ISCA '86 Proceedings of the 13th annual international symposium on Computer architecture
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Achieving high instruction cache performance with an optimizing compiler
ISCA '89 Proceedings of the 16th annual international symposium on Computer architecture
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
A static performance estimator to guide data partitioning decisions
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
Using profile information to assist classic code optimizations
Software—Practice & Experience
Profile-guided automatic inline expansion for C programs
Software—Practice & Experience
Predicting conditional branch directions from previous runs of a program
ASPLOS V Proceedings of the fifth international conference on Architectural support for programming languages and operating systems
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
A comparison of dynamic branch predictors that use two levels of branch history
ISCA '93 Proceedings of the 20th annual international symposium on computer architecture
Accurate static estimators for program optimization
PLDI '94 Proceedings of the ACM SIGPLAN 1994 conference on Programming language design and implementation
ATOM: a system for building customized program analysis tools
PLDI '94 Proceedings of the ACM SIGPLAN 1994 conference on Programming language design and implementation
Fast and accurate instruction fetch and branch prediction
ISCA '94 Proceedings of the 21st annual international symposium on Computer architecture
Static branch frequency and program profile analysis
MICRO 27 Proceedings of the 27th annual international symposium on Microarchitecture
Reducing branch costs via branch alignment
ASPLOS VI Proceedings of the sixth international conference on Architectural support for programming languages and operating systems
ICS '90 Proceedings of the 4th international conference on Supercomputing
Mathematical Perspectives on Neural Networks
Mathematical Perspectives on Neural Networks
A study of branch prediction strategies
ISCA '81 Proceedings of the 8th annual symposium on Computer Architecture
The predictability of branches in libraries
Proceedings of the 28th annual international symposium on Microarchitecture
Compiler synthesized dynamic branch prediction
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Implementation and analysis of path history in dynamic branch prediction schemes
ICS '97 Proceedings of the 11th international conference on Supercomputing
Analyzing the working set characteristics of branch execution
MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Branch Prediction Using Profile Data
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
An alternative to branch prediction: pre-computed branches
ACM SIGARCH Computer Architecture News
Fast Path-Based Neural Branch Prediction
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Two-level branch prediction using neural networks
Journal of Systems Architecture: the EUROMICRO Journal - Special issue: Synthesis and verification
Fast searches for effective optimization phase sequences
Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation
Improved latency and accuracy for neural branch prediction
ACM Transactions on Computer Systems (TOCS)
Fast and efficient searches for effective optimization-phase sequences
ACM Transactions on Architecture and Code Optimization (TACO)
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Correctly predicting the direction that branches will take is increasingly important in today's wide-issue computer architectures. The name program-based branch prediction is given to static branch prediction techniques that base their prediction on a program's structure. In this paper, we investigate a new approach to program-based branch prediction that uses a body of existing programs to predict the branch behavior in a new program. We call this approach to program-based branch prediction, evidence-based static prediction, or ESP. The main idea of ESP is that the behavior of a corpus of programs can be used to infer the behavior of new programs. In this paper, we use a neural network to map static features associated with each branch to the probability that the branch will be taken. ESP shows significant advantages over other prediction mechanisms. Specifically, it is a program-based technique, it is effective across a range of programming languages and programming styles, and it does not rely on the use of expert-defined heuristics. In this paper, we describe the application of ESP to the problem of branch prediction and compare our results to existing program-based branch predictors. We also investigate the applicability of ESP across computer architectures, programming languages, compilers, and run-time systems. Averaging over a body of 43 C and Fortran programs, ESP branch prediction results in a miss rate of 20%, as compared with the 25% miss rate obtained using the best existing program-based heuristics.