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Adapting Convergent Scheduling Using Machine-Learning
[chapter]
2004
Lecture Notes in Computer Science
Convergent scheduling is a general framework for instruction scheduling and cluster assignment for parallel, clustered architectures. A convergent scheduler is composed of many independent passes, each of which implements a specific compiler heuristic. Each of the passes shares a common interface, which allows them to be run multiple times, and in any order. Because of this, a convergent scheduler is presented with a vast number of legal pass orderings. In this work, we use machine-learning
doi:10.1007/978-3-540-24644-2_2
fatcat:mutyd35akbbizam7n4i6lgbuf4