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  • May 27, 2010: Add a support tab for user feedback and suggestions.
  • May 27, 2010: We finally got the http download links ready :)
  • May 26, 2010: Yang's PDLI'10 paper is available now.

While iterative optimization has become a popular compiler optimization approach, it is based on a premise which has never been truly evaluated: that it is possible to learn the best compiler optimizations across data sets.

Up to now, most iterative optimization studies find the best optimizations through repeated runs on the same data set. Only a handful of studies have attempted to exercise iterative optimization on a few tens of data sets.

We try to truly put iterative compilation to the test for the first time by evaluating its effectiveness across a large number of data sets. We therefore compose KDataSets, a data set suite with 1000 data sets for 32 programs, which we release to the public. 

 

Please cite the following paper if you use KDataSets for a publication.

  • Y. Chen, Y. Huang, L. Eeckhout, G. Fursin, L. Peng, O. Temam, and C. Wu, "Evaluating Iterative Optimization Across 1000 Data Sets," In Proceedings of the ACM SIGPLAN 2010 Conference on Programming Language Design and Implementation (PLDI'10), Toronto, Canada: 2010.  [pdf] [bib]