|
|
|
|
|
Mikhail Alexandrovich Padalko, Yuriy Andreevich Shevchenko, Vitalii Yurievich Kapitan and Konstantin Valentinovich Nefedev
A scheme for parallel computation of the two-dimensional Edwards?Anderson model based on the transfer matrix approach is proposed. Free boundary conditions are considered. The method may find application in calculations related to spin glasses and in qua...
ver más
|
|
|
|
|
|
|
|
|
Jin Cao, Bo Li, Mengni Fan and Huiyu Liu
Deep neural network-based computer vision applications have exploded and are widely used in intelligent services for IoT devices. Due to the computationally intensive nature of DNNs, the deployment and execution of intelligent applications in smart scena...
ver más
|
|
|
|
|
|
|
|
|
Yan Zeng, Jiyang Wu, Jilin Zhang, Yongjian Ren and Yunquan Zhang
Deep learning, with increasingly large datasets and complex neural networks, is widely used in computer vision and natural language processing. A resulting trend is to split and train large-scale neural network models across multiple devices in parallel,...
ver más
|
|
|
|
|
|
|
|
|
David Blinder and Peter Schelkens
Computer-generated holography (CGH) is a notoriously difficult computation problem, simulating numerical diffraction, where every scene point can affect every hologram pixel. To tackle this challenge, specialized software instructions and hardware soluti...
ver más
|
|
|
|
|
|
|
|
|
Ralf Stemmer, Hai-Dang Vu, Sébastien Le Nours, Kim Grüttner, Sébastien Pillement and Wolfgang Nebel
Fast yet accurate performance and timing prediction of complex parallel data flow applications on multi-processor systems remains a very difficult discipline. The reason for it comes from the complexity of the data flow applications w.r.t. data dependent...
ver más
|
|
|
|