Languages and Compilers for Parallel Computing
32nd International Workshop, LCPC 2019, Atlanta, GA, USA, October 22-24, 2019, Revised Selected Papers
(Sprache: Englisch)
This book constitutes the thoroughly refereed post-conference proceedings of the 32nd International Workshop on Languages and Compilers for Parallel Computing, LCPC 2019, held in Atlanta, GA, USA, in October 2019.
The 8 revised full papers and 3...
The 8 revised full papers and 3...
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Klappentext zu „Languages and Compilers for Parallel Computing “
This book constitutes the thoroughly refereed post-conference proceedings of the 32nd International Workshop on Languages and Compilers for Parallel Computing, LCPC 2019, held in Atlanta, GA, USA, in October 2019.The 8 revised full papers and 3 revised short papers were carefully reviewed and selected from 17 submissions. The scope of the workshop includes advances in programming systems for current domains and platforms, e.g., scientific computing, batch/ streaming/ real-time data analytics, machine learning, cognitive computing, heterogeneous/ reconfigurable computing, mobile computing, cloud computing, IoT, as well as forward-looking computing domains such as analog and quantum computing.
Inhaltsverzeichnis zu „Languages and Compilers for Parallel Computing “
Performance of Static and Dynamic Task Scheduling for Real-Time Engine Control System on Embedded Multicore Processor.- PostSLP: Cross-Region Vectorization of Fully or Partially Vectorized Code.- FLARE: Flexibly Sharing Commodity GPUs to Enforce QoS and Improve Utilization.- Foundations of consistency types for a higher-order distributed language.- Common Subexpression Convergence: A New Code Optimization for SIMT processors.- Using Performance Event Profiles to Deduce an Execution Model of MATLAB with Just-In-Time Compilation.- CLAM: Compiler Leasing of Accelerator Memory.- Abstractions for Polyhedral Topology-Aware Tasking.- SWIRL++: Evaluating Performance Models to Guide Code Transformation in Convolutional Neural Networks.- A Structured Grid Solver with Polyhedral+Dataflow Representation.- CubeGen: Code Generation for Accelerated GEMM-based Convolution with Tiling.
Bibliographische Angaben
- 2021, 1st ed. 2021, XII, 165 Seiten, 47 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Santosh Pande, Vivek Sarkar
- Verlag: Springer, Berlin
- ISBN-10: 3030727882
- ISBN-13: 9783030727888
Sprache:
Englisch
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