NDLI: Variable length path branch prediction (SIGP, Vol. 33, Issue. 11)

Content Provider	ACM Digital Library
Author	Evers, Marius Stark, Jared Patt, Yale N.
Abstract	Accurate branch prediction is required to achieve high performance in deeply pipelined, wide-issue processors. Recent studies have shown that conditional and indirect (or computed) branch targets can be accuratelypredicted by recording the path, which consists of the target addresses of recent branches, leading up to the branch. In current path based branch predictors, the N most recent target addresses are hashed together to form an index into a table, where N is some fixed integer. The indexed table entry isused to make a prediction for the current branch.This paper introduces a new branch predictor in which the value of N is allowed to vary. By constructing the index into the table using the last N target addresses, and using profiling information to select the proper value of N for each branch, extremely accurate branch prediction is achieved. For the SPECint95 gee benchmark, this new predictor has a conditional branch misprediction rate of 4.3% given a 4K byte hardware budget. For comparison, the gshare predictor, a predictor known for its high accuracy, has a conditional branch misprediction rate of 8.8% given the same hardware budget. For the indirect branches in gee, the new predictor achieves a misprediction rate of 27.7% when given a hardware budget of 512 bytes, whereas the best competingpredictor achieves a misprediction rate of 44.2% when given the same hardware budget.
Starting Page	170
Ending Page	179
Page Count	10
File Format	PDF
ISSN	03621340 15581160
DOI	10.1145/291006.291042
Journal	ACM SIGPLAN Notices (SIGP)
Volume Number	33
Issue Number	11
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1983-05-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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