Cilk: an efficient multithreaded runtime system
PPOPP '95 Proceedings of the fifth ACM SIGPLAN symposium on Principles and practice of parallel programming
X10: an object-oriented approach to non-uniform cluster computing
OOPSLA '05 Proceedings of the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Concurrent clustered programming
CONCUR 2005 - Concurrency Theory
Parallel Programmability and the Chapel Language
International Journal of High Performance Computing Applications
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Scheduling multithreaded computations by work stealing
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Flexible architectural support for fine-grain scheduling
Proceedings of the fifteenth edition of ASPLOS on Architectural support for programming languages and operating systems
The D Programming Language
Real time contingency analysis for power grids
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part II
Large-Scale Transient Stability Simulation of Electrical Power Systems on Parallel GPUs
IEEE Transactions on Parallel and Distributed Systems
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Due to recent trends of expansion and deregulation in power systems, the stress level of power systems has increased which has highlighted the importance of conducting stability analysis. Further, due to increasing emphasis on analyzing N -- k contingency, the number of contingencies which are required to be analyzed has greatly increased. To address this challenge, researchers have used parallel computing resources, however, in absence of efficient load-balanced scheduling, parallelization leads to wastage of computation resources. In this paper, we present an approach to parallelize power system contingency analysis using X10 language. We discuss the features of X10 which enable us to achieve high performance gains. Our approach is evaluated using a large 13029-bus power systems. We parallelize contingency analysis over 2, 4, 8 and 16 threads and use efficient work-stealing algorithm to achieve load-balancing. The results have shown that our approach scales effectively with the number of cores and provides large computational gains. Also, it outperforms a conventional scheduling technique, namely master-slave scheduling.