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Package: sqldeveloper-package
Description-md5: 7fabc3fa20df18b43a17959dd66a466c
Description-en: Oracle SQL Developer Debian package builder
 This utility makes it possible to build a Debian package of Oracle SQL
 Developer. The Oracle SQL Developer program is governed by the copyright
 holder (Oracle USA, Inc.), so you may be limited as to what you can do with
 the resulting package (i.e. no redistribution, etc). This utility will simply
 help you create the Debian package, it is your responsibility to use the
 resulting package acordingly with the OTN license, a copy of which is included
 in the created package, that you must agree on when downloading the source.
 .
 This utility will require you to download the architecture independent archive
 from <http://www.oracle.com/technetwork/developer-tools/sql-developer>,
 identified as "Oracle SQL Developer for other platforms", "Oracle SQL
 Developer for Multiple Platforms" or "Oracle SQL Developer for Linux and Unix"
 (depending on which version you  are building), to create the Debian package
 from.

Package: libsocl-contrib-1.2-0
Description-md5: 607f8f9648f71dbaceaaeeaa04f4c6e8
Description-en: Task scheduler for heterogeneous multicore machines
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains an OpenCL-compatible library interface to StarPU.

Package: libstarpu-contrib-1.2-0
Description-md5: 6e4e8db53b47fb942bef212def2a1e22
Description-en: Task scheduler for heterogeneous multicore machines
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains the main StarPU library

Package: libstarpu-contrib-dev
Description-md5: 967c103c8b3cf3662ee291f422fa5be6
Description-en: Task scheduler for heterogeneous multicore machines - dev
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains development headers and libraries.

Package: libstarpu-contribfft-1.2-0
Description-md5: a1e84fcd5b7aa1a04d6c8089b0a0ecef
Description-en: Task scheduler for heterogeneous multicore machines
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains a hybrid CPU+GPU FFT library.

Package: libstarpu-contribmpi-1.2-0
Description-md5: a7034f989f1ae2e40b4db1b5bb58bd47
Description-en: Task scheduler for heterogeneous multicore machines
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains MPI extensions for StarPU.

Package: starpu-contrib-examples
Description-md5: 601fd3c318d53962421cdbdd364f312b
Description-en: Task scheduler for heterogeneous multicore machines - exs
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains application examples.

Package: starpu-contrib-tools
Description-md5: eb2ba87d4cd88833bc91b0cf6b977279
Description-en: Task scheduler for heterogeneous multicore machines - tools
 StarPU is a runtime system that offers support for heterogeneous
 multicore machines. While many efforts are devoted to design efficient
 computation kernels for those architectures (e.g. to implement BLAS
 kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
 offloading such kernels (and implementing data coherency across
 the machine), but it also makes sure the kernels are executed as
 efficiently as possible.
 .
 This package contains StarPU tools.
.
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Package: caffe-cuda
Description-md5: b93e8b129977d3d95bfdb17281d84865
Description-en: Fast, open framework for Deep Learning (Meta)
 Caffe is a deep learning framework made with expression, speed,
 and modularity in mind. It is developed by the Berkeley AI Research
 Lab (BAIR) and community contributors.
 .
 This metapackage pulls CUDA version of caffe:
  * caffe-tools-cuda
  * libcaffe-cuda*
  * python3-caffe-cuda
 And suggests these packages:
  * libcaffe-cuda-dev
  * caffe-doc
 .
 Note, this CUDA version cannot co-exist with the CPU_ONLY version.

Package: caffe-tools-cuda
Description-md5: 615a4c93f6cedb2bd35c6b6226415d6b
Description-en: Tools for fast, open framework for Deep Learning (CUDA)
 Caffe is a deep learning framework made with expression, speed,
 and modularity in mind. It is developed by the Berkeley AI Research
 Lab (BAIR) and community contributors.
 .
 It contains caffe executables, configured with CUDA.

Package: libcaffe-cuda-dev
Description-md5: 045f57a94680a15e78b7c646916fba70
Description-en: development files for Caffe (CUDA)
 Caffe is a deep learning framework made with expression, speed,
 and modularity in mind. It is developed by the Berkeley AI Research
 Lab (BAIR) and community contributors.
 .
 It contains the development files of caffe.

Package: libcaffe-cuda1
Description-md5: 7aaab677789490769df141ec809753b7
Description-en: library of Caffe, deep leanring framework (CUDA)
 Caffe is a deep learning framework made with expression, speed,
 and modularity in mind. It is developed by the Berkeley AI Research
 Lab (BAIR)and community contributors.
 .
 It contains caffe shared library, configured with CUDA.

Package: python3-caffe-cuda
Description-md5: 09838b3c464bba5d6ce1e2fa714afbe8
Description-en: Python3 interface of Caffe (CUDA)
 Caffe is a deep learning framework made with expression, speed,
 and modularity in mind. It is developed by the Berkeley AI Research
 Lab (BAIR) and community contributors.
 .
 It contains the CUDA version of python3 Caffe interface.

.
