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authorNikolay Nikolov <nikobnikolov[at]gmail[dot]com>2017-07-18 11:47:28 +0100
committerWilly Sudiarto Raharjo <willysr@slackbuilds.org>2017-07-22 06:56:01 +0700
commit620777f1f9a6c5136e582aa3cd01107b9641c26e (patch)
tree07f2f4fa3c78db3a1bf0d8201a1784de7d61084b /development/cudnn
parent33f1a4ccea9fe4905e9f4322a0dff9f0ebfd4f79 (diff)
downloadslackbuilds-620777f1f9a6c5136e582aa3cd01107b9641c26e.tar.gz
development/cudnn: Added (CUDA Deep Neural Network library).
Signed-off-by: David Spencer <idlemoor@slackbuilds.org>
Diffstat (limited to 'development/cudnn')
-rw-r--r--development/cudnn/README12
-rw-r--r--development/cudnn/cudnn.SlackBuild95
-rw-r--r--development/cudnn/cudnn.info10
-rw-r--r--development/cudnn/slack-desc19
4 files changed, 136 insertions, 0 deletions
diff --git a/development/cudnn/README b/development/cudnn/README
new file mode 100644
index 0000000000..097b80517b
--- /dev/null
+++ b/development/cudnn/README
@@ -0,0 +1,12 @@
+The NVIDIA CUDA Deep Neural Network library (cuDNN) is a GPU-accelerated
+library of primitives for deep neural networks. cuDNN provides highly tuned
+implementations for standard routines such as forward and backward convolution,
+pooling, normalization, and activation layers. cuDNN is part of the NVIDIA
+Deep Learning SDK.
+
+You will need to register for NVIDIA developer account to download the source.
+
+Make sure you create the CUDA_HOME environment variable and add it to your
+~/.bashrc. The default should be
+
+CUDA_HOME=/usr/share/cuda
diff --git a/development/cudnn/cudnn.SlackBuild b/development/cudnn/cudnn.SlackBuild
new file mode 100644
index 0000000000..248450a15b
--- /dev/null
+++ b/development/cudnn/cudnn.SlackBuild
@@ -0,0 +1,95 @@
+#!/bin/sh
+
+# Slackware build script for cudnn
+
+# Copyright 2016 Nikolay Nikolov <nikobnikolov[at]gmail[dot]com>
+# All rights reserved.
+#
+# Redistribution and use of this script, with or without modification, is
+# permitted provided that the following conditions are met:
+#
+# 1. Redistributions of this script must retain the above copyright
+# notice, this list of conditions and the following disclaimer.
+#
+# THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR IMPLIED
+# WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+# MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
+# EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
+# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+PRGNAM=cudnn
+VERSION=${VERSION:-v5.1_8.0}
+BUILD=${BUILD:-1}
+TAG=${TAG:-_SBo}
+
+CUDNN_VERSION=${VERSION%_*}
+CUDA_VERSION=${VERSION#*_}
+
+if [ -z "$ARCH" ]; then
+ case "$( uname -m )" in
+ i?86) ARCH=i586 ;;
+ arm*) ARCH=arm ;;
+ *) ARCH=$( uname -m ) ;;
+ esac
+fi
+
+CWD=$(pwd)
+TMP=${TMP:-/tmp/SBo}
+PKG=$TMP/package-$PRGNAM
+OUTPUT=${OUTPUT:-/tmp}
+
+if [ "$ARCH" = "i586" ]; then
+ SLKCFLAGS="-O2 -march=i586 -mtune=i686"
+ LIBDIRSUFFIX=""
+elif [ "$ARCH" = "i686" ]; then
+ SLKCFLAGS="-O2 -march=i686 -mtune=i686"
+ LIBDIRSUFFIX=""
+elif [ "$ARCH" = "x86_64" ]; then
+ SLKCFLAGS="-O2 -fPIC"
+ LIBDIRSUFFIX="64"
+else
+ SLKCFLAGS="-O2"
+ LIBDIRSUFFIX=""
+fi
+
+set -e
+
+rm -rf $PKG
+mkdir -p $TMP $PKG $OUTPUT
+cd $TMP
+rm -rf cuda
+tar xvf $CWD/$PRGNAM-$CUDA_VERSION-linux-x64-$CUDNN_VERSION.tgz
+cd cuda
+chown -R root:root .
+find -L . \
+ \( -perm 777 -o -perm 775 -o -perm 750 -o -perm 711 -o -perm 555 \
+ -o -perm 511 \) -exec chmod 755 {} \; -o \
+ \( -perm 666 -o -perm 664 -o -perm 640 -o -perm 600 -o -perm 444 \
+ -o -perm 440 -o -perm 400 \) -exec chmod 644 {} \;
+
+mkdir -p $PKG/usr/share/cuda/include
+cp -P \
+ include/cudnn.h \
+$PKG/usr/share/cuda/include
+
+mkdir -p $PKG/usr/share/cuda/lib64
+cp -P \
+ lib64/libcudnn* \
+$PKG/usr/share/cuda/lib64
+
+find $PKG -print0 | xargs -0 file | grep -e "executable" -e "shared object" | grep ELF \
+ | cut -f 1 -d : | xargs strip --strip-unneeded 2> /dev/null || true
+
+mkdir -p $PKG/usr/doc/$PRGNAM-$VERSION
+cat $CWD/$PRGNAM.SlackBuild > $PKG/usr/doc/$PRGNAM-$VERSION/$PRGNAM.SlackBuild
+
+mkdir -p $PKG/install
+cat $CWD/slack-desc > $PKG/install/slack-desc
+
+cd $PKG
+/sbin/makepkg -l y -c n $OUTPUT/$PRGNAM-$VERSION-$ARCH-$BUILD$TAG.${PKGTYPE:-tgz}
diff --git a/development/cudnn/cudnn.info b/development/cudnn/cudnn.info
new file mode 100644
index 0000000000..fc880026df
--- /dev/null
+++ b/development/cudnn/cudnn.info
@@ -0,0 +1,10 @@
+PRGNAM="cudnn"
+VERSION="v5.1_8.0"
+HOMEPAGE="https://developer.nvidia.com/cudnn"
+DOWNLOAD="UNSUPPORTED"
+MD5SUM=""
+DOWNLOAD_x86_64="https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v6/prod/8.0_20170427/cudnn-8.0-linux-x64-v5.1-tgz"
+MD5SUM_x86_64="406f4ac7f7ee8aa9e41304c143461a69"
+REQUIRES="cudatoolkit"
+MAINTAINER="Nikolay Nikolov"
+EMAIL="nikobnikolov[at]gmail[dot]com"
diff --git a/development/cudnn/slack-desc b/development/cudnn/slack-desc
new file mode 100644
index 0000000000..8d2866e86c
--- /dev/null
+++ b/development/cudnn/slack-desc
@@ -0,0 +1,19 @@
+# HOW TO EDIT THIS FILE:
+# The "handy ruler" below makes it easier to edit a package description.
+# Line up the first '|' above the ':' following the base package name, and
+# the '|' on the right side marks the last column you can put a character in.
+# You must make exactly 11 lines for the formatting to be correct. It's also
+# customary to leave one space after the ':' except on otherwise blank lines.
+
+ |-----handy-ruler------------------------------------------------------|
+cudnn: cudnn (CUDA Deep Neural Network library)
+cudnn:
+cudnn: The NVIDIA CUDA Deep Neural Network library (cuDNN) is a GPU
+cudnn: accelerated library of primitives for deep neural networks. cuDNN
+cudnn: provides highly tuned implementations for standard routines such as
+cudnn: forward and backward convolution, pooling, normalization, and
+cudnn: activation layers. cuDNN is part of the NVIDIA Deep Learning SDK.
+cudnn:
+cudnn:
+cudnn: https://developer.nvidia.com/cudnn
+cudnn: