Efficient Representation Scheme for Multidimensional Array Operations
IEEE Transactions on Computers
Probabilistic Miss Equations: Evaluating Memory Hierarchy Performance
IEEE Transactions on Computers
ICCS '01 Proceedings of the International Conference on Computational Sciences-Part I
Data cache locking for higher program predictability
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A comparison of empirical and model-driven optimization
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
IEEE Transactions on Parallel and Distributed Systems
A fast and accurate framework to analyze and optimize cache memory behavior
ACM Transactions on Programming Languages and Systems (TOPLAS)
Efficient and Accurate Analytical Modeling of Whole-Program Data Cache Behavior
IEEE Transactions on Computers
A compiler tool to predict memory hierarchy performance of scientific codes
Parallel Computing
Predicting Cache Space Contention in Utility Computing Servers
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
Statistical Models for Empirical Search-Based Performance Tuning
International Journal of High Performance Computing Applications
CMP cache performance projection: accessibility vs. capacity
ACM SIGARCH Computer Architecture News
Loop Optimization using Hierarchical Compilation and Kernel Decomposition
Proceedings of the International Symposium on Code Generation and Optimization
International Journal of Computational Science and Engineering
Automatic analysis for managing and optimizing performance-code quality
Proceedings of the 2008 workshop on Static analysis
Iterative compilation with kernel exploration
LCPC'06 Proceedings of the 19th international conference on Languages and compilers for parallel computing
Tightening the bounds on feasible preemptions
ACM Transactions on Embedded Computing Systems (TECS)
SEEP: exploiting symbolic execution for energy-aware programming
HotPower '11 Proceedings of the 4th Workshop on Power-Aware Computing and Systems
SEEP: exploiting symbolic execution for energy-aware programming
ACM SIGOPS Operating Systems Review
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Caches play a very important role in the performance of modern computer systems due to the gap between the memory and the processor speed. Among the methods for studying their behavior, the most widely used by now has been trace-driven simulation. Nevertheless, analytical modeling gives more information and requires smaller computation times that allow it to be used in the compilation step to drive automatic optimizations on the code. The traditional drawback of analytical modeling has been its limited precision and the lack of techniques to apply it systematically without user intervention. In this work we present a methodology to build analytical models for codes with regular access patterns. These models can be applied to caches with an arbitrary size, line size and associativity. Their validation through simulations using typical scientific code fragments has proved a good degree of accuracy.