普利茅斯将来会允许使用专有图形驱动程序获得良好的启动体验吗？

Question

greatfiction

Asked: 2018-05-02 21:27:48 +0800 CST2018-05-02 21:27:48 +0800 CST 2018-05-02 21:27:48 +0800 CST

如何使用 Coffee Lake 在 18.04 上安装 NVIDIA CUDA 工具包 - 是否支持？

772

我喜欢 18.04 的安装，而且我也经常使用 blender3d。我需要 CUDA 工具包才能使用我的 GPU 而不是我的 CPU 进行渲染。

我已经读过，获得正确的工具包至关重要，否则可能会遇到一些非常糟糕的问题。只是想确认它可用于 Ubuntu 18.04。

另外，从哪里得到它并确认它是正确的？

谢谢

2 个回答

Voted

Terrance · Answer 1 · 2018-05-02T21:58:36+08:00

现在看起来好像CUDA 9.1实际上在官方 18.04 存储库中。从终端窗口运行以下命令：

sudo apt install nvidia-cuda-toolkit

安装后运行nvcc -V确认。您应该会看到与此类似的内容：

terrance@terrance-ubuntu:~$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85

该工具包还安装了必要的驱动程序和对OpenCL. 只需安装clinfo并运行它即可查看：

sudo apt install clinfo

然后你应该得到类似下面的东西：

terrance@terrance-ubuntu:~$ clinfo
Number of platforms                               1
  Platform Name                                   NVIDIA CUDA
  Platform Vendor                                 NVIDIA Corporation
  Platform Version                                OpenCL 1.2 CUDA 9.2.101
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer
  Platform Extensions function suffix             NV

  Platform Name                                   NVIDIA CUDA
Number of devices                                 1
  Device Name                                     GeForce GTX 760
  Device Vendor                                   NVIDIA Corporation
  Device Vendor ID                                0x10de
  Device Version                                  OpenCL 1.2 CUDA
  Driver Version                                  396.24
  Device OpenCL C Version                         OpenCL C 1.2 
  Device Type                                     GPU
  Device Topology (NV)                            PCI-E, 02:00.0
  Device Profile                                  FULL_PROFILE
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Max compute units                               6
  Max clock frequency                             1032MHz
  Compute Capability (NV)                         3.0
  Device Partition                                (core)
    Max number of sub-devices                     1
    Supported partition types                     None
  Max work item dimensions                        3
  Max work item sizes                             1024x1024x64
  Max work group size                             1024
  Preferred work group size multiple              32
  Warp size (NV)                                  32
  Preferred / native vector sizes                 
    char                                                 1 / 1       
    short                                                1 / 1       
    int                                                  1 / 1       
    long                                                 1 / 1       
    half                                                 0 / 0        (n/a)
    float                                                1 / 1       
    double                                               1 / 1        (cl_khr_fp64)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  Yes
  Double-precision Floating-point support         (cl_khr_fp64)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
  Address bits                                    64, Little-Endian
  Global memory size                              2095710208 (1.952GiB)
  Error Correction support                        No
  Max memory allocation                           523927552 (499.7MiB)
  Unified memory for Host and Device              No
  Integrated memory (NV)                          No
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       4096 bits (512 bytes)
  Global Memory cache type                        Read/Write
  Global Memory cache size                        98304 (96KiB)
  Global Memory cache line size                   128 bytes
  Image support                                   Yes
    Max number of samplers per kernel             32
    Max size for 1D images from buffer            134217728 pixels
    Max 1D or 2D image array size                 2048 images
    Max 2D image size                             16384x16384 pixels
    Max 3D image size                             4096x4096x4096 pixels
    Max number of read image args                 256
    Max number of write image args                16
  Local memory type                               Local
  Local memory size                               49152 (48KiB)
  Registers per block (NV)                        65536
  Max number of constant args                     9
  Max constant buffer size                        65536 (64KiB)
  Max size of kernel argument                     4352 (4.25KiB)
  Queue properties                                
    Out-of-order execution                        Yes
    Profiling                                     Yes
  Prefer user sync for interop                    No
  Profiling timer resolution                      1000ns
  Execution capabilities                          
    Run OpenCL kernels                            Yes
    Run native kernels                            No
    Kernel execution timeout (NV)                 Yes
  Concurrent copy and kernel execution (NV)       Yes
    Number of async copy engines                  1
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels                                
  Device Extensions                               cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  NVIDIA CUDA
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [NV]
  clCreateContext(NULL, ...) [default]            Success [NV]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  Invalid device type for platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  No platform

ICD loader properties
  ICD loader Name                                 OpenCL ICD Loader
  ICD loader Vendor                               OCL Icd free software
  ICD loader Version                              2.2.11
  ICD loader Profile                              OpenCL 2.1

要在 18.04LTS 中安装 NVIDIA 显卡驱动程序，请按照以下步骤操作：

在终端窗口中，输入：

sudo apt-add-repository ppa:graphics-drivers/ppa

然后运行更新：

sudo apt update

然后安装显卡驱动：

sudo apt install nvidia-driver-396

重启后可以运行nvidia-smi查看是否安装：

terrance@terrance-ubuntu:~$ nvidia-smi
Wed May  2 22:38:14 2018       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 396.24                 Driver Version: 396.24                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 760     Off  | 00000000:02:00.0 N/A |                  N/A |
| 49%   51C    P0    N/A /  N/A |    262MiB /  1998MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0                    Not Supported                                       |
+-----------------------------------------------------------------------------+

希望这可以帮助！

Christian Aubry · Answer 2 · 2019-02-05T10:27:42+08:00

Christian Aubry

2019-02-05T10:27:42+08:002019-02-05T10:27:42+08:00

我设法在我的笔记本电脑上安装了 CUDA，但在遇到 gcc-6 问题之前一直卡住。所以，总结一下：

安装nvidia专有驱动；
从 Ubuntu 存储库安装 nvidia-settings、nvidia-prime 和 nvidia-cuda-toolkit。
使用“nvcc --version”和/或“nvidia-smi”命令检查终端中是否安装了 CUDA。
最后，如果你看不到 CUDA，你必须确保你使用的是 gcc-6 而不是 gcc-7 或更高版本。我在这个线程中找到了解决方案并且它有效。

1) 安装 gcc-6、g++-6 (CUDA 需要 gcc-6 ！) 2) 在 /usr/bin 中以 root 身份，删除或重命名 gcc、gcc-ar、gcc-nm、gcc-ranlib 和 g++（如果它存在），然后 ln -s gcc-6 gcc；ln -s gcc-ar-6 gcc-ar; ln -s gcc-nm-6 gcc-nm；ln -s gcc-ranlib-6 gcc-ranlib; 和 ln -s g++-6 g++

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