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CGO 2011: Chamonix, France
- Proceedings of the CGO 2011, The 9th International Symposium on Code Generation and Optimization, Chamonix, France, April 2-6, 2011. IEEE Computer Society 2011, ISBN 978-1-61284-356-8
Keynotes
- Erik R. Altman:
The language, optimizer, and tools mess. - Xavier Leroy:
Formally verifying a compiler: Why? How? How far?
Low Level Code Optimization
- Robert Hundt, Easwaran Raman, Martin Thuresson, Neil Vachharajani:
MAO - An extensible micro-architectural optimizer. 1-10 - Tyler Sondag, Hridesh Rajan
:
Phase-based tuning for better utilization of performance-asymmetric multicore processors. 11-20 - Jianjun Li, Chenggang Wu, Wei-Chung Hsu
Dynamic register promotion of stack variables. 21-31 - Timothy M. Jones
Link-time optimization for power efficiency in a tagless instruction cache. 32-41
Speculation and Transactional Memory
- Dhruva R. Chakrabarti, Prithviraj Banerjee, Hans-Juergen Boehm, Pramod G. Joisha, Robert S. Schreiber:
The runtime abort graph and its application to software transactional memory optimization. 42-53 - Edson Borin, Youfeng Wu, Maurício Breternitz Jr.
LAR-CC: Large atomic regions with conditional commits. 54-63 - Ben Hertzberg, Kunle Olukotun:
Runtime automatic speculative parallelization. 64-73 - Mojtaba Mehrara, Scott A. Mahlke:
Dynamically accelerating client-side web applications through decoupled execution. 74-84
Language Support for Optimization
- Jason Ansel, Yee Lok Wong, Cy P. Chan, Marek Olszewski, Alan Edelman, Saman P. Amarasinghe:
Language and compiler support for auto-tuning variable-accuracy algorithms. 85-96 - Qing Yi:
Automated programmable control and parameterization of compiler optimizations. 97-106 - Huimin Cui, Jingling Xue
Extendable pattern-oriented optimization directives. 107-118
Vectorization and Parallelization
- Eunjung Park, Louis-Noël Pouchet, John Cavazos, Albert Cohen, P. Sadayappan:
Predictive modeling in a polyhedral optimization space. 119-129 - Sanghoon Lee, James Tuck
Automatic parallelization of fine-grained meta-functions on a chip multiprocessor. 130-140 - Ralf Karrenberg, Sebastian Hack:
Whole-function vectorization. 141-150 - Dorit Nuzman, Sergei Dyshel, Erven Rohou, Ira Rosen, Kevin Williams, David Yuste, Albert Cohen, Ayal Zaks:
Vapor SIMD: Auto-vectorize once, run everywhere. 151-160
Data Locality
- Jun Liu, Yuanrui Zhang, Wei Ding, Mahmut T. Kandemir:
On-chip cache hierarchy-aware tile scheduling for multicore machines. 161-170 - Xu Liu, John M. Mellor-Crummey
Pinpointing data locality problems using data-centric analysis. 171-180 - Silvius Rus, Raksit Ashok, Xinliang David Li:
Automated locality optimization based on the reuse distance of string operations. 181-190 - Mahmut T. Kandemir, Yuanrui Zhang, Jun Liu, Taylan Yemliha:
Neighborhood-aware data locality optimization for NoC-based multicores. 191-200
Program Safety
- Xinwei Xie, Jingling Xue
Acculock: Accurate and efficient detection of data races. 201-212 - Derek Bruening, Qin Zhao:
Practical memory checking with Dr. Memory. 213-223
Dynamic Compilation
- Chris J. Newburn, Byoungro So, Zhenying Liu, Michael D. McCool, Anwar M. Ghuloum, Stefanus Du Toit, Zhi-Gang Wang, Zhaohui Du, Yongjian Chen, Gansha Wu, Peng Guo, Zhanglin Liu, Dan Zhang:
Intel's Array Building Blocks: A retargetable, dynamic compiler and embedded language. 224-235 - Youfeng Wu, Shiliang Hu, Edson Borin, Cheng Wang:
A HW/SW co-designed heterogeneous multi-core virtual machine for energy-efficient general purpose computing. 236-245 - Hiroshi Inoue, Hiroshige Hayashizaki, Peng Wu, Toshio Nakatani:
A trace-based Java JIT compiler retrofitted from a method-based compiler. 246-256 - Ricardo Nabinger Sanchez, José Nelson Amaral, Duane Szafron, Marius Pirvu, Mark G. Stoodley:
Using machines to learn method-specific compilation strategies. 257-266
Program Analysis
- Rupesh Nasre
Prioritizing constraint evaluation for efficient points-to analysis. 267-276 - Joseph L. Greathouse, Chelsea LeBlanc, Todd M. Austin, Valeria Bertacco:
Highly scalable distributed dataflow analysis. 277-288 - Ben Hardekopf, Calvin Lin:
Flow-sensitive pointer analysis for millions of lines of code. 289-298
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