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Package: python3-tomopy
Description-md5: 9a7c0aa2da2602d75a31a35cb002c912
Description-en: Python package for tomographic data processing and image reconstruction
 Features:
  * Image reconstruction algorithms for tomography.
  * Various filters, ring removal algorithms, phase retrieval algorithms.
  * Forward projection operator for absorption and wave propagation.
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3763,3780c
Package: libtensorpipe-cuda-0
Description-md5: b49a93726d4da68e6161824dc04f12b3
Description-en: tensor-aware point-to-point communication primitive for machine learning
 The TensorPipe project provides a tensor-aware channel to transfer rich
 objects from one process to another while using the fastest transport for the
 tensors contained therein (e.g., CUDA device-to-device copy).
 .
 This package contains shared objects.

Package: libtensorpipe-cuda-dev
Description-md5: 6b4397dd30e29fe70ebb4ea9c71ececf
Description-en: tensor-aware point-to-point communication primitive for machine learning
 The TensorPipe project provides a tensor-aware channel to transfer rich
 objects from one process to another while using the fastest transport for the
 tensors contained therein (e.g., CUDA device-to-device copy).
 .
 This package contains development files.

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Package: libsocl-contrib-1.4-1t64
Description-md5: 4a69ce3f02f2cf01466ed8b9a22d8758
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.
 This "contrib" version is built against CUDA.

Package: libstarpu-contrib-1.4-9
Description-md5: f0ca811d02d6bbb6c830781bf9811bff
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
 This "contrib" version is built against CUDA.

Package: libstarpu-contrib-dev
Description-md5: e7f42763fbe9c087a6defa203190f56e
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.
 This "contrib" version is built against CUDA.

Package: libstarpu-contrib-openmp-llvm-1.4-1t64
Description-md5: 0c4cf9967f5b66c184481dbb23c8faa6
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 runtime support for LLVM OpenMP.
 This "contrib" version is built against CUDA.

Package: libstarpu-contribfft-1.4-1t64
Description-md5: 1079179920c93a735ab89566a3855d36
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.
 This "contrib" version is built against CUDA.

Package: libstarpu-contribmpi-1.4-3t64
Description-md5: 4d3ce5602db3c9fbd91b7e19dcc14e2a
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.
 This "contrib" version is built against CUDA.

Package: libstarpu-contribrm-1.4-1t64
Description-md5: 3008682b6502a417f1d5f1b0170499a0
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 resource management library.
 This "contrib" version is built against CUDA.

Package: starpu-contrib-examples
Description-md5: 11b8c6811b08d3b761c4e2f5fd0e0890
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.
 This "contrib" version is built against CUDA.

Package: starpu-contrib-tools
Description-md5: 21e204c0915cd3972a9cf41ad059d147
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.
 This "contrib" version is built against CUDA.

Package: libstdgpu-cuda-dev
Description-md5: e4dd50a6deda827edd854dc36f6898ac
Description-en: Efficient STL-like Data Structures on the GPU (CUDA development headers)
 stdgpu is an open-source library providing several generic GPU data structures
 for fast and reliable data management. Multiple platforms such as CUDA,
 OpenMP, and HIP are supported allowing you to rapidly write highly complex
 agnostic and native algorithms that look like sequential CPU code but are
 executed in parallel on the GPU.
 .
 This package installs the development headers for the CUDA version.

Package: libstdgpu-cuda0d
Description-md5: 86f2a09d523e7b55fff456ecf5defbc3
Description-en: Efficient STL-like Data Structures on the GPU (CUDA backend)
 stdgpu is an open-source library providing several generic GPU data structures
 for fast and reliable data management. Multiple platforms such as CUDA,
 OpenMP, and HIP are supported allowing you to rapidly write highly complex
 agnostic and native algorithms that look like sequential CPU code but are
 executed in parallel on the GPU.
 .
 This package installs the shared library that runs on CUDA.
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Package: slurm-wlm-nvml-plugin
Description-md5: 382ad5eb1a96045c9ecbf90f2e89d21b
Description-en: SLURM NVML plugins
 SLURM, the Simple Linux Utility for Resource Management,
 is an open-source cluster resource management and job scheduling.
 .
 This package contains the Nvidia NVML-based SLURM plugin.

Package: slurm-wlm-nvml-plugin-dev
Description-md5: 25e2f364af04a256ac8860bffe699da0
Description-en: SLURM NVML plugin development files
 SLURM, the Simple Linux Utility for Resource Management,
 is an open-source cluster resource management and job scheduling.
 .
 This package contains development files for the Nvidia NVML-based
 SLURM plugins.

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Package: shockolate
Description-md5: 8cf0cb25bf0b6d52c9dd0baf16acf149
Description-en: System Shock game engine
 Shockolate is a source port of System Shock, a 1994 first-person
 action-adventure developed by LookingGlass Technologies.
 The game is set inside a large, multi-level space station,
 in which players explore, combat enemies and solve puzzles.
 .
 Shockolate aims to preserve the original gaming experience with a few
 improvements, such as an OpenGL renderer and support for mods.
 .
 The original System Shock game data files are required to run Shockolate.
 You can install them by using the game-data-packager tool.

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Package: python3-pycudwt
Description-md5: 6df6073c729e5bb493e299895787595d
Description-en: Python-CUDA implementation of the Wavelet Transform
 pycudwt is a python module for parallel Discrete Wavelet Transform
 using CUDA.

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Package: libnccl-dev
Description-md5: eb51ac028af4e93d497fb00fb21ea648
Description-en: NVIDIA Optimized primitives for inter-GPU communication (development)
 NCCL (pronounced "Nickel") is a stand-alone library of standard communication
 routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast,
 reduce-scatter, as well as any send/receive based communication pattern. It
 has been optimized to achieve high bandwidth on platforms using PCIe, NVLink,
 NVswitch, as well as networking using InfiniBand Verbs or TCP/IP sockets. NCCL
 supports an arbitrary number of GPUs installed in a single node or across
 multiple nodes, and can be used in either single- or multi-process (e.g., MPI)
 applications.
 .
 This package contains the development files.

Package: libnccl2
Description-md5: 9d65922c97dff88e1fb00aa87e7e5d73
Description-en: NVIDIA Optimized primitives for inter-GPU communication
 NCCL (pronounced "Nickel") is a stand-alone library of standard communication
 routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast,
 reduce-scatter, as well as any send/receive based communication pattern. It
 has been optimized to achieve high bandwidth on platforms using PCIe, NVLink,
 NVswitch, as well as networking using InfiniBand Verbs or TCP/IP sockets. NCCL
 supports an arbitrary number of GPUs installed in a single node or across
 multiple nodes, and can be used in either single- or multi-process (e.g., MPI)
 applications.
 .
 This package contains the shared objects.

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Package: nvbandwidth
Description-md5: 3761e1e5cbde48c98f34e9b72ed8a46d
Description-en: tool for bandwidth measurements on NVIDIA GPUs
 This measures bandwidth for various memcpy patterns across different links
 using copy engine or kernel copy methods. nvbandwidth reports current measured
 bandwidth on your system. Additional system-specific tuning may be required to
 achieve maximal peak bandwidth.

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Package: mumax3
Description-md5: 31b32b8b874fff7a3226df456e85a895
Description-en: GPU-accelerated micromagnetic simulator
 mumax3 is a GPU-accelerated micromagnetic simulation program developed
 at the DyNaMat group of Prof. Van Waeyenberge at Ghent University.
 .
 A speed-up of the order of 100x compared to CPU-based simulations can
 easily be reached, even with relatively inexpensive gaming
 GPUs. Additionally, the software is optimized for low memory use and
 can handle about 16 million FD cells with 2GB of GPU RAM.
 .
 Features:
  - Landau-Lifshitz micromagnetic formalism
  - Magnetostatic field
  - Heisenberg exchange
  - Arbitrary inter-region exchange like RKKY coupling
  - Dzyaloshinskii-Moriya interaction
  - Spin-transfer torque (Zhang-Li and Slonczewski)
  - Uniaxial and cubic magnetocrystalline anisotropy
  - Thermal fluctuations (Brown)
  - Voronoi tessellation
  - Time- and space dependent material parameters
  - Arbitrary complex excitation (field, current)
  - Simulation window can automatically follow a moving domain wall
  - Edge charges can be removed to simulate an infinitely long geometry
  - Optional 1D, 2D or 3D periodic boundary conditions

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Package: libmagma-dev
Description-md5: 8c96c9659ed332fd1cc18082bb49c285
Description-en: Matrix Algebra on GPU and Multicore Architectures (dev)
 The MAGMA project aims to develop a dense linear algebra library similar to
 LAPACK but for heterogeneous/hybrid architectures, starting with current
 "Multicore+GPU" systems.
 .
 The MAGMA research is based on the idea that, to address the complex challenges
 of the emerging hybrid environments, optimal software solutions will themselves
 have to hybridize, combining the strengths of different algorithms within a
 single framework. Building on this idea, we aim to design linear algebra
 algorithms and frameworks for hybrid manycore and GPU systems that can enable
 applications to fully exploit the power that each of the hybrid components
 offers.
 .
 This package contains the headers and the static libraries.

Package: libmagma-doc
Description-md5: acda0a8ac99c17cd5657815ecee12b3d
Description-en: Matrix Algebra on GPU and Multicore Architectures (doc)
 The MAGMA project aims to develop a dense linear algebra library similar to
 LAPACK but for heterogeneous/hybrid architectures, starting with current
 "Multicore+GPU" systems.
 .
 The MAGMA research is based on the idea that, to address the complex challenges
 of the emerging hybrid environments, optimal software solutions will themselves
 have to hybridize, combining the strengths of different algorithms within a
 single framework. Building on this idea, we aim to design linear algebra
 algorithms and frameworks for hybrid manycore and GPU systems that can enable
 applications to fully exploit the power that each of the hybrid components
 offers.
 .
 This package contains the Doxygen HTML documentation.

Package: libmagma-sparse2
Description-md5: 7466d1ecd53172205761e441ae3ae3e8
Description-en: Matrix Algebra on GPU and Multicore Architectures (solib, sparse)
 The MAGMA project aims to develop a dense linear algebra library similar to
 LAPACK but for heterogeneous/hybrid architectures, starting with current
 "Multicore+GPU" systems.
 .
 The MAGMA research is based on the idea that, to address the complex challenges
 of the emerging hybrid environments, optimal software solutions will themselves
 have to hybridize, combining the strengths of different algorithms within a
 single framework. Building on this idea, we aim to design linear algebra
 algorithms and frameworks for hybrid manycore and GPU systems that can enable
 applications to fully exploit the power that each of the hybrid components
 offers.
 .
 This package contains the shared object libmagma_sparse.so.2

Package: libmagma-test
Description-md5: baed7e032a53edc2a27a115e648b92ee
Description-en: Matrix Algebra on GPU and Multicore Architectures (tests)
 The MAGMA project aims to develop a dense linear algebra library similar to
 LAPACK but for heterogeneous/hybrid architectures, starting with current
 "Multicore+GPU" systems.
 .
 The MAGMA research is based on the idea that, to address the complex challenges
 of the emerging hybrid environments, optimal software solutions will themselves
 have to hybridize, combining the strengths of different algorithms within a
 single framework. Building on this idea, we aim to design linear algebra
 algorithms and frameworks for hybrid manycore and GPU systems that can enable
 applications to fully exploit the power that each of the hybrid components
 offers.
 .
 This package contains the test executables.

Package: libmagma2
Description-md5: 1b5c7a1b292272888775bfbb96c3b347
Description-en: Matrix Algebra on GPU and Multicore Architectures (solib)
 The MAGMA project aims to develop a dense linear algebra library similar to
 LAPACK but for heterogeneous/hybrid architectures, starting with current
 "Multicore+GPU" systems.
 .
 The MAGMA research is based on the idea that, to address the complex challenges
 of the emerging hybrid environments, optimal software solutions will themselves
 have to hybridize, combining the strengths of different algorithms within a
 single framework. Building on this idea, we aim to design linear algebra
 algorithms and frameworks for hybrid manycore and GPU systems that can enable
 applications to fully exploit the power that each of the hybrid components
 offers.
 .
 This package contains the shared object libmagma.so.2

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Package: indi-pentax
Description-md5: fcb9c4bf63087b6503ee2a63bcc8566c
Description-en: INDI driver for Pentax cameras
 This package contains an INDI driver for Pentax cameras.
 .
 This driver is compatible with any INDI client such as KStars or Xephem.

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Package: libhwloc-contrib-plugins
Description-md5: 2b02fbf995ab5fe6645ca4e4ad3e8d3f
Description-en: Hierarchical view of the machine - contrib plugins
 libhwloc provides a portable abstraction (across OS, versions,
 architectures, ...) of the hierarchical topology of modern architectures. It
 primarily aims at helping high-performance computing applications with
 gathering information about the hardware so as to exploit it accordingly and
 efficiently.
 .
 libhwloc provides a hierarchical view of the machine, NUMA memory nodes,
 sockets, shared caches, cores and simultaneous multithreading. It also gathers
 various attributes such as cache and memory information.
 .
 libhwloc supports old kernels not having sysfs topology information,
 with knowledge of cpusets, offline cpus, and Kerrighed support
 .
 This package contains plugins to add discovery support for non-free items. This
 includes
  - CUDA support.

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Package: gpu-burn
Description-md5: 92df966436bfa80d74015599c50bb431
Description-en: Multi-GPU CUDA stress test
 This allows one to run a stress test on your GPUs. Memory usage can
 be controlled by absolute number or percentage. Also allows one to run
 on specific GPU, useful if you have mixed multi GPU system.

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Package: libggml0-backend-cuda
Description-md5: 56db844880e610d6c8401c92a13f05dd
Description-en: Tensor library for machine learning - CUDA backend
 ggml is a tensor library for machine learning with the following features:
 .
  * Low-level cross-platform implementation
  * Integer quantization support
  * Broad hardware support
  * Automatic differentiation
  * ADAM and L-BFGS optimizers
  * No third-party dependencies
  * Zero memory allocations during runtime
 .
 On Debian, ggml is shipped as a package that depends on one of the CPU or
 GPU backends.
 .
 This package provides the CUDA backend, for NVIDIA GPUs.

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Package: libeztrace0-contrib
Description-md5: 0d7dd19ec5cdd84ca4eb1c67b1cf99b9
Description-en: Automatic execution trace generation for HPC - runtime libraries
 EZTrace is a tool that aims at generating automatically execution traces
 from HPC (High Performance Computing) programs. It generates execution
 trace files that can be interpreted by visualization tools such as
 ViTE. It uses LD_PRELOAD and dlsym() to intercept calls to the usual HPC
 primitives, to be observed.
 .
 This package contains the development files depending on CUDA.

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Package: dhewm3-cdoom
Description-md5: f8565308ef163459a58b6b6741b23cb0
Description-en: dhewm3's gamelibrary for the title Classic Doom³
 This package contains the shared library containing the game logic for
 the mod "Classic Doom³"
 .
 Please note that this package does not contain any game data, which is
 required to actually play the game.
 .
 The package game-data-packager can help you to package your copy of the
 game data. Please see README.Debian for details.

Package: dhewm3-d3le
Description-md5: c4d6f95a4525e5681966ffc96e33f611
Description-en: dhewm3's gamelibrary for the title DOOM³: The Lost Mission
 This package contains the shared library containing the game logic for
 the mod "DOOM3³: The Lost Mission"
 .
 Please note that this package does not contain any game data, which is
 required to actually play the game.
 .
 The package game-data-packager can help you to package your copy of the
 game data. Please see README.Debian for details.

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Description-md5: ae3c58118cee02e359fba426ae62a4b2
Description-en: Atari 8-bit emulator
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