Reducing the delay for decoding instructions by predicting their source register operands

Sanghyun Park, Jaeyung Jun, Changhyun Kim, Gyeongil Min, Hun Jae Lee, Seonwook Kim

Research output: Contribution to journalArticlepeer-review


The fetched instructions would have data dependency with in-flight ones in the pipeline execution of a processor, so the dependency prevents the processor from executing the incoming instructions for guaranteeing the program’s correctness. The register and memory dependencies are detected in the decode and memory stages, respectively. In a small embedded processor that supports as many ISAsas possible to reduce code size, the instruction decoding to identify register usage with the dependence check generally results in long delay and sometimes a critical path in its implementation. For reducing the delay, this paper proposes two methods—One method assumes the widely used source register operand bit-fields without fully decoding the instructions. However, this assumption would cause additional stalls due to the incorrect prediction; thus, it would degrade the performance. To solve this problem, as the other method, we adopt a table-based way to store the dependence history and later use this information for more precisely predicting the dependency. We applied our methods to the commercial EISC embedded processor with the Samsung 65nm process; thus, we reduced the critical path delay and increased its maximum operating frequency by 12.5% and achieved an average 11.4% speed-up in the execution time of the EEMBC applications. We also improved the static, dynamic power consumption, and EDP by 7.2%, 8.5%, and 13.6%, respectively, despite the implementation area overhead of 2.5%.

Original languageEnglish
Article number820
JournalElectronics (Switzerland)
Issue number5
Publication statusPublished - 2020 May


  • Data dependency
  • Decoding
  • ISAs
  • Register operand detection

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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