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Titlebook: Languages and Compilers for Parallel Computing; 30th International W Lawrence Rauchwerger Conference proceedings 2019 Springer Nature Switz

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书目名称Languages and Compilers for Parallel Computing
副标题30th International W
编辑Lawrence Rauchwerger
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Languages and Compilers for Parallel Computing; 30th International W Lawrence Rauchwerger Conference proceedings 2019 Springer Nature Switz
描述.This book constitutes the proceedings of the 30th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2017, held in College Station, TX, USA, in October 2017... The 17 full papers presented together with abstracts of 5 keynote talks, 11 invited speakers and 4 poster papers in this volume were carefully reviewed and selected from 26 submissions. LCPC encourages submissions that go outside its original scope of scientific computing to diverse areas that are enable or enhanced by the power of parallel systems such as mobile computing, big data, relevant aspects of machine learning, data centers, cognitive computing, etc. LCPC strongly encourages personal interaction and technical discussions along the initial material..
出版日期Conference proceedings 2019
关键词compilers; computer architecture; concurrency; concurrency control; databases; distributed computing; hard
版次1
doihttps://doi.org/10.1007/978-3-030-35225-7
isbn_softcover978-3-030-35224-0
isbn_ebook978-3-030-35225-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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978-3-030-35224-0Springer Nature Switzerland AG 2019
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Lock-Free Transactional Adjacency Listee Transactional Transformation (LFTT) methodology to efficiently enable transactional execution. In our performance evaluation, our lock-free transactional adjacency list achieves an average of 50% speedup over a transactional boosting implementation.
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Polyhedral Compilation Support for C++ Features: A Case Study with CPPTRAJe show how we can rewrite the computation to affine form suitable for CUDA-CHiLL, and also describe how to support the original C++ code in a polyhedral framework. The result of this effort yielded speedups over serial ranging from 3. to 278. on the six optimized kernels, and up to 100. over serial and 10. speedup over OpenMP.
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