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Iterative optimization in the polyhedral model: Part II, multidimensional time (2008)
| Content Provider | CiteSeerX |
|---|---|
| Author | Cavazos, John Cohen, Albert Bastoul, Cédric Pouchet, Louis-Noël |
| Description | In PLDI ’08: Proceedings of the 2008 ACM SIGPLAN Conference on Programming Language Design and Implementation |
| Abstract | High-level loop optimizations are necessary to achieve good performance over a wide variety of processors. Their performance impact can be significant because they involve in-depth program transformations that aim to sustain a balanced workload over the computational, storage, and communication resources of the target architecture. Therefore, it is mandatory that the compiler accurately models the target architecture as well as the effects of complex code restructuring. However, because optimizing compilers (1) use simplistic performance models that abstract away many of the complexities of modern architectures, (2) rely on inaccurate dependence analysis, and (3) lack frameworks to express complex interactions of transformation sequences, they typically uncover only a fraction of the peak performance available on many applications. We propose a |
| File Format | |
| Publisher Date | 2008-01-01 |
| Access Restriction | Open |
| Subject Keyword | Complex Interaction Transformation Sequence Performance Impact Iterative Optimization High-level Loop Optimization Wide Variety Polyhedral Model Target Architecture Lack Framework Many Application Complex Code Restructuring Balanced Workload Modern Architecture Communication Resource Part Ii Inaccurate Dependence Analysis Use Simplistic Performance Model Peak Performance In-depth Program Transformation Multidimensional Time |
| Content Type | Text |
| Resource Type | Proceeding |
