Results 191 to 200 of about 21,831,698 (267)

Tracking polygenic adaptation: phenotypic stasis after rapid adaptation in large populations of Drosophila

Ramirez-Lanzas C, Dolezal M, Signor S, Schlötterer C, Barghi N.   +4 more
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High-Level Stream and Data Parallelism in C++ for GPUs

Brazilian Symposium on Programming Languages, 2022
GPUs are massively parallel processors that allow solving problems that are not viable to traditional processors like CPUs. However, implementing applications for GPUs is challenging to programmers as it requires parallel programming to efficiently ...
Dinei A. Rockenbach, Júnior Löff, G. Araujo, Dalvan Griebler, L. G. Fernandes   +4 more
semanticscholar   +1 more source

Distributed Model Training Based on Data Parallelism in Edge Computing-Enabled Elastic Optical Networks

IEEE Communications Letters, 2021
The emergence of edge computing provides an effective solution to execute distributed model training (DMT). The deployment of training data among edge nodes affects the training efficiency and network resource usage.
Yajie Li, Zebin Zeng, Jun Li, Boyuan Yan, Yongli Zhao, Jie Zhang   +5 more
semanticscholar   +1 more source

High-Level Stream and Data Parallelism in C++ for Multi-Cores

Brazilian Symposium on Programming Languages, 2021
Stream processing applications have seen an increasing demand with the increased availability of sensors, IoT devices, and user data. Modern systems can generate millions of data items per day that require to be processed timely. To deal with this demand,
Junior Loff, Renato B. Hoffmann, Dalvan Griebler, L. G. Fernandes   +3 more
semanticscholar   +1 more source

Data Parallelism

The Art of Multiprocessor Programming, 1993
M. Herlihy, N. Shavit, Victor Luchangco, Michael Spear   +3 more
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Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations

Proceedings of the VLDB Endowment, 2022
Systems performing large data-parallel computations, including online analytical processing (OLAP) systems like Druid and search engines like Elasticsearch, are increasingly being used for business-critical real-time applications where providing low query latency is paramount.
Nirvik Baruah, Peter Kraft, Fiodar Kazhamiaka, Peter Bailis, Matei Zaharia   +4 more
openaire   +1 more source

How Reduced Data Precision and Degree of Parallelism Impact the Reliability of Convolutional Neural Networks on FPGAs

IEEE Transactions on Nuclear Science, 2021
Convolutional neural networks (CNNs) are becoming attractive alternatives to traditional image-processing algorithms in self-driving vehicles for automotive, military, and aerospace applications.
F. Libano, P. Rech, B. Neuman, J. Leavitt, Michael Wirthlin, J. Brunhaver   +5 more
semanticscholar   +1 more source

Incremental flattening for nested data parallelism

ACM SIGPLAN Symposium on Principles & Practice of Parallel Programming, 2019
Compilation techniques for nested-parallel applications that can adapt to hardware and dataset characteristics are vital for unlocking the power of modern hardware.
Troels Henriksen, Frederik Thorøe, M. Elsman, C. Oancea   +3 more
semanticscholar   +1 more source

Measurement-Based Evaluation of Data-Parallelism for OpenCV Feature-Detection Algorithms

Annual International Computer Software and Applications Conference, 2018
We investigate the effects on the execution time, shared cache usage and speed-up gains when using datapartitioned parallelism for the feature detection algorithms available in the OpenCV library.
Jakob Danielsson, Marcus Jägemar, M. Behnam, Mikael Sjödin, T. Seceleanu   +4 more
semanticscholar   +1 more source