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
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
A quantitative analysis of loop nest locality
Proceedings of the seventh international conference on Architectural support for programming languages and operating systems
Trace-driven memory simulation: a survey
ACM Computing Surveys (CSUR)
Modeling set associative caches behavior for irregular computations
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Analytical Modeling of Set-Associative Cache Behavior
IEEE Transactions on Computers
Cache miss equations: a compiler framework for analyzing and tuning memory behavior
ACM Transactions on Programming Languages and Systems (TOPLAS)
Symbolic Cache Analysis for Real-Time Systems
Real-Time Systems - Special issue on worst-case execution-time analysis
Performance analysis using the MIPS R10000 performance counters
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Exact analysis of the cache behavior of nested loops
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Parallel Programming with Polaris
Computer
Measuring Cache and TLB Performance and Their Effect on Benchmark Runtimes
IEEE Transactions on Computers
On Estimating and Enhancing Cache Effectiveness
Proceedings of the Fourth International Workshop on Languages and Compilers for Parallel Computing
A Comparison of Compiler Tiling Algorithms
CC '99 Proceedings of the 8th International Conference on Compiler Construction, Held as Part of the European Joint Conferences on the Theory and Practice of Software, ETAPS'99
Automatic Analytical Modeling for the Estimation of Cache Misses
PACT '99 Proceedings of the 1999 International Conference on Parallel Architectures and Compilation Techniques
Let's Study Whole-Program Cache Behaviour Analytically
HPCA '02 Proceedings of the 8th International Symposium on High-Performance Computer Architecture
Compile-time performance prediction of scientific programs
Compile-time performance prediction of scientific programs
Generating cache hints for improved program efficiency
Journal of Systems Architecture: the EUROMICRO Journal
Journal of Computational Physics
Analytical modeling of codes with arbitrary data-dependent conditional structures
Journal of Systems Architecture: the EUROMICRO Journal
Cache-aware iteration space partitioning
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
Automatic analysis for managing and optimizing performance-code quality
Proceedings of the 2008 workshop on Static analysis
Cache-aware partitioning of multi-dimensional iteration spaces
SYSTOR '09 Proceedings of SYSTOR 2009: The Israeli Experimental Systems Conference
Address independent estimation of the boundaries of cache performance
Microprocessors & Microsystems
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The study and understanding of memory hierarchy behavior is essential, as it is critical to current systems performance. The design of optimising environments and compilers, which allow the guidance of program transformation applications in order to improve cache performance with as little user intervention as possible, is particularly interesting. In this paper we introduce a fast analytical modelling technique that is suitable for arbitrary set-associative caches with LRU replacement policy, which overcomes weak points of other approaches found in the literature. The model was integrated in the Polaris parallelizing compiler, to allow automated analysis of loop-oriented scientific codes and to drive code optimizations. Results from detailed validations using well-known benchmarks show that the model predictions are usually very accurate and that the code optimizations proposed by the model are always, or nearly always, optimal.