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As illustrated by the emergence of a class of new languages and runtimes, itis expected that a large portion of the programs to run on extreme scalecomputers will need to be written as graphs of event-driven tasks (EDTs). EDTruntime systems, which schedule such collections of tasks, enable moreconcurrency than traditional runtimes by reducing the amount of inter-tasksynchronization, improving dynamic load balancing and making more operationsasynchronous.  We present an efficient technique to generate such task graphs from apolyhedral representation of a program, both in terms of compilation time andasymptotic execution time. Task dependences become materialized in differentforms, depending upon the synchronization model available with the targetedruntime.  We explore the different ways of programming EDTs using each synchronizationmodel, and identify important sources of overhead associated with them. Weevaluate these programming schemes according to the cost they entail in termsof sequential start-up, in-flight task management, space used forsynchronization objects, and garbage collection of these objects.  While our implementation and evaluation take place in a polyhedral compiler,the presented overhead cost analysis is useful in the more general context ofautomatic code generation.

Efficient Compilation to Event-Driven Task Programs