Skip to content
forked from davidrohr/hpl-gpu

High Performance Linpack for GPUs (Using OpenCL, CUDA, CAL)

License

Notifications You must be signed in to change notification settings

ddemidov/hpl-gpu

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

==============================================================
 High Performance Computing Linpack Benchmark (HPL-GPU)
 HPL-GPU - 1.2 - 2015
==============================================================

 This is a largely rewritten version of the traditional High
 Performance Linpack as published on netlib.org. It has been
 modified to make use of modern multi-core CPUs, enhanced
 lookahead and a high performance DGEMM for AMD GPUs. It can
 use AMD CAL, OpenCL, and CUDA as GPU backend.

 See http://code.compeng.uni-frankfurt.de/projects/hpl for 
 detailed and up to date informaion.


 Installation
 ------------
 This software requires the CALDGEMM library available from
 http://code.compeng.uni-frankfurt.de/projects/caldgemm
 HPL-GPU assumes a link to caldgemm inside its top directory
 and this link must be called caldgemm.
 CALDGEMM provides backends for CAL, OPENCL, CUDA, CPU.
 The default is OpenCL and OpenCL is in the following assumed.
 For compiling CALDGEMM, in principle, you only have to select
 the desirect backends in config.options.mak that ships with
 CALDGEMM and compile it.

 Both, HPL-GPU and CALDGEMM require a BLAS library. Supported
 BLAS libraries include Intel MKL, GotoBLAS2, and AMD ACML.
 The default library is MKL, and MKL is assumed in the
 following.

 HPL-GPU requires Intel TBB. It will usually download and
 compile TBB automatically during HPl-GPU compilation.

 For running HPL-GPU on multiple-nodes, you need an MPI
 library, by default OpenMPI, which is assumed in the README.

 You need to set the following environment variables.

 export AMDAPPSDKROOT=[Root of AMD APP SDK]
 export OPENMPIPATH=[Install Path of OpenMPI]
 export MKL_PATH=[Install Path of Intel MKL]
 export ICC_PATH=[Install Path of Intel Compiler (for libs)]

 In addition, we suggest the following settings:
 export GPU_FORCE_64BIT_PTR=1 (Use 64Bit Ptrs on AMD GPU)
 export GPU_NUM_COMPUTE_RINGS=1 (Setting for AMD GPUs)
 export DISPLAY=:0 (For headless system with X-Server needed)

 In order to allow allocation of large amount of pinned
 memory you need to set the following limits in Linux:
 ulimit -v unlimited
 ulimit -m unlimited
 ulimit -l unlimited

 In addition, it is strongly suggested to disable the Intel
 HyperThreading feature if available.

 For compiling HPL-GPU after the above prerequisites are met,
 copy Make.Generic and Make.Generic.Options from the setup
 directory in its top directory. Principally all relevant
 options can be controlled in Make.Generic.Options. If you
 need to change paths for includes / libraries, you have to
 check Make.Generic.

 run ./build.sh to start compilation.

 In order to tune HPL-GPU, have a look at the comments in
 Make.Generic.Options. A detailed description and some
 tuning comments for CALDGEMM are available in the CALDGEMM
 README file, and HPL compile time options are listed in
 setup/readme. A detailed HPL-GPU tuning guide is available
 in the TUNING file that ships with this software.


 Newest Version
 --------------
 The newest version of HPL-GPU is available at
 http://code.compeng.uni-frankfurt.de/projects/hpl


 Information
 -----------
 See the wiki at
 http://code.compeng.uni-frankfurt.de/projects/hpl/wiki


 License
 -------
 This software is licensed partly under GPL and partly under
 BSD license. See COPYING for details.
 

 Bugs
 ----
 Are tracked at
 http://code.compeng.uni-frankfurt.de/projects/hpl/issues

=============================================================

About

High Performance Linpack for GPUs (Using OpenCL, CUDA, CAL)

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C 89.7%
  • C++ 9.5%
  • Other 0.8%