By Xipeng Shen, Frank Mueller, James Tuck
This ebook constitutes the completely refereed post-conference court cases of the twenty eighth foreign Workshop on Languages and Compilers for Parallel Computing, LCPC 2015, held in Raleigh, NC, united states, in September 2015.
The 19 revised complete papers have been rigorously reviewed and chosen from forty four submissions. The papers are equipped in topical sections on programming types, optimizing framework, parallelizing compiler, verbal exchange and locality, parallel functions and knowledge constructions, and correctness and reliability.
Read or Download Languages and Compilers for Parallel Computing: 28th International Workshop, LCPC 2015, Raleigh, NC, USA, September 9-11, 2015, Revised Selected Papers (Lecture Notes in Computer Science) PDF
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Extra resources for Languages and Compilers for Parallel Computing: 28th International Workshop, LCPC 2015, Raleigh, NC, USA, September 9-11, 2015, Revised Selected Papers (Lecture Notes in Computer Science)
When n is large or k is small the performance of this approach is limited by the locking overhead. On the other hand, when n is small or k is large the scalability is limited by coarse-grained locking. In contrast, as we will see, in CA trees k is dynamic and adapted at runtime to provide a good trade-oﬀ between scalability and locking overhead. The Leaplist  is a concurrent ordered set implementation with native support for range operations. Leaplist is based on a skip list data structure with fat nodes that can contain up to k elements.
Both ﬁles consist of two parts as meta-data and computation-space objects. 1 Checkpointing DISC model automates application-level checkpointing, alleviating the need for expensive system-level checkpointing that is normally used for programming models like MPI. Like any checkpointing-based approach, we assume the existence of a persistent storage where the checkpoint ﬁles can be written into. C. Kurt et al. Two important questions for application-level checkpointing are: (1) when should checkpoints be taken, and (2) what data structures will be needed to restart the computation in case of a failure, and therefore, need to be checkpointed.
In: Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2010, pp. 1–11. IEEE Computer Society, Washington, DC (2010) 18. : ACR: Automatic checkpoint/restart for soft and hard error protection. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC 2013, pp. 7:1–7:12. ACM, New York (2013) 19. : Algorithm-based diskless checkpointing for fault tolerant matrix operations.