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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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樓主: Blandishment
41#
發(fā)表于 2025-3-28 16:47:13 | 只看該作者
Using Hardware Counters to Predict Vectorizationllelism through the generation of microprocessor vector instructions. Using abstract models and source level information, compilers can identify opportunities for auto-vectorization. However, compilers do not always predict the runtime effects accurately or completely fail to identify vectorization
42#
發(fā)表于 2025-3-28 22:32:06 | 只看該作者
43#
發(fā)表于 2025-3-29 00:48:27 | 只看該作者
44#
發(fā)表于 2025-3-29 06:46:42 | 只看該作者
45#
發(fā)表于 2025-3-29 09:51:07 | 只看該作者
Memory Distance Measurement for Concurrent Programsure data locality and predict memory behavior. Many existing methods on memory distance measurement and analysis consider sequential programs only. With the trend towards concurrent programming, it is necessary to study the impact of memory distance on the performance of concurrent programs. Unfortu
46#
發(fā)表于 2025-3-29 12:13:52 | 只看該作者
47#
發(fā)表于 2025-3-29 19:05:16 | 只看該作者
ADLER: Adaptive Sampling for Precise Monitoringermine the adaptive sampling rate for any application, but also can instrument the code for profiling so that different parts of the application can be sampled at different frequencies. The frequencies are selected to provide enough information without collecting redundant data. ADLER uses performan
48#
發(fā)表于 2025-3-29 20:33:29 | 只看該作者
How Low Can You Go?Moore predicted in 1965 – a trend that many now claim is coming to an end [.]. Whether that rate slows or not, it is no longer the driver; there is already more circuitry than can be continuously powered. The immediate future of parallel language and compiler technology should be less about finding
49#
發(fā)表于 2025-3-30 02:19:04 | 只看該作者
50#
發(fā)表于 2025-3-30 04:24:36 | 只看該作者
Characterizing Performance of Imbalanced Collectives on Hybrid and Task Centric Runtimes for Two-PhaMP) for on-node parallelism with MPI for inter-node parallelism—the so-called “MPI+X”. In important use cases, such as reductions, this hybrid approach can necessitate a scalability-limiting sequence of independent parallel operations, one for each paradigm. For example, MPI+OpenMP typically perform
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