The Constellation Project

unifying software and hardware for performant and frictionless heterogeneous parallelism



Parallelism should be frictionless, allowing every developer to start with the assumption of parallelism instead of being forced to take it up once performance demands it. Considerable progress has been made in achieving this vision on the language and training front; it has been demonstrated that sophomores can learn basic data structures and algorithms in a “parallel first” model enabled by a high-level parallel language. However, achieving both high productivity and high performance on current and future heterogeneous systems requires innovation throughout the hardware/software stack. This project brings two distinct perspectives to this problem: the “theory down” approach, focusing on high-level parallel languages and the theory and practice of achieving provable performance bounds within them; and the “architecture up” approach, focusing on rethinking abstractions at the architectural, operating system, runtime, and compiler levels to optimize raw performance. Constellation has roots partially in the Interweaving Project.


Faculty and Research Scientists#

Ph.D. Students and Postdocs#

M.S. Students#

Undergrad Students and REU Students#





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The Constellation Project is made possible by support from the National Science Foundation via awards CCF-2119069, CCF-2119352, CCF-2028851, CCF-2028921 and CCF-2028958, and via the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration, by the U.S. Department of Energy, Office of Science, under Contract DE-AC02- 06CH11357. David Krasowska and Kirill Nagaitsev are Department of Energy Computational Science Graduate Fellows.