Integer and combinatorial optimization
Integer and combinatorial optimization
The cache performance and optimizations of blocked algorithms
ASPLOS IV Proceedings of the fourth international conference on Architectural support for programming languages and operating systems
Optimizing for parallelism and data locality
ICS '92 Proceedings of the 6th international conference on Supercomputing
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
SUIF: an infrastructure for research on parallelizing and optimizing compilers
ACM SIGPLAN Notices
An optimizing Fortran D compiler for MIMD distributed-memory machines
An optimizing Fortran D compiler for MIMD distributed-memory machines
Compiling for numa parallel machines
Compiling for numa parallel machines
Combining loop transformations considering caches and scheduling
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Data-centric multi-level blocking
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Advanced compiler design and implementation
Advanced compiler design and implementation
Locality optimizations for multi-level caches
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
OCEANS: Optimizing Compilers for Embedded Applications
Euro-Par '97 Proceedings of the Third International Euro-Par Conference on Parallel Processing
Influence of Loop Optimizations on Energy Consumption of Multi-bank Memory Systems
CC '02 Proceedings of the 11th International Conference on Compiler Construction
A Quantitative analysis of disk drive power management in portable computers
WTEC'94 Proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference
Thwarting the power-hungry disk
WTEC'94 Proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference
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One of the most important factors that determine performance of data-intensive applications is data locality. A program with high data locality makes better use of fast, on-chip memories and can avoid large main memory latencies. Although previous compiler research investigated numerous techniques for enhancing locality, we lack of formal techniques, against which the existing heuristics can be compared. Motivated by this observation, this paper presents a fresh look at locality optimization based on integer linear programming (ILP). We formulate the conditions for data locality, and present a system of constraints whose solution gives optimal computation re-ordering and data-to-memory assignment under our objective function and cost model. Our experimental results using three data-intensive applications clearly indicate that the ILP-based approach generates very good results and outperforms a previously proposed heuristic solution to locality.