Along with the advancement of chip architecture and density of processor design, there are more functional units that can execute in parallel on a chip. In order to make good use of them, it is important to obtain enough and accurate instructions ahead of time. Branch prediction provides a way to know the instruction stream ahead of time. Its prediction accuracy is thus one of the key factors of system performance.
In our research, we designed a branch prediction method based upon the loop-relevance classifications of conditional jump instructions. It divides conditional jump instructions into two classifications: loop-exit and non-loop-exit conditional jump instructions. We utilized various prediction methods to perform the branch prediction tasks for these two classes of conditional branch instructions, separately. Inside these methods, dynamic learning from actual branch results is carried out to switch to suitable prediction models such that more prediction accuracy can be obtained.
In this thesis research, in order to validate the accuracy of this prediction method vs. other prediction methods, we designed a software performance evaluation environment to do trace-driven simulation of types of branch prediction methods. It consists of an instruction trace extractor and a set of trace-driven simulators. Experiment results shows that our prediction methods performs near the same as other prediction methods on the scalar processing programs that have little or no amount of regularly behaved loops. However, on the scientific or engineering programs that exhibit certain percentage of regularly behaved loops, experiment results shows that our prediction method recognizes their loop behavior patterns and achieves better prediction accuracy.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0928101-155800 |
| Date | 28 September 2001 |
| Creators | Luo, Shiu-Tang |
| Contributors | Jer-Min Jou, Chia-Hsiung Kao, Tsung Lee |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0928101-155800 |
| Rights | restricted, Copyright information available at source archive |
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