不同新目标通常可以重复使用第一阶段。我们使用 LLVM 12.0 中总共 1 029 条指令中的九个 RISC-V 指令集对 ATG 进行了评估。ATG 使编译器开发人员能够为这些 ISA 生成编译器后端,这些后端可生成与现有 RISC-V 编译器后端相同的汇编代码,但开发工作量却大大减少(只需在多达 61 个目标特定属性中指定每条指令)。
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来源期刊
Journal of Computer Science and Technology
Journal of Computer Science and Technology 工程技术-计算机:软件工程
CiteScore
4.00
自引率
0.00%
发文量
2255
审稿时长
9.8 months
期刊介绍: Journal of Computer Science and Technology (JCST), the first English language journal in the computer field published in China, is an international forum for scientists and engineers involved in all aspects of computer science and technology to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the journal are selected through rigorous peer review, to ensure originality, timeliness, relevance, and readability. While the journal emphasizes the publication of previously unpublished materials, selected conference papers with exceptional merit that require wider exposure are, at the discretion of the editors, also published, provided they meet the journal''s peer review standards. The journal also seeks clearly written survey and review articles from experts in the field, to promote insightful understanding of the state-of-the-art and technology trends. Topics covered by Journal of Computer Science and Technology include but are not limited to: -Computer Architecture and Systems -Artificial Intelligence and Pattern Recognition -Computer Networks and Distributed Computing -Computer Graphics and Multimedia -Software Systems -Data Management and Data Mining -Theory and Algorithms -Emerging Areas
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