An Automated Code Generation of Instruction Set Implementation and Functional Testing for gem5

Zhao Ziwei; Tu Hang; Liu Qin; Li Li; Yu Tao

doi:10.7544/issn1000-1239.202220158

Journal of Computer Research and Development > 2023 > 60(7): 1678-1691. > DOI: 10.7544/issn1000-1239.202220158 CSTR: 32373.14.issn1000-1239.202220158

Zhao Ziwei, Tu Hang, Liu Qin, Li Li, Yu Tao. An Automated Code Generation of Instruction Set Implementation and Functional Testing for gem5[J]. Journal of Computer Research and Development, 2023, 60(7): 1678-1691. DOI: 10.7544/issn1000-1239.202220158

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An Automated Code Generation of Instruction Set Implementation and Functional Testing for gem5

School of Cyber Science and Engineering, Wuhan University, Wuhan 430072

Funds: This work was supported by the National Key Research and Development Program of China (2018YFC1315404, 2018YFC1604004).

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Author Bio:
Zhao Ziwei: born in 1998. Master candidate. Her main research interest includes embedded system security

Tu Hang: born in 1975. PhD, associate professor. Member of CCF. His main research interests include IoT security, embedded system security, cryptography and network security

Liu Qin: born in 1978. PhD, associate professor. Member of CCF. Her main research interests include IoT security, embedded system security, and cloud computing security

Li Li: born in 1976. PhD, associate professor. Member of CCF. Her main research interests include embedded system security, IoT security, and mobile security

Yu Tao: born in 1997. Master candidate. His main research interest includes embedded system security
Received Date: February 20, 2022
Revised Date: July 07, 2022
Available Online: February 28, 2023

Graphical Abstract

Abstract

Abstract

Computer system simulators are important tools for research and prototype development of embedded systems. For interpretation-based simulators, the decoding process of CPU models has an important effect on their performance. Therefore, improving the performance of the decoding process is one of the key problems of simulation efficiency. Besides, for instruction sets without a standard test suite (such as custom instructions), writing functional tests manually leads to low development efficiency. The instruction information required by functional tests is practically the same as the implementation of the decoding process. To solve the above problems, we propose a code generation method, which takes an instruction set description as input and outputs its implementation codes optimized for gem5 and its functional tests. Firstly, we extend the instruction set description language of gem5 and divide it into code description, function description, and test description. Secondly, we optimize the construction algorithm of decoding decision trees for gem5 and generate decoding codes, instruction codes, and functional test cases. Lastly, we take the Cortex-M3 instruction set as an example and compare our method with the original method of gem5. The total generation time is reduced by about 64%, the compiled executable code size is reduced by about 407 KB, the performance is improved by about 13%, and our method can improve the development efficiency.
- code generation,
- instruction set,
- decoding,
- simulator,
- functional testing

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References (19)

References

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