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在Jetson Tk1板上将CULA密集库加载到python中

[英]Load CULA dense library into python on jetson tk1 board

Having successfully downloaded and installed the full CULA dense R18 package from this website ( http://www.culatools.com/downloads/dense/ ) onto my jetson TK1 board, I haven't been able to load the library into python using ctypes. 从此网站( http://www.culatools.com/downloads/dense/ )成功下载并安装了完整的CULA密集R18程序包后,我无法使用ctypes将库加载到python中。 I've changed LD_LIBRARY_PATH in ./bashrc to include the directory which contains the libcula_lapack.so shared object file: 我已将./bashrc中的LD_LIBRARY_PATH更改为包含包含libcula_lapack.so共享库文件的目录:

export PATH=/usr/local/cuda-6.0/bin:$PATH
LD_LIBRARY_PATH=/usr/local/cula/lib/
export LD_LIBRARY_PATH

but when I run the following code: 但是当我运行以下代码时:

import ctypes
libculac = ctypes.cdll.LoadLibrary("libcula_scalapack.so")

I get this error: 我收到此错误:

libcula_scalapack.so: cannot open shared object file: No such file or directory

I have tried putting the full directory in as an argument etc. and I have also tried every .so file in the lib directory and lib64 directory in case I had the wrong file. 我尝试将完整目录作为参数等,并且还尝试了lib目录和lib64目录中的每个.so文件,以防文件错误。 When I put a text file within the same directory (or any directory for that matter) and call it in the LoadLibrary command, the aforementioned error code does not trigger unless I make a typo (another error message is of course triggered though as expected). 当我在同一个目录(或与此相关的任何目录)中放置一个文本文件并在LoadLibrary命令中调用它时,除非输入错误,否则不会触发上述错误代码(当然也会触发另一个错误消息,尽管如此) 。

In contrast I have applied the exact same methodology (as far as I can tell) to importing cudart and npp libraries into python with great success. 相比之下,我将完全相同的方法(据我所知)成功地将cudart和npp库导入python。 Any help would be greatly appreciated and please inform me if I've left out any important information or if I'm being very dense (pun intended). 任何帮助将不胜感激,如果我遗漏了任何重要信息,或者如果我很忙(双关语),请通知我。 Thanks! 谢谢!

Board: Jetson TK1 董事会:Jetson TK1

CUDA: 6.0 (downloaded from https://developer.nvidia.com/jetson-tk1-support ) CUDA:6.0(从https://developer.nvidia.com/jetson-tk1-support下载)

OS: L4T Ubuntu 14.04 (from https://developer.nvidia.com/jetson-tk1-support ) 操作系统:L4T Ubuntu 14.04(来自https://developer.nvidia.com/jetson-tk1-support

Language: Python 2.7 语言:Python 2.7

好像CULA库与ARM体系结构不兼容,如《参考指南》中的“ CULA内部使用英特尔®数学内核库(MKL)”行所示,因此与Jetson TK1不兼容。真是可惜。

I don't know if it means anything 8 months later, but in the spirit of documenting progress... I've been able to get a convolutional neural network running on CUDA 6.5 + Python + Theano + Lasagne working successfully on a Jetson TK1, more info in the Lasagne google group: https://groups.google.com/d/msg/lasagne-users/GtcQo1dSJdo/3X5DVSkvGNUJ 我不知道这在8个月后是否意味着任何意义,但是本着记录进度的精神……我已经能够在CUDA 6.5 + Python + Theano + Lasagne上运行的卷积神经网络在Jetson TK1上成功运行,在Lasagne google组中的更多信息: https : //groups.google.com/d/msg/lasagne-users/GtcQo1dSJdo/3X5DVSkvGNUJ

So it absolutely is possible to get a working CUDA implementation on a Jetson TK1 and also have it perform computation for stereotypical exercises. 因此,绝对有可能在Jetson TK1上获得有效的CUDA实现,并使其执行用于定型练习的计算。 Luckily, NVIDIA has released instructions for installing Ubuntu with all of the correct CUDA and GPU drivers. 幸运的是,NVIDIA发布了有关使用所有正确的CUDA和GPU驱动程序安装Ubuntu的说明。

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