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  • High Performance Computing 综述


    文章目录

    • Overview
      • Heterogeneous Computing
      • MPI (Message Passing Interface)
      • Concurrency
        • Multi-Processing
          • IPC
        • Multi-Threading
    • CPU
      • CPU Info
        • ARM CPU features
      • CPU Benchmark
        • Sysbench
        • htop
        • 压力测试
      • CPU Instructions & Intrinsics
        • Assembly
        • SIMD
          • Intel MMX & SSE
          • ARM NEON
          • Converter
      • OpenMP
      • OpenACC
      • Intel TBB
      • Intel IPP
    • GPU
      • GPU Benchmark
      • Platforms
      • Languages
        • OpenCL
        • CUDA
          • Thrust
    • DSP
    • Software Optimization

    Overview

    • cggos

      • hpc
      • multicore_gpu_programming
    • StreamHPC is a software development company in parallel software for many-core processors.

    • The Supercomputing Blog

    • FastC++: Coding Cpp Efficiently

    Heterogeneous Computing

    • Introduction to Parallel Computing

    MPI (Message Passing Interface)

    • MPI Forum: the standardization forum for MPI
    • Open MPI: Open Source High Performance Computing.

    Concurrency

    • task switching
    • hardware concurrency

    Multi-Processing

    IPC
    • Interprocess Communications (Microsoft)

    • Inter-Process Communication (IPC) Introduction and Sample Code

    Multi-Threading

    • POSIX C pthread
    • boost::thread
    • c++11 std::thread

    CPU

    • Intel® 64 and IA-32 Architectures Software Developer Manuals
    • Hotspots, FLOPS, and uOps: To-The-Metal CPU Optimization

    CPU Info

    8 commands to check cpu information on Linux:

    • /proc/cpuinfo: The /proc/cpuinfo file contains details about individual cpu cores.

    • lscpu: simply print the cpu hardware details in a user-friendly format

    • cpuid: fetches CPUID information about Intel and AMD x86 processors

    • nproc: just prints out the number of processing units available, note that the number of processing units might not always be the same as number of cores

    • dmidecode: displays some information about the cpu, which includes the socket type, vendor name and various flags

    • hardinfo: would produce a large report about many hardware parts, by reading files from the /proc directory

    • lshw -class processor: lshw by default shows information about various hardware parts, and the -class option can be used to pickup information about a specific hardware part

    • inxi: a script that uses other programs to generate a well structured easy to read report about various hardware components on the system

    ARM CPU features

    • Runtime detection of CPU features on an ARMv8-A CPU

    CPU Benchmark

    Sysbench

    Sysbench – Scriptable database and system performance benchmark, a cross-platform and multi-threaded benchmark tool

    sysbench --test=cpu --cpu-max-prime=20000 --num-threads=4 run
    
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    htop

    • htop - an interactive process viewer for Unix

    • htop explained - Explanation of everything you can see in htop/top on Linux

    压力测试

    https://www.tecmint.com/linux-cpu-load-stress-test-with-stress-ng-tool/

    cat /sys/class/thermal/thermal_zone0/temp
    
    # stress
    stress --cpu 4 --io 4 --vm 1 --vm-bytes 1G
    
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    CPU Instructions & Intrinsics

    • Compiler Intrinsics

    Assembly

    • x86 Assembly

    • winasm: The x86 Assembly community and official home of WinAsm Studio and HiEditor

    • Easy Code Visual assembly IDE

    • 0xAX/asm: Learning assembly for linux-x64

    SIMD

    Intel MMX & SSE
    • Intel Intrinsics Guide

    • SSE (Streaming SIMD Extentions)

      • C++ - Getting started with SSE
      • SSE - Vectorizing conditional code
      • SSE图像算法优化系列(cnblogs)
    ARM NEON

    Arm NEON technology is an advanced SIMD (single instruction multiple data) architecture extension for the Arm Cortex-A series and Cortex-R52 processors.

    • NEON Intrinsics Reference
    • ARM NEON Tutorial in C and Assembler
    • ARM NEON编程初探——一个简单的BGR888转YUV444实例详解

    Compiler Options:

    • test ARM NEON

      gcc -dM -E -x c /dev/null | grep -i -E "(SIMD|NEON|ARM)"
      
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    • Raspberry Pi 3 Model B

      • g++ options
        -std=c++11 -O3 -march=native -mfpu=neon-vfpv4 -mfloat-abi=softfp -ffast-math
        
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      • for the compilation error error: ‘vfmaq_f32’ was not declared in this scope, you might add the option -mfpu=neon-vfpv4 to enable __ARM_FEATURE_FMA in arm_neon.h

    Reference Books:

    • NEON Programmer’s Guide
    • ARM® NEON Intrinsics Reference
    Converter
    • jratcliff63367/sse2neon
    • From ARM NEON* to Intel® SSE - The Automatic Porting Solution, Tips and Tricks

    OpenMP

    The OpenMP API specification for parallel programming, an Application Program Interface (API) that may be used to explicitly direct multi-threaded, shared memory parallelism.

    OpenMP有两种常用的并行开发形式: 一是通过简单的 fork/join 对串行程序并行化,二是采用 单程序多数据 对串行程序并行化。

    • OpenMP Tutorials

    • OpenMP in a nutshell

    OpenMP in CMakeLists.txt:

    find_package(OpenMP)
    if (OPENMP_FOUND)
        set (CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
        set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
        set (CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} ${OpenMP_EXE_LINKER_FLAGS}")
    endif()
    
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    OpenACC

    OpenACC is a user-driven directive-based performance-portable parallel programming model designed for scientists and engineers interested in porting their codes to a wide-variety of heterogeneous HPC hardware platforms and architectures with significantly less programming effort than required with a low-level model.

    Intel TBB

    Intel Threading Building Blocks (TBB) lets you easily write parallel C++ programs that take full advantage of multicore performance, that are portable and composable, and that have future-proof scalability.

    Intel IPP

    GPU

    • GPU世界技术论坛
    • General-Purpose Computation on Graphics Hardware

    GPU Benchmark

    • For the Raspberry Pi GPU benchmark, use the OpenGL 2.1 test that comes with GeeXLab

    • msalvaris/gpu_monitor: Monitor your GPUs whether they are on a single computer or in a cluster

    • Benchmark Your Graphics Card On Linux

    watch -n 10 nvidia-smi       # 每隔10秒更新一下显卡
    
    # on Android
    watch -n 0.1 adb shell cat /sys/class/kgsl/kgsl-3d0/gpu_busy_percentage # 0.1s
    
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    Platforms

    • ARM MALI GPU

    • Nvidia GPU

    Languages

    • CUDA vs OpenCL: Which should I use?

    OpenCL

    OpenCL™ (Open Computing Language) is the open, royalty-free standard for cross-platform, parallel programming of diverse processors found in personal computers, servers, mobile devices and embedded platforms.

    • install OpenCL

      # required: Ubuntu 16.04, nvidia GPU and nvidia driver installed
      sudo apt-get install nvidia-prime nvidia-modprobe nvidia-opencl-dev
      sudo ln -s /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/local/lib/libOpenCL.so
      
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    • build program

      g++ main.cpp -lOpenCL
      
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    CUDA

    CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs).

    • CUDA Zone
    • ArchaeaSoftware/cudahandbook
    • CUDA for ARM Platforms is Now Available
    Thrust
    • Thrust
    • Thrust in CUDA Toolkit

    DSP

    Software Optimization

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  • 原文地址:https://blog.csdn.net/u011178262/article/details/126643661
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