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
Trace-driven memory simulation: a survey
ACM Computing Surveys (CSUR)
Exploiting hardware performance counters with flow and context sensitive profiling
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
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
Cache performance analysis of traversals and random accesses
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Cache miss equations: a compiler framework for analyzing and tuning memory behavior
ACM Transactions on Programming Languages and Systems (TOPLAS)
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
Probabilistic Miss Equations: Evaluating Memory Hierarchy Performance
IEEE Transactions on Computers
ICCS '01 Proceedings of the International Conference on Computational Sciences-Part I
A GSA-based compiler infrastructure to extract parallelism from complex loops
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
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
Miss Rate Prediction across All Program Inputs
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques
Optimizing Program Locality Through CMEs and GAs
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques
Analytical modeling of codes with arbitrary data-dependent conditional structures
Journal of Systems Architecture: the EUROMICRO Journal
Cache behavior modelling for codes involving banded matrices
LCPC'06 Proceedings of the 19th international conference on Languages and compilers for parallel computing
Near-optimal padding for removing conflict misses
LCPC'02 Proceedings of the 15th international conference on Languages and Compilers for Parallel Computing
Optimizing shared cache behavior of chip multiprocessors
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
Cache behavior modelling for codes involving banded matrices
LCPC'06 Proceedings of the 19th international conference on Languages and compilers for parallel computing
Static analysis of the worst-case memory performance for irregular codes with indirections
ACM Transactions on Architecture and Code Optimization (TACO)
Address independent estimation of the boundaries of cache performance
Microprocessors & Microsystems
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The performance of memory hierarchies, in which caches play an essential role, is critical in nowadays general-purpose and embedded computing systems because of the growing memory bottleneck problem. Unfortunately, cache behavior is very unstable and difficult to predict. This is particularly true in the presence of irregular access patterns, which exhibit little locality. Such patterns are very common, for example, in applications in which pointers or compressed sparse matrices give place to indirections. Nevertheless, cache behavior in the presence of irregular access patterns has not been widely studied. In this paper we present an extension of a systematic analytical modeling technique based on PMEs (probabilistic miss equations), previously developed by the authors, that allows the automated analysis of the cache behavior for codes with irregular access patterns resulting from indirections. The model generates very accurate predictions despite the irregularities and has very low computing requirements, being the first model that gathers these desirable characteristics that can automatically analyze this kind of codes. These properties enable this model to help drive compiler optimizations, as we show with an example.