1. Evaluation of Branch Predictors Using High-density-branch Programs Fang Pang MEng. Lei Zhu MEng. Electrical and Computer Engineering Department University of Alberta November, 2002

2. Introduction In this project, we are going to evaluate different branch predictors for high-density-branch programs. A C code for Binary (6,4) encoder and decoder is used as example program. 1. Simplescalar tool will be used as the simulation tool. 2. The effectiveness of different types of branch predictors is observed. And the effect of the size of predictor is observed.

3. Example Program The Binary (6,4) encoder takes 4-bit source words as inputs, reads though the lookup table stored in the memory, finds out the corresponding 6-bit code words and exports code words. All code words are added by random noise and sent to Binary (6,4) decoder. The Binary (6,4) decoder takes these 6-bit code words as inputs, reads through the lookup table, finds out the corresponding 4-bit source words and exports source words. And it treats it as an error if the corresponding source word can’t be found in the lookup table. At the end of process, it calculates the number of errors and the error rate. This program contains high-density branches. Most of them are random conditon branches.

4. Project Description Taken branch, bimodal predictor, 2-level adaptive predictor and combined predictor are evaluated. Different size of predictors are compared. Multiple function units and multiple ports of memory are used to support wide issue. Different caches for data and instructions are used.

5. Simulation Sim-Outorder will be used to evaluate performance of different branch predictors. Different size predictors will be tested and compared.

6. Goal Find out the best branch predictor for this example program. Find out the relationship between the size of predictor and its performance.

7. Question ??? Thanks!