#pyopencl

[jordanrousseau-blog]

Because it Was Stated Beforehand

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[tofutimbre]

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geil. 20 minuten für Berechnungen die vorher über 24 Stunden gedauert haben.

I love it!

[sage-t]

pyOpenCLのビルド

前の記事：RadeonとGeForceの並列

というわけでせっかく導入したマルチGPGPU環境、せっかくなのでOpenCLを入れてみようと思います。

pip install pyopencl

失敗。CL/cl.hがないとのこと。

これはpipが呼び出しているC++コンパイラが必要なヘッダファイルの場所を知らないという状況です。 これはsetup.pyと同じフォルダに置かれたsiteconf.pyを通じてコンパイラに教えることができます。

とりあえずAMDの方のを使います。

まずpyopencl.tar.gzを拾ってきて解凍、なかのconfigure.pyを実行。生成したsiteconf.pyを編集します。

CL_TRACE = False CL_ENABLE_GL = False CL_INC_DIR = ['C:\\Program Files (x86)\\AMD APP SDK\\3.0\\include'] CL_LIB_DIR = ['C:\\Program Files (x86)\\AMD APP SDK\\3.0\\lib\\x86_64'] CL_LIBNAME = ['OpenCL']

これでpyopenclのディレクトリから

pip install .

するとガンガンエラーが出る。uint32_tがどうとか、syntax errorとか。

今の僕にはNvidiaもあるんだ、ということでそちらに切り替え。

CL_INC_DIR = ['C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v7.5\\include'] CL_LIB_DIR = ['C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v7.5\\lib\\x64']

でもやっぱり同じエラー。

エラーの内容を見ると、まずwrap_cl_core.hで

uint32_tが定義されていない

typedef usingが使えない

で引っかかり、それ以降に進ま��い感じです。

賢明な読者諸君にはお分かりの通り、これはC++0xの仕様です。

翻ってコンパイラはVisual C++ for python、中身はVS2008で使われていたVC9です。

解決策は・・・・

ビルドをあきらめてバイナリをインストール

python 3に移行（python本体がVS2010以降でビルド）

コンパイラを変える

ソースコードをいじる

C++0xを使っていない時代のpyOpenCLのバージョンを使う

が考えられるかな、と。ということで最後のを試してみます。

git clone https://github.com/pyopencl/pyopencl.git cd pyopencl git checkout v2015.1 vi siteconf.py pip install .

するとコンパイル成功。やったぜ。 ちなみに環境はWindowsですが、viはmsysのものです。

だけどエラーは出た。

thread.obj : error LNK2001: unresolved external symbol "void __cdecl pyopenclboost::throw_exception(class std::exception const &)" (?throw_exception@pyopenclboost@@YAXAEBVexception@std@@@Z) wrap_mempool.obj : error LNK2001: unresolved external symbol "void __cdecl pyopenclboost::throw_exception(class std::exception const &)" (?throw_exception@pyopenclboost@@YAXAEBVexception@std@@@Z) builtin_converters.obj : error LNK2001: unresolved external symbol "void __cdecl pyopenclboost::throw_exception(class std::exception const &)" (?throw_exception@pyopenclboost@@YAXAEBVexception@std@@@Z)

以下略。

エラーをよく見ると/EHscを使えってあったので、siteconf.pyに

CXXFLAGS = ['/EHsc']

を追加、またpip install .。

.

.

.

インストール成功。やったぜ。

なお、siteconf.pyのオプションを調べてたり、ソースコードを覗いていたら、Boostを使っているのかもしれません。 僕は以前PCLで遊ぶためにビルドとパス設定をしたBoost（VC120とVC140）があるので、問題はありませんでした。

とりあえず上の設定でやってみて���Boostのライブラリが足りないっぽいエラーが出たらBoostをインストールしてみたらいいと思います。

せっかくなのでベンチマーク。opyopenclの中のexampleを使います。

cd examples python download-examples-from-wwiki.py cd wiki-examples python MatrixMultiply.py # for python MatrixMultiply.py python MatrixMultiply.py

結果は以下のとおり。

$ python MatrixMultiply.py Choose platform: [0] [1] Choice [0]:1 Set the environment variable PYOPENCL_CTX='1' to avoid being asked again. GPU push+compute+pull total [s]: 0.0306499838829 GPU push [s]: 0.00999999046326 GPU pull [s]: 0.00999999046326 GPU compute (host-timed) [s]: 0.0106500029564 GPU compute (event-timed) [s]: 0.010541984 GFlops/s: 192.300416102 GPU==CPU: True CPU time (s) 1.88499999046 GPU speedup (with transfer): 61.5008476893 GPU speedup (without transfer): 176.995255136 $ python MatrixMultiply.py Choose platform: [0] [1] Choice [0]:0 Choose device(s): [0] [1] Choice, comma-separated [0]:0 Set the environment variable PYOPENCL_CTX='0:0' to avoid being asked again. GPU push+compute+pull total [s]: 0.047450363636 GPU push [s]: 0.00400018692017 GPU pull [s]: 0.00400018692017 GPU compute (host-timed) [s]: 0.0394499897957 GPU compute (event-timed) [s]: 0.03938454 GFlops/s: 51.9138283839 GPU==CPU: True CPU time (s) 1.84999990463 GPU speedup (with transfer): 38.9881080538 GPU speedup (without transfer): 46.8948132614 $ python MatrixMultiply.py Choose platform: [0] [1] Choice [0]:0 Choose device(s): [0] [1] Choice, comma-separated [0]:1 Set the environment variable PYOPENCL_CTX='0:1' to avoid being asked again. GPU push+compute+pull total [s]: 7.53135018349 GPU push [s]: 0.00400018692017 GPU pull [s]: 0.0 GPU compute (host-timed) [s]: 7.52734999657 GPU compute (event-timed) [s]: 7.636417726 GFlops/s: 0.272074501775 GPU==CPU: True CPU time (s) 1.72899985313 GPU speedup (with transfer): 0.22957369011 GPU speedup (without transfer): 0.229695690239

device GFlops/s GTX750Ti 192.300416102 Radeon 51.9138283839 A10 0.272074501775

さすがにCPU遅すぎなので、設定がまずいのかもしれません。

今回はとりあえずこれくらいで。

[neilad-blog]

Compiling PyOpenCL 2013 on Scientific Linux 6.x

# pre

sudo easy_install pip

yum install tkinter python-imaging python-imaging-tk

git clone http://git.tiker.net/trees/pyopencl.git

cd pyopencl

git submodule init

git submodule update

python configure.py --cl-enable-gl \

  --cl-inc-dir=/usr/local/cuda-5.5/include \

  --cl-lib-dir=/usr/local/cuda-5.5/lib64 \