Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Language and machine-independent global optimization on intermediate code
Computer Languages
Advanced compiler optimizations for supercomputers
Communications of the ACM - Special issue on parallelism
Effectiveness of a machine-level, global optimizer
SIGPLAN '86 Proceedings of the 1986 SIGPLAN symposium on Compiler construction
Optimizing compilers are here (mostly)
ACM SIGPLAN Notices
Vectorizing compilers: a test suite and results
Proceedings of the 1988 ACM/IEEE conference on Supercomputing
An evaluation of vector Fortran 200 generated by Cyber 205 and ETA-10 pre-compilation tools
Proceedings of the 1988 ACM/IEEE conference on Supercomputing
Interprocedual optimization: experimental results
Software—Practice & Experience
Machine Characterization Based on an Abstract High-Level Language Machine
IEEE Transactions on Computers
An analysis of MIPS and SPARC instruction set utilization on the SPEC benchmarks
ASPLOS IV Proceedings of the fourth international conference on Architectural support for programming languages and operating systems
CPU performance evaluation and execution time prediction using narrow spectrum benchmarking
CPU performance evaluation and execution time prediction using narrow spectrum benchmarking
An instruction timing model of CPU performance
ISCA '77 Proceedings of the 4th annual symposium on Computer architecture
Performance Characterization of Optimizing Compilers
Performance Characterization of Optimizing Compilers
Analysis and performance of computer instruction sets.
Analysis and performance of computer instruction sets.
A portable machine-independent global optimizer--design and measurements
A portable machine-independent global optimizer--design and measurements
Where are the optimizing compilers?
ACM SIGPLAN Notices
Analysis of benchmark characteristics and benchmark performance prediction
ACM Transactions on Computer Systems (TOCS)
Chronos: a Performance Characterization Tool Inside the EDPEPPS Toolset
The Journal of Supercomputing
Measuring Cache and TLB Performance and Their Effect on Benchmark Runtimes
IEEE Transactions on Computers
Fortran RED - A Retargetable Environment for Automatic Data Layout
LCPC '98 Proceedings of the 11th International Workshop on Languages and Compilers for Parallel Computing
EMPS: An Environment for Memory Performance Studies
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
How Well Can Simple Metrics Represent the Performance of HPC Applications?
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
A performance prediction framework for scientific applications
Future Generation Computer Systems
A performance prediction framework for scientific applications
Future Generation Computer Systems
Performance modeling for dynamic algorithm selection
ICCS'03 Proceedings of the 2003 international conference on Computational science
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Optimizing compilers have become an essential component in achieving high levels of performance. Various simple and sophisticated optimizations are implemented at different stages of compilation to yield significant improvements, but little work has been done in characterizing the effectiveness of optimizers, or in understanding where most of this improvement comes from. In this paper we study the performance impact of optimization in the context of our methodology for CPU performance characterization based on the abstract machine model. The model considers all machines to be different implementations of the same high level language abstract machine; in previous research, the model has been used as a basis to analyze machine and benchmark performance. In this paper, we show that our model can be extended to characterize the performance improvement provided by optimizers and to predict the run time of optimized programs, and measure the effectiveness of several compilers in implementing different optimization techniques.