Global instruction scheduling for superscalar machines
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Branch history table prediction of moving target branches due to subroutine returns
ISCA '91 Proceedings of the 18th annual international symposium on Computer architecture
Target prediction for indirect jumps
Proceedings of the 24th annual international symposium on Computer architecture
The predictability of data values
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
The cascaded predictor: economical and adaptive branch target prediction
MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Improving prediction for procedure returns with return-address-stack repair mechanisms
MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Predicting indirect branches via data compression
MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Improving virtual function call target prediction via dependence-based pre-computation
ICS '99 Proceedings of the 13th international conference on Supercomputing
Improving branch predictors by correlating on data values
Proceedings of the 32nd annual ACM/IEEE international symposium on Microarchitecture
Using SimPoint for accurate and efficient simulation
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Optimizing indirect branch prediction accuracy in virtual machine interpreters
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Dynamic Data Dependence Tracking and its Application to Branch Prediction
HPCA '03 Proceedings of the 9th International Symposium on High-Performance Computer Architecture
Control-Flow Speculation through Value Prediction for Superscalar Processors
PACT '99 Proceedings of the 1999 International Conference on Parallel Architectures and Compilation Techniques
Proceedings of the 30th annual international symposium on Computer architecture
Improving Indirect Branch Prediction With Source- and Arity-based Classification and Cascaded Prediction
Adapting branch-target buffer to improve the target predictability of java code
ACM Transactions on Architecture and Code Optimization (TACO)
VPC prediction: reducing the cost of indirect branches via hardware-based dynamic devirtualization
Proceedings of the 34th annual international symposium on Computer architecture
Improving the performance of object-oriented languages with dynamic predication of indirect jumps
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Creating artificial global history to improve branch prediction accuracy
Proceedings of the 23rd international conference on Supercomputing
EXACT: explicit dynamic-branch prediction with active updates
Proceedings of the 7th ACM international conference on Computing frontiers
Communications of the ACM
ICCD '11 Proceedings of the 2011 IEEE 29th International Conference on Computer Design
A new case for the TAGE branch predictor
Proceedings of the 44th Annual IEEE/ACM International Symposium on Microarchitecture
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Indirect branch prediction is becoming increasingly important in modern high-performance processors. However, previous indirect branch predictors either require a significant amount of hardware storage and complexity, or heavily rely on the expensive manual profiling. In this paper, we propose the Compiler-Guided Value Pattern (CVP) prediction, an energy-efficient and accurate indirect branch prediction via compiler-microarchitecture cooperation. The key of CVP prediction is to use the compiler-guided value pattern as the correlated information to hint the dynamic predictor. The value pattern reflects the pattern regularity of the value correlation, and thus significantly improves the prediction accuracy even in the case of deep pipeline stage or long memory latency. CVP prediction relies on the compiler to automatically identify the primary value correlation based on three high-level program substructures: virtual function calls, switch-case statements and function pointer calls. The compiler-identified information is then fed back to the dynamic predictor and is further used to hint the indirect branch prediction at runtime. We show that CVP prediction can be implemented in modern processors with little extra hardware support. Evaluations show that CVP prediction can significantly improve the prediction accuracy by 46% over the traditional BTB-based prediction, leading to the performance improvement of 20%. Compared with the state-of-the-art aggressive ITTAGE and VBBI predictors, CVP prediction can improve the performance by 5.5% and 4.2% respectively.