How to compile HPL-GPU: Difference between revisions
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== Overview == | == Overview == | ||
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* 왜 필요한가? - HPC 및 서버 환경에서 필수 개념 | * 왜 필요한가? - HPC 및 서버 환경에서 필수 개념 | ||
* 언제 사용하는가? - 서버 구성, 성능 튜닝, 문제 해결 시 | * 언제 사용하는가? - 서버 구성, 성능 튜닝, 문제 해결 시 | ||
== Purpose == | == Purpose == | ||
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* Scope: How to compile HPL-GPU의 개념, 사용법, 설정 | * Scope: How to compile HPL-GPU의 개념, 사용법, 설정 | ||
* Non-goals: 다른 주제로의 확장 | * Non-goals: 다른 주제로의 확장 | ||
== Key Concepts == | == Key Concepts == | ||
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| [[Linux]], [[Server]] | | [[Linux]], [[Server]] | ||
|} | |} | ||
== Detailed Explanation == | == Detailed Explanation == | ||
There are many combination to compile High Performance LINPACK (HPL) with different configurations such as different compiler, different basic linear algebra subprograms (BLAS), massage passing interface (MPI) libraries: for example | There are many combination to compile High Performance LINPACK (HPL) with different configurations such as different compiler, different basic linear algebra subprograms (BLAS), massage passing interface (MPI) libraries: for example | ||
* Which compiler + HPL + which Blas (OpenBLAS / Intel MKL / CuBLAS) + which MPI (OpenMPI, MPICH, Intel MPI) | * Which compiler + HPL + which Blas (OpenBLAS / Intel MKL / [[CuBLAS]]) + which MPI (OpenMPI, MPICH, Intel MPI) | ||
In this post, we are going to use GNU compiler, OpenBLAS, OpenMPI for HPL-GPU | In this post, we are going to use GNU compiler, OpenBLAS, OpenMPI for HPL-GPU | ||
* The build system is Intel Skylake CPU, 128GB Memory, [[NVIDIA GPUs|Nvidia GPUs]] on Ubuntu 20.04 | * The build system is Intel Skylake CPU, 128GB Memory, [[NVIDIA GPUs|Nvidia GPUs]] on Ubuntu 20.04 | ||
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ls ~/lib/OpenBLAS-0.3.23/lib | ls ~/lib/OpenBLAS-0.3.23/lib | ||
</syntaxhighlight>now, compiled OpenBLAS's library and header file is available ~/lib/OpenBLAS-0.3.23 | </syntaxhighlight>now, compiled OpenBLAS's library and header file is available ~/lib/OpenBLAS-0.3.23 | ||
== Best Practices == | == Best Practices == | ||
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* 공식 문서 참고 | * 공식 문서 참고 | ||
* 테스트 환경에서 먼저 검증 | * 테스트 환경에서 먼저 검증 | ||
== References == | == References == | ||
* [https://wiki.hpcmate.com How to compile HPL-GPU] | * [https://wiki.hpcmate.com How to compile HPL-GPU] | ||
== Related Pages == | == Related Pages == | ||
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* [[Hardware]] | * [[Hardware]] | ||
* [[Network]] | * [[Network]] | ||
[[Category:GPU]] | [[Category:GPU]] | ||
Latest revision as of 13:24, 2 October 2026
Overview
How to compile HPL-GPU에 대한 기술 문서입니다.
Summary
- 무엇인가? - How to compile HPL-GPU
- 왜 필요한가? - HPC 및 서버 환경에서 필수 개념
- 언제 사용하는가? - 서버 구성, 성능 튜닝, 문제 해결 시
Purpose
이 문서가 존재하는 이유
- Goal: How to compile HPL-GPU에 대한 기술 정보 제공
- Scope: How to compile HPL-GPU의 개념, 사용법, 설정
- Non-goals: 다른 주제로의 확장
Key Concepts
| Concept | Description | Related |
|---|---|---|
| How to compile HPL-GPU | HPC/서버 환경에서 중요한 기술 개념 | Linux, Server |
Detailed Explanation
There are many combination to compile High Performance LINPACK (HPL) with different configurations such as different compiler, different basic linear algebra subprograms (BLAS), massage passing interface (MPI) libraries: for example
- Which compiler + HPL + which Blas (OpenBLAS / Intel MKL / CuBLAS) + which MPI (OpenMPI, MPICH, Intel MPI)
In this post, we are going to use GNU compiler, OpenBLAS, OpenMPI for HPL-GPU
- The build system is Intel Skylake CPU, 128GB Memory, Nvidia GPUs on Ubuntu 20.04
- NVIDIA driver is ready and CUDA 12.0 has been installed and library can be found at /usr/local/cuda
- We are using OpenMPI, OpenBlas and hpl-2.0_FERMI_v15 as a ingredient, gcc version 10, g++ version 10 and gfortran version 10
_version=v0.3.23
FILE=$_version.tar.gz
wget http://github.com/xianyi/OpenBLAS/archive/$FILE
tar -xzvf $FILE
cd OpenBLAS-0.3.23
# OpenBLAS does not support f77, GCC or Intel are supported
# type make to detect the CPU automatically. or type make TARGET=xxx to set target CPU, e.g. make TARGET=NEHALEM. The full target list is in file TargetList.txt.
make
# To install the library, you can run "make PREFIX=/path/to/your/installation install".
mkdir -p /opt/hpcmate/home/lib/OpenBLAS-0.3.23
make PREFIX=/opt/hpcmate/home/lib/OpenBLAS-0.3.23 install
ls ~/lib/OpenBLAS-0.3.23/lib
now, compiled OpenBLAS's library and header file is available ~/lib/OpenBLAS-0.3.23
Best Practices
- 최신 버전 사용 권장
- 공식 문서 참고
- 테스트 환경에서 먼저 검증
References
Related Pages
Knowledge Graph
Related
→ CUDA → GPU → NVIDIA GPU → NVLink → AMD GPUs → MIG → NVIDIA GPUs → Tensor Core