C
Cy Chan
Researcher at Lawrence Berkeley National Laboratory
Publications - 38
Citations - 1380
Cy Chan is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Computer science & Speedup. The author has an hindex of 14, co-authored 34 publications receiving 1187 citations. Previous affiliations of Cy Chan include Massachusetts Institute of Technology.
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Proceedings ArticleDOI
PetaBricks: a language and compiler for algorithmic choice
TL;DR: PetaBricks is presented, a new implicitly parallel language and compiler where having multiple implementations of multiple algorithms to solve a problem is the natural way of programming and makes algorithmic choice a first class construct of the language.
Proceedings ArticleDOI
An auto-tuning framework for parallel multicore stencil computations
TL;DR: In this article, the authors present a stencil auto-tuning framework that significantly advances programmer productivity by automatically converting a straightforward sequential Fortran 95 stencil expression into tuned parallel implementations in Fortran, C, or CUDA.
Journal ArticleDOI
AMReX: a framework for block-structured adaptive mesh refinement
Weiqun Zhang,Ann S. Almgren,V E Beckner,John B. Bell,Johannes Blaschke,Cy Chan,Marcus S. Day,Brian Friesen,Kevin Gott,Daniel Graves,Maximilian Katz,Andrew C. Myers,Tan Nguyen,Andrew Nonaka,Michele Rosso,Samuel Williams,Michael Zingale +16 more
TL;DR: Author(s): Zhang, Weiqun; Almgren, Ann; Beckner, Vince; Bell, John; Blaschke, Johannes; Chan, Cy; Day, Marcus; Friesen, Brian; Gott, Kevin; Graves, Daniel; Katz, Max; Myers, Andrew; Nguyen, Tan; Nonaka, Andrew ; Rosso, Michele; Williams, Samuel; Zingale, Michael
Proceedings ArticleDOI
Language and compiler support for auto-tuning variable-accuracy algorithms
TL;DR: Language extensions are proposed that expose trade-offs between time and accuracy to the compiler and a structured genetic tuning algorithm to search the space of candidate algorithms and accuracies in the presence of recursion and sub-calls to other variable accuracy code.
Proceedings ArticleDOI
Siblingrivalry: online autotuning through local competitions
Jason Ansel,Maciej Pacula,Yee Lok Wong,Cy Chan,Marek Olszewski,Una-May O'Reilly,Saman Amarasinghe +6 more
TL;DR: SiblingRivalry is presented, a new model for always-on online autotuning that allows parallel programs to continuously adapt and optimize themselves to their environment and often outperform the original algorithm that uses the entire system.