nvidia-cuda-toolkit 10.1.243-3 source package in Ubuntu

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 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 This package contains the CUDA Runtime API library for high-level CUDA
 programming, on top of the CUDA Driver API.

 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 The FFT is a divide-and-conquer algorithm for efficiently computing discrete
 Fourier transforms of complex or real-valued data sets. It is one of the most
 important and widely used numerical algorithms in computational physics and
 general signal processing. The cuFFT library provides a simple interface for
 computing FFTs on an NVIDIA GPU, which allows users to quickly leverage the
 floating-point power and parallelism of the GPU in a highly optimized and
 tested FFT library.
 .
 This package contains the cuFFT runtime library.

 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 The FFT is a divide-and-conquer algorithm for efficiently computing discrete
 Fourier transforms of complex or real-valued data sets. It is one of the most
 important and widely used numerical algorithms in computational physics and
 general signal processing. The cuFFT library provides a simple interface for
 computing FFTs on an NVIDIA GPU, which allows users to quickly leverage the
 floating-point power and parallelism of the GPU in a highly optimized and
 tested FFT library.
 .
 This package contains the cuFFTW runtime library.

 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 CUINJ is the CUDA internal library for profiling.
 .
 This package contains the 64-bit CUINJ runtime library.

 The CUDA Profiler Tools Interface (CUPTI) enables the creation of
 profiling and tracing tools that target CUDA applications. CUPTI
 provides a set of APIs targeted at ISVs creating profilers and other
 performance optimization tools. The CUPTI APIs are not intended to be
 used by developers in their CUDA applications.
 .
 This package contains the development files: headers and libraries.

 The CUDA Profiler Tools Interface (CUPTI) enables the creation of
 profiling and tracing tools that target CUDA applications. CUPTI
 provides a set of APIs targeted at ISVs creating profilers and other
 performance optimization tools. The CUPTI APIs are not intended to be
 used by developers in their CUDA applications.
 .
 This package contains the documentation and examples.

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 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 The cuRAND library provides facilities that focus on the simple and efficient
 generation of high-quality pseudorandom and quasirandom numbers.
 A pseudorandom sequence of numbers satisfies most of the statistical
 properties of a truly random sequence but is generated by a deterministic
 algorithm. A quasirandom sequence of n-dimensional points is generated by a
 deterministic algorithm designed to fill an n-dimensional space evenly.
 .
 This package contains the cuRAND runtime library.

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 NVIDIA NPP is a library of functions for performing CUDA accelerated
 processing. The initial set offunctionality in the library focuses on imaging
 and video processing and is widely applicable for developers in these areas.
 NPP will evolve over time to encompass more of the compute heavy tasks in a
 variety of problem domains. The NPP library is written to maximize
 flexibility, while maintaining high performance.
 .
 This package contains the NVIDIA Performance Primitives core runtime library.

No description available for libnppial10 in ubuntu groovy.

 NVIDIA NPP is a library of functions for performing CUDA accelerated
 processing.
 .
 This package contains the NVIDIA Performance Primitives runtime library for
 Image Color and sampling Conversion, which is a sub-library of nppi.

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 NVIDIA NPP is a library of functions for performing CUDA accelerated
 processing.
 .
 This package contains the NVIDIA Performance Primitives runtime library for
 Image Data Exchange and Initialization, which is a sub-library of nppi.

 NVIDIA NPP is a library of functions for performing CUDA accelerated
 processing.
 .
 This package contains the NVIDIA Performance Primitives runtime library for
 Image Filters, which is a sub-library of nppi.

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 NVIDIA NPP is a library of functions for performing CUDA accelerated
 processing.
 .
 This package contains the NVIDIA Performance Primitives runtime library for
 Image Support, which is a sub-library of nppi.

 NVIDIA NPP is a library of functions for performing CUDA accelerated
 processing.
 .
 This package contains the NVIDIA Performance Primitives runtime library for
 Image Threshold and Compare, which is a sub-library of nppi.

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 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 The NVBLAS Library is a GPU-accelerated Library that implements BLAS (Basic
 Linear Algebra Subprograms). It can accelerate most BLAS Level-3 routines by
 dynamically routing BLAS calls to one or more NVIDIA GPUs present in the
 system, when the characteristics of the call make it to speedup on a GPU.

 The NVIDIA Graph Analytics library (nvGRAPH) comprises of parallel
 algorithms for high performance analytics on graphs with up to 2 billion
 edges. nvGRAPH makes it possible to build interactive and high throughput
 graph analytics applications.
 .
 nvGRAPH supports three widely-used algorithms:
  * [Page Rank] is most famously used in search engines, and also used in
    social network analysis, recommendation systems, and for novel uses
    in natural science when studying the relationship between proteins
    and in ecological networks.
  * [Single Source Shortest Path] is used to identify the fastest path from
    A to B through a road network, and can also be used for a optimizing
    a wide range of other logistics problems.
  * [Single Source Widest Path] is used in domains like IP traffic routing
    and traffic-sensitive path planning.
 .
 In addition, the nvGRAPH semi-ring SPMV operations can be used to build
 a wide range of innovative graph traversal algorithms.
 .
 nvGRAPH accelerates analysis of large graphs by making efficient use of
 the massive parallelism available in NVIDIA Tesla GPUs. The size of a
 graph in memory is dominated by the number of edges.
 An M40 with 24 GB can support a graph of up to 2 billion edges.

 The NVIDIA Management Library (NVML) provides a monitoring and management API.
 It provides a direct access to the queries and commands exposed via nvidia-smi.
 .
 This package contains the header file and depends on the driver-provided
 library.

 The nvJPEG 1.0 library provides high-performance, GPU accelerated JPEG
 decoding functionality for image formats commonly used in deep learning and
 hyperscale multimedia applications. The library offers single and batched JPEG
 decoding capabilities which efficiently utilize the available GPU resources
 for optimum performance; and the flexibility for users to manage the memory
 allocation needed for decoding.

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 NVIDIA Nsight Compute is an interactive kernel profiler for CUDA applications.
 It provides detailed performance metrics and API debugging via a user
 interface and command line tool. In addition, its baseline feature allows
 users to compare results within the tool. Nsight Compute provides a
 customizable and data-driven user interface and metric collection and can be
 extended with analysis scripts for post-processing results.

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 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 This package contains the development files: headers and libraries.

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 The Compute Unified Device Architecture (CUDA) enables NVIDIA
 graphics processing units (GPUs) to be used for massively parallel
 general purpose computation.
 .
 This package contains the nvcc compiler and other tools needed for building
 CUDA applications.
 .
 Running CUDA applications requires a supported NVIDIA GPU and the NVIDIA
 driver kernel module.

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 NVIDIA Nsight Eclipse Edition is a full-featured IDE powered by the Eclipse
 platform that provides an all-in-one integrated environment to edit, build,
 debug and profile CUDA-C applications.
 Nsight Eclipse Edition supports a rich set of commercial and free plugins.

 OpenCL (Open Computing Language) is a multi-vendor open standard for
 general-purpose parallel programming of heterogeneous systems that include
 CPUs, GPUs and other processors.
 .
 This metapackage provides the development files: headers and libraries.

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