논문 상세보기

농업정보기술을 위한 ILP 프로세서에서 새로운 복구 메커니즘 적용 분기예측기

A Branch Predictor with New Recovery Mechanism in ILP Processors for Agriculture Information Technology

  • 언어KOR
  • URLhttps://db.koreascholar.com/Article/Detail/243021
구독 기관 인증 시 무료 이용이 가능합니다. 5,200원
한국농식품정보과학회 (Korean Society of Food and Agricultural Information Science)
초록

To improve the performance of wide-issue superscalar processors, it is essential to increase the width of instruction fetch and the issue rate. Removal of control hazard has been put forward as a significant new source of instruction-level parallelism for superscalar processors and the conditional branch prediction is an important technique for improving processor performance. Branch mispredictions, however, waste a large number of cycles, inhibit out-of-order execution, and waste electric power on mis-speculated instructions. Hence, the branch predictor with higher accuracy is necessary for good processor performance. In global-history-based predictors like gshare and GAg, many mispredictions come from commit update of the branch history. Some works on this subject have discussed the need for speculative update of the history and recovery mechanisms for branch mispredictions. In this paper, we present a new mechanism for recovering the branch history after a misprediction. The proposed mechanism adds an age_counter to the original predictor and doubles the size of the branch history register. The age_counter counts the number of outstanding branches and uses it to recover the branch history register. Simulation results on the SimpleScalar 3.0/PISA tool set and the SPECINT95 benchmarks show that gshare and GAg with the proposed recovery mechanism improved the average prediction accuracy by 2.14% and 9.21%, respectively and the average IPC by 8.75% and 18.08%, respectively over the original predictor.

저자
  • 고광현(한국농수산대학교 정보교육센터) | Kwang Hyun Ko
  • 조영일(수원대학교 컴퓨터학과) | Young Il Cho