Dynamic Ineffectuality-based Clustered Architectures (2304.12762v1)

Abstract: The direction of conditional branches is predicted correctly in modern processors with great accuracy. We find several instructions in the dynamic instruction stream that contribute only towards computing the condition of these instructions. Hence, when the predicted direction of conditional branches is indeed correct, these instructions become Ineffectual - the functional state of the program would not be different had these instructions been dropped. However, the execution of ineffectual instructions cannot be avoided altogether because it is possible that the prediction of the branch direction is wrong. In this work, we determine all sources of ineffectuality in an instruction stream such as conditional branches, predicated instructions, indirect jumps and dynamically dead instructions. Then, we propose a technique to steer the ineffectual instructions away from the primary execution cluster so that effectual instructions can execute uncontended. We find that such ineffectuality-based clustering of instructions naturally simplifies the design and avoids several caveats of a clustered architecture. Finally, we propose a technique to detect instances when instructions were incorrectly marked as ineffectual, say due to a branch misprediction, and recover the pipeline. The empirical evaluation of the proposed changes on the SPEC CPU2017 and GAPBS benchmarks show performance uplifts of up to 4.9% and 10.3% on average respectively.