Athapascan-1: On-line building data flow graph in a parallel language

In order to achieve practical efficient execution on a parallel architecture, a knowledge of the data dependencies related to the application appears as the key point for building an efficient schedule. By restricting accesses in shared memory, we show that such a data dependency graph can be computed on-line on a distributed architecture. The overhead introduced is bounded with respect to the parallelism expressed by the user: each basic computation corresponds to a user-defined task, each data-dependency to a user-defined data structure. We introduce a language named Athapascan-1 that allows to build a graph of dependencies from a strong typing of shared memory accesses. We detail compilation and implementation of the language. Besides, the performance of a code (parallel time, communication and arithmetic works, memory space) are defined from a cost model without the need of a machine model. We exhibit efficient scheduling with respect to these costs on theoretical machine models