On parallel block algorithms for exact triangularizations
Parallel Computing
Automatic re-scheduling of dependencies in a RPC-based grid
Proceedings of the 18th annual international conference on Supercomputing
Re-scheduling invocations of services for RPC grids
Computer Languages, Systems and Structures
Adaptive loops with kaapi on multicore and grid: applications in symmetric cryptography
Proceedings of the 2007 international workshop on Parallel symbolic computation
Fine Grain Distributed Implementation of a Dataflow Language with Provable Performances
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Scheduling dynamically spawned processes in MPI-2
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Anahy: a programming environment for cluster computing
VECPAR'06 Proceedings of the 7th international conference on High performance computing for computational science
Adaptive encoding of multimedia streams on MPSoC
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
A checkpoint/recovery model for heterogeneous dataflow computations using work-stealing
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Improving performance of adaptive component-based dataflow middleware
Parallel Computing
Impact of over-decomposition on coordinated checkpoint/rollback protocol
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing - Volume 2
LIBKOMP, an efficient openMP runtime system for both fork-join and data flow paradigms
IWOMP'12 Proceedings of the 8th international conference on OpenMP in a Heterogeneous World
Æminium: A Permission-Based Concurrent-by-Default Programming Language Approach
ACM Transactions on Programming Languages and Systems (TOPLAS)
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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 built 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.