| commit | 42bff7ad39de3eb520cb20ab27f51ed816935edc | [log] [tgz] |
|---|---|---|
| author | Prashanth Swaminathan <40780424+prashanthswami@users.noreply.github.com> | Sat Jan 06 01:17:27 2024 |
| committer | GitHub <noreply@github.com> | Sat Jan 06 01:17:27 2024 |
| tree | 8144d604fefbdffe0b2b14a99eab1389c8ac1d87 | |
| parent | 313524ab20d2041854af8ad07bf726ddd485d258 [diff] |
Add .clang-format to enforce project style (#204) * Add .clang-format to enforce project style The settings here match the current settings for the pytorch/pytorch project, with the exception that 8-character-width tabs are preferred in place of spaces. * Mass reformat of all .c and .h files Now that we have a clang-format file defined, clean up all usages once. * Enable clang-format-check workflow Enforce clang-format consistency on all new changes.
cpuinfo is a library to detect essential for performance optimization information about host CPU.
Log processor name:
cpuinfo_initialize(); printf("Running on %s CPU\n", cpuinfo_get_package(0)->name);
Detect if target is a 32-bit or 64-bit ARM system:
#if CPUINFO_ARCH_ARM || CPUINFO_ARCH_ARM64 /* 32-bit ARM-specific code here */ #endif
Check if the host CPU supports ARM NEON
cpuinfo_initialize(); if (cpuinfo_has_arm_neon()) { neon_implementation(arguments); }
Check if the host CPU supports x86 AVX
cpuinfo_initialize(); if (cpuinfo_has_x86_avx()) { avx_implementation(arguments); }
Check if the thread runs on a Cortex-A53 core
cpuinfo_initialize(); switch (cpuinfo_get_current_core()->uarch) { case cpuinfo_uarch_cortex_a53: cortex_a53_implementation(arguments); break; default: generic_implementation(arguments); break; }
Get the size of level 1 data cache on the fastest core in the processor (e.g. big core in big.LITTLE ARM systems):
cpuinfo_initialize(); const size_t l1_size = cpuinfo_get_processor(0)->cache.l1d->size;
Pin thread to cores sharing L2 cache with the current core (Linux or Android)
cpuinfo_initialize(); cpu_set_t cpu_set; CPU_ZERO(&cpu_set); const struct cpuinfo_cache* current_l2 = cpuinfo_get_current_processor()->cache.l2; for (uint32_t i = 0; i < current_l2->processor_count; i++) { CPU_SET(cpuinfo_get_processor(current_l2->processor_start + i)->linux_id, &cpu_set); } pthread_setaffinity_np(pthread_self(), sizeof(cpu_set_t), &cpu_set);
If you would like to provide your project's build environment with the necessary compiler and linker flags in a portable manner, the library by default when built enables CPUINFO_BUILD_PKG_CONFIG and will generate a pkg-config manifest (libcpuinfo.pc). Here are several examples of how to use it:
If you used your distro's package manager to install the library, you can verify that it is available to your build environment like so:
$ pkg-config --cflags --libs libcpuinfo -I/usr/include/x86_64-linux-gnu/ -L/lib/x86_64-linux-gnu/ -lcpuinfo
If you have installed the library from source into a non-standard prefix, pkg-config may need help finding it:
$ PKG_CONFIG_PATH="/home/me/projects/cpuinfo/prefix/lib/pkgconfig/:$PKG_CONFIG_PATH" pkg-config --cflags --libs libcpuinfo -I/home/me/projects/cpuinfo/prefix/include -L/home/me/projects/cpuinfo/prefix/lib -lcpuinfo
To use with the GNU Autotools include the following snippet in your project's configure.ac:
# CPU INFOrmation library... PKG_CHECK_MODULES( [libcpuinfo], [libcpuinfo], [], [AC_MSG_ERROR([libcpuinfo missing...])]) YOURPROJECT_CXXFLAGS="$YOURPROJECT_CXXFLAGS $libcpuinfo_CFLAGS" YOURPROJECT_LIBS="$YOURPROJECT_LIBS $libcpuinfo_LIBS"
To use with Meson you just need to add dependency('libcpuinfo') as a dependency for your executable.
project( 'MyCpuInfoProject', 'cpp', meson_version: '>=0.55.0' ) executable( 'MyCpuInfoExecutable', sources: 'main.cpp', dependencies: dependency('libcpuinfo') )
This project can be built using Bazel.
You can also use this library as a dependency to your Bazel project. Add to the WORKSPACE file:
load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository") git_repository( name = "org_pytorch_cpuinfo", branch = "master", remote = "https://github.com/Vertexwahn/cpuinfo.git", )
And to your BUILD file:
cc_binary( name = "cpuinfo_test", srcs = [ # ... ], deps = [ "@org_pytorch_cpuinfo//:cpuinfo", ], )
To use with CMake use the FindPkgConfig module. Here is an example:
cmake_minimum_required(VERSION 3.6) project("MyCpuInfoProject") find_package(PkgConfig) pkg_check_modules(CpuInfo REQUIRED IMPORTED_TARGET libcpuinfo) add_executable(${PROJECT_NAME} main.cpp) target_link_libraries(${PROJECT_NAME} PkgConfig::CpuInfo)
To use within a vanilla makefile, you can call pkg-config directly to supply compiler and linker flags using shell substitution.
CFLAGS=-g3 -Wall -Wextra -Werror ... LDFLAGS=-lfoo ... ... CFLAGS+= $(pkg-config --cflags libcpuinfo) LDFLAGS+= $(pkg-config --libs libcpuinfo)
/proc/cpuinfo on ARMro.chipname, ro.board.platform, ro.product.board, ro.mediatek.platform, ro.arch properties (Android)dmesg) on ARM Linux/proc/cpuinfo on 32-bit ARM EABI (Linux)FPSID and WCID registers (32-bit ARM)getauxval (Linux/ARM)/proc/self/auxv (Android/ARM)/proc/cpuinfo (Linux/pre-ARMv7)sysctlbyname (Mach)typology directories (ARM/Linux)cache directories (Linux)GetLogicalProcessorInformationEx on ARM64 Windows/proc/cpuinfo (Linux)host_info (Mach)GetLogicalProcessorInformationEx (Windows)