Cargando…
Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel FPGA
<!--HTML-->AI and deep learning have been widely used and shown great promise in recent scientific research activities. Deep neural network (DNN) models are proven to be highly efficient in big data analytic application for scientific experiments. However, traditional CPU-based sequential comp...
Autor principal: | Vallecorsa, Sofia |
---|---|
Lenguaje: | eng |
Publicado: |
2019
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2691452 |
Ejemplares similares
-
Accelerate Scientific Deep Learning Models on Heterogeneous Computing Platform with FPGA
por: Jiang, Chao, et al.
Publicado: (2020) -
Intel: High Throughput Computing Collaboration: A CERN openlab / Intel collaboration
por: NEUFELD, Niko
Publicado: (2015) -
Performance and Scalability Analysis of CNN-based Deep Learning Inference in the Intel Distribution of OpenVINO Toolkit
por: Meyerov, Iosif
Publicado: (2019) -
Next generation Intel MPI product for next generation systems. The latest Intel MPI features and optimization techniques
por: Oertel, Klaus-Dieter
Publicado: (2019) -
Natural Language Processing with Intel Quantum Simulator
por: Doyle, Myles
Publicado: (2019)