Parallel Programmability and the Chapel Language

By B. Chamberlain, D. Callahan, H. Zima. The international journal of high performance computing applications, 2007

1,020 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

HPX: A Task Based Programming Model in a Global Address Space (2014, background): “The most prominent examples are Chapel [11] and X10 [13] which represent the PGAS languages.”
Efficient Memory Disaggregation with Infiniswap (2017, methodology): “To avoid coherence costs, the HPC community has favored the Partitioned Global Address Space (PGAS) model [30, 34] instead.”
Legion: Expressing locality and independence with logical regions (2012, background): “Chapel has several concepts to support the expression of locality [12].”
Julia: A Fresh Approach to Numerical Computing (2014, methodology): “us out of our research boundaries. The rst decade of the 21st century saw a boost in such research with the High Productivity Computing Systems DARPA funded projects into the languages such as Chapel [6, 7], Fortress [37, 1] and X10 [34, 8]. Also contemporaneous has been a growing acceptance of Pyth”
Halide (2017, background): “6 Popular today, CUDA and OpenCL expose an imperative, single program-multiple data programming model which can target both GPUs and multicore CPUs with SIMD units.”
Scalable work stealing (2009, methodology): “HPCS languages such as X10 [9], Chapel [8] and”
Supporting Very Large Models using Automatic Dataflow Graph Partitioning (2018, background): “In the low-level, ZPL [64], Chapel [65] and Unified Parallel C [66] are parallel language supports.”