0bce11f7a5
-- remove MDCG support on windows -- integrate fixes to nvrtc samples makefile and driver api samples makefiles
2.5 KiB
conjugateGradientMultiDeviceCG - conjugateGradient using MultiDevice Cooperative Groups
Description
This sample implements a conjugate gradient solver on multiple GPUs using Multi Device Cooperative Groups, also uses Unified Memory optimized using prefetching and usage hints.
Key Concepts
Unified Memory, Linear Algebra, Cooperative Groups, MultiDevice Cooperative Groups
Supported SM Architectures
Supported OSes
Linux
Supported CPU Architecture
x86_64, ppc64le
CUDA APIs involved
CUDA Runtime API
cudaMemAdvise, cudaMemPrefetchAsync, cudaLaunchCooperativeKernelMultiDevice, cudaStreamSynchronize, cudaOccupancyMaxActiveBlocksPerMultiprocessor
Dependencies needed to build/run
Prerequisites
Download and install the CUDA Toolkit 9.2 for your corresponding platform. Make sure the dependencies mentioned in Dependencies section above are installed.
Build and Run
Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
$ cd <sample_dir>
$ make
The samples makefiles can take advantage of certain options:
-
TARGET_ARCH= - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le. By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.
$ make TARGET_ARCH=x86_64
$ make TARGET_ARCH=ppc64le
See here for more details. -
dbg=1 - build with debug symbols
$ make dbg=1 -
SMS="A B ..." - override the SM architectures for which the sample will be built, where
"A B ..."is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, useSMS="50 60".$ make SMS="50 60" -
HOST_COMPILER=<host_compiler> - override the default g++ host compiler. See the Linux Installation Guide for a list of supported host compilers.
$ make HOST_COMPILER=g++