devtoolset-9-gcc 是CentOS 或 RHEL(Red Hat Enterprise Linux)系统上的 Software Collections (SCL) 仓库中的一个软件包,用于提供较新版本的 GCC 编译器。 如果你使用的是 CentOS 或 RHEL,包管理器通常是 yum 或dnf(在 CentOS 8 和 RHEL 8 及更高版本中)。
sudo yum -y install centos-release-scl sudo yum -y install devtoolset-9-gcc devtoolset-9-gcc-c++ sclenabledevtoolset-9 bash For the initial compilation, it is recommended to use the build script build.sh, which checks if the required software is available on the local machine. ...
CUDA available: True numpy_random_seed: 2147483648 GPU 0: NVIDIA TITAN X (Pascal) CUDA_HOME: /usr/local/cuda-10.2 NVCC: Cuda compilation tools, release 10.2, V10.2.8 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.12.1+cu102 PyTorch compiling details: PyTorch built with: GCC...
+ cd /home/my.name/Qt/qt5-build/config.tests/c11 && MAKEFLAGS= /opt/rh/devtoolset-8/root/usr/bin/gmake > gcc -c -pipe -O2 -std=gnu11 -w -fPIC -I. -I/home/my.name/Qt/qt-everywhere-src-5.15.5/qtbase/mkspecs/linux-g++ -o main.o main.c ...
yum install -y devtoolset-8-toolchain scl enable devtoolset-8 bash # 安装完成后查看版本 gcc --version ``` ### 3.安装并指定安装目录 ```bash make install PREFIX=/usr/local/redis #拷贝一份配置文件 cp /data/redis/redis-6.0.8/redis.conf /usr/local/redis/bin/ ``` ### 至此安装完成 ...
What needs to happen to make the build work is to somehow install a GCC that is newer than 4.9 (if I recall correctly). One can use https://www.softwarecollections.org/en/scls/rhscl/devtoolset-8/ to get a recent GCC on such a system. @MasterDuke17 I think you said you know ...
CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 ...
sudo yum -y install centos-release-scl sudo yum -y install devtoolset-9-gcc devtoolset-9-gcc-c++ scl enable devtoolset-9 bash For the initial compilation, it is recommended to use the build script build.sh, which checks if the required software is available on the local machine. ./build....
CUDA available: True numpy_random_seed: 2147483648 GPU 0,1: NVIDIA GeForce RTX 4090 CUDA_HOME: /usr/local/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 6.5.0-2ubuntu1~18.04) 6.5.0 20181026 PyTorch: 1.9.0+cu111 ...