Heterogeneous computing with OpenCL 2.0

Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in Open...

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Detalles Bibliográficos
Autores principales: Kaeli, David R, Mistry, Perhaad, Schaa, Dana, Zhang, Dong Ping
Lenguaje:eng
Publicado: Morgan Kaufmann 2015
Materias:
Computing and Computers
Acceso en línea:http://cds.cern.ch/record/2032027
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author Kaeli, David R
Mistry, Perhaad
Schaa, Dana
Zhang, Dong Ping
author_facet Kaeli, David R
Mistry, Perhaad
Schaa, Dana
Zhang, Dong Ping
author_sort Kaeli, David R
collection CERN
description Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources Dynamic parallelism which reduces processor load and avoids bottlenecks Improved imaging support and integration with OpenGL  Designed to work on multiple platfor
id cern-2032027
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
publisher Morgan Kaufmann
record_format invenio
spelling cern-20320272021-04-21T20:10:25Zhttp://cds.cern.ch/record/2032027engKaeli, David RMistry, PerhaadSchaa, DanaZhang, Dong PingHeterogeneous computing with OpenCL 2.0Computing and ComputersHeterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources Dynamic parallelism which reduces processor load and avoids bottlenecks Improved imaging support and integration with OpenGL  Designed to work on multiple platforMorgan Kaufmannoai:cds.cern.ch:20320272015
spellingShingle Computing and Computers
Kaeli, David R
Mistry, Perhaad
Schaa, Dana
Zhang, Dong Ping
Heterogeneous computing with OpenCL 2.0
title Heterogeneous computing with OpenCL 2.0
title_full Heterogeneous computing with OpenCL 2.0
title_fullStr Heterogeneous computing with OpenCL 2.0
title_full_unstemmed Heterogeneous computing with OpenCL 2.0
title_short Heterogeneous computing with OpenCL 2.0
title_sort heterogeneous computing with opencl 2.0
topic Computing and Computers
url http://cds.cern.ch/record/2032027
work_keys_str_mv AT kaelidavidr heterogeneouscomputingwithopencl20
AT mistryperhaad heterogeneouscomputingwithopencl20
AT schaadana heterogeneouscomputingwithopencl20
AT zhangdongping heterogeneouscomputingwithopencl20

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