nvidia-cuda-toolkit 11.5.1-ok2 source package in openKylin
Changelog
nvidia-cuda-toolkit (11.5.1-ok2) yangtze; urgency=medium * Fix DEFAULT_GCC_VERSION = 10. -- zhouganqing <email address hidden> Fri, 23 Sep 2022 16:44:00 +0800
nvidia-cuda-toolkit (11.5.1-ok2) yangtze; urgency=medium * Fix DEFAULT_GCC_VERSION = 10. -- zhouganqing <email address hidden> Fri, 23 Sep 2022 16:44:00 +0800
Series | Published | Component | Section | |
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Huanghe V3.0 | proposed | pty | libs | |
Huanghe V3.0 | release | pty | libs | |
Nile V2.0 | proposed | pty | libs | |
Nile V2.0 | release | pty | libs | |
Yangtze V1.0 | release | pty | libs | |
Yangtze V1.0 | proposed | pty | libs |
File | Size | SHA-256 Checksum |
---|---|---|
nvidia-cuda-toolkit_11.5.1.orig-amd64.tar.xz | 1.7 GiB | 3a1a12932d2bb1eb02152f4584278bbdea07d322cfdddb7e13443f1d9b99dd5d |
nvidia-cuda-toolkit_11.5.1.orig-arm64.tar.xz | 1.2 GiB | c55d0601a56c19592a261e287d6678c4fcf705199951b9b36e27ebbbd379478c |
nvidia-cuda-toolkit_11.5.1.orig-openjdk-8-jre-amd64-8u312-b07-1.tar.xz | 26.9 MiB | 6016dd7e4a7b0e235423d26b6b300a659bd65c15c4ae91cae818c994701a3485 |
nvidia-cuda-toolkit_11.5.1.orig-openjdk-8-jre-ppc64el-8u312-b07-1.tar.xz | 26.8 MiB | 565239d72ce72432cc87aa4b9dc6d90d65ecb173781bf5d147c539dc82ed7f86 |
nvidia-cuda-toolkit_11.5.1.orig-openjdk-8-source-8u312-b07-1.tar.xz | 70.4 MiB | 45e76b80e184c572a0987c688c61c2a43ac649df88ba64084c4a4f5a3de278a7 |
nvidia-cuda-toolkit_11.5.1.orig-ppc64el.tar.xz | 1.4 GiB | 3cba134d0826451408af0cc79fffd1559be3b3811662f8df97392ed6fc93f307 |
nvidia-cuda-toolkit_11.5.1.orig.tar.xz | 196 bytes | c682e7ea2872041676307c70c3826d077c1458f9a1bfe4883d8e31b2f282f4de |
nvidia-cuda-toolkit_11.5.1-ok2.debian.tar.xz | 47.0 KiB | 0ca5d8d0ed80fa4ba93ab646205fd92db04e7012863d1c9994492b261e2468cc |
nvidia-cuda-toolkit_11.5.1-ok2.dsc | 8.4 KiB | 1cb3207944fc4443158ff021478c0e82eab5fb3c7b1d529b40d987339e065971 |
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
ACCINJ is the OpenACC internal library for profiling.
.
This package contains the 64-bit ACCINJ runtime library.
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
The cuBLAS library is an implementation of BLAS (Basic Linear Algebra
Subprograms) on top of the NVIDIA CUDA runtime. It allows the user to access
the computational resources of NVIDIA Graphics Processing Unit (GPU), but
does not auto-parallelize across multiple GPUs.
.
This package contains the cuBLAS runtime library.
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
The cuBLASLt library is a lightweight GEMM library with a flexible API and
tensor core support for INT8 inputs and FP16 CGEMM split-complex matrix
multiplication.
.
This package contains the cuBLASLt runtime library.
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.
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 runtime library.
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.
The cuSOLVER library contains LAPACK-like functions in dense and sparse
linear algebra, including linear solver, least-square solver and eigenvalue
solver.
.
This package contains the cuSOLVER runtime library.
The cuSOLVER library contains LAPACK-like functions in dense and sparse
linear algebra, including linear solver, least-square solver and eigenvalue
solver.
.
This package contains the cuSOLVERmg runtime library.
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
The cuSPARSE library contains a set of basic linear algebra subroutines used
for handling sparse matrices. It is implemented on top of the NVIDIA CUDA
runtime and is designed to be called from C and C++. The library routines can
be classified into four categories:
* Level 1: operations between a vector in sparse format and a vector in dense
format
* Level 2: operations between a matrix in sparse format and a vector in dense
format
* Level 3: operations between a matrix in sparse format and a set of vectors
in dense format
* Conversion: operations that allow conversion between different matrix
formats
.
This package contains the cuSPARSE runtime library.
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.
NVIDIA NPP is a library of functions for performing CUDA accelerated
processing.
.
This package contains the NVIDIA Performance Primitives runtime library for
Image Arithmetic and Logic operations, 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 Color and sampling Conversion, 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 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.
NVIDIA NPP is a library of functions for performing CUDA accelerated
processing.
.
This package contains the NVIDIA Performance Primitives runtime library for
Image Geometry transforms, 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 Morphological operations, 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 Statistics and Linear Transformation, 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 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.
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 runtime library for
signal processing.
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 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.
CUDA Runtime Compilation library (nvrtc) provides an API to compile
CUDA-C++ device source code at runtime.
.
The resulting compiled PTX can be launched on a GPU using the CUDA
Driver API.
.
This package contains the NVRTC Builtins library.
CUDA Runtime Compilation library (nvrtc) provides an API to compile
CUDA-C++ device source code at runtime.
.
The resulting compiled PTX can be launched on a GPU using the CUDA
Driver API.
.
This package contains the NVRTC library.
The NVIDIA Tools Extension SDK (NVTX) is a C-based API for marking events and
ranges in your applications. Applications which integrate NVTX can use Nsight
to capture and visualize these events and ranges.
.
This package contains the NVIDIA Tools Extension runtime library.
NVIDIA's CUDA Compiler (NVCC) is based on the widely used LLVM open source
compiler infrastructure.
.
The NVVM library is used by NVCC to compile CUDA binary code to run on NVIDIA
GPUs.
.
This package contains the NVIDIA NVVM runtime library.
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.
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.
.
This package contains the target specific libraries.
NVIDIA Nsight Systems is a system-wide performance analysis tool designed to
visualize an application’s algorithms, help you identify the largest
opportunities to optimize, and tune to scale efficiently across any quantity
or size of CPUs and GPUs; from large server to smallest SoCs.
NVIDIA Nsight Systems is a system-wide performance analysis tool designed to
visualize an application’s algorithms, help you identify the largest
opportunities to optimize, and tune to scale efficiently across any quantity
or size of CPUs and GPUs; from large server to smallest SoCs.
.
This package contains the target specific libraries.
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.
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-gdb debugger.
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.
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
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.
.
Note that CUDA documentation is no longer bundled with CUDA toolkit releases.
Visit https:/
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
This package provides the /usr/bin/cuda-gcc, /usr/bin/cuda-g++ symlinks to
simplify building packages that need to be built with a CUDA-compatible
compiler.
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.
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
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 package contains the nvprof profiler.
The NVIDIA Visual Profiler is a cross-platform performance profiling tool
that delivers developers vital feedback for optimizing CUDA C/C++ and OpenCL
applications.