[petsc-users] Configuring PETSc for KNL

[murat keçeli]

How about replacing --download-fblaslapack with vendor specific
BLAS/LAPACK?

Murat

On Mon, Apr 3, 2017 at 2:45 PM, Richard Mills <richardtmills at gmail.com>
wrote:

> On Mon, Apr 3, 2017 at 12:24 PM, Zhang, Hong <hongzhang at anl.gov> wrote:
>
>>
>> On Apr 3, 2017, at 1:44 PM, Justin Chang <jychang48 at gmail.com> wrote:
>>
>> Richard,
>>
>> This is what my job script looks like:
>>
>> #!/bin/bash
>> #SBATCH -N 16
>> #SBATCH -C knl,quad,flat
>> #SBATCH -p regular
>> #SBATCH -J knlflat1024
>> #SBATCH -L SCRATCH
>> #SBATCH -o knlflat1024.o%j
>> #SBATCH --mail-type=ALL
>> #SBATCH --mail-user=jychang48 at gmail.com
>> #SBATCH -t 00:20:00
>>
>> #run the application:
>> cd $SCRATCH/Icesheet
>> sbcast --compress=lz4 ./ex48cori /tmp/ex48cori
>> srun -n 1024 -c 4 --cpu_bind=cores numactl -p 1 /tmp/ex48cori -M 128 -N
>> 128 -P 16 -thi_mat_type baij -pc_type mg -mg_coarse_pc_type gamg -da_refine
>> 1
>>
>>
>> Maybe it is a typo. It should be numactl -m 1.
>>
>
> "-p 1" will also work.  "-p" means to "prefer" NUMA node 1 (the MCDRAM),
> whereas "-m" means to use only NUMA node 1.  In the former case, MCDRAM
> will be used for allocations until the available memory there has been
> exhausted, and then things will spill over into the DRAM.  One would think
> that "-m" would be better for doing performance studies, but on systems
> where the nodes have swap space enabled, you can get terrible performance
> if your code's working set exceeds the size of the MCDRAM, as the system
> will obediently obey your wishes to not use the DRAM and go straight to the
> swap disk!  I assume the Cori nodes don't have swap space, though I could
> be wrong.
>
>
>> According to the NERSC info pages, they say to add the "numactl" if using
>> flat mode. Previously I tried cache mode but the performance seems to be
>> unaffected.
>>
>>
>> Using cache mode should give similar performance as using flat mode with
>> the numactl option. But both approaches should be significant faster than
>> using flat mode without the numactl option. I usually see over 3X speedup.
>> You can also do such comparison to see if the high-bandwidth memory is
>> working properly.
>>
>> I also comparerd 256 haswell nodes vs 256 KNL nodes and haswell is nearly
>> 4-5x faster. Though I suspect this drastic change has much to do with the
>> initial coarse grid size now being extremely small.
>>
>> I think you may be right about why you see such a big difference.  The
> KNL nodes need enough work to be able to use the SIMD lanes effectively.
> Also, if your problem gets small enough, then it's going to be able to fit
> in the Haswell's L3 cache.  Although KNL has MCDRAM and this delivers *a
> lot* more memory bandwidth than the DDR4 memory, it will deliver a lot less
> bandwidth than the Haswell's L3.
>
>> I'll give the COPTFLAGS a try and see what happens
>>
>>
>> Make sure to use --with-memalign=64 for data alignment when configuring
>> PETSc.
>>
>
> Ah, yes, I forgot that.  Thanks for mentioning it, Hong!
>
>
>> The option -xMIC-AVX512 would improve the vectorization performance. But
>> it may cause problems for the MPIBAIJ format for some unknown reason.
>> MPIAIJ should work fine with this option.
>>
>
> Hmm.  Try both, and, if you see worse performance with MPIBAIJ, let us
> know and I'll try to figure this out.
>
> --Richard
>
>
>>
>> Hong (Mr.)
>>
>> Thanks,
>> Justin
>>
>> On Mon, Apr 3, 2017 at 1:36 PM, Richard Mills <richardtmills at gmail.com>
>> wrote:
>>
>>> Hi Justin,
>>>
>>> How is the MCDRAM (on-package "high-bandwidth memory") configured for
>>> your KNL runs?  And if it is in "flat" mode, what are you doing to ensure
>>> that you use the MCDRAM?  Doing this wrong seems to be one of the most
>>> common reasons for unexpected poor performance on KNL.
>>>
>>> I'm not that familiar with the environment on Cori, but I think that if
>>> you are building for KNL, you should add "-xMIC-AVX512" to your compiler
>>> flags to explicitly instruct the compiler to use the AVX512 instruction
>>> set.  I usually use something along the lines of
>>>
>>>   'COPTFLAGS=-g -O3 -fp-model fast -xMIC-AVX512'
>>>
>>> (The "-g" just adds symbols, which make the output from performance
>>> profiling tools much more useful.)
>>>
>>> That said, I think that if you are comparing 1024 Haswell cores vs. 1024
>>> KNL cores (so double the number of Haswell nodes), I'm not surprised that
>>> the simulations are almost twice as fast using the Haswell nodes.  Keep in
>>> mind that individual KNL cores are much less powerful than an individual
>>> Haswell node.  You are also using roughly twice the power footprint (dual
>>> socket Haswell node should be roughly equivalent to a KNL node, I
>>> believe).  How do things look on when you compare equal nodes?
>>>
>>> Cheers,
>>> Richard
>>>
>>> On Mon, Apr 3, 2017 at 11:13 AM, Justin Chang <jychang48 at gmail.com>
>>> wrote:
>>>
>>>> Hi all,
>>>>
>>>> On NERSC's Cori I have the following configure options for PETSc:
>>>>
>>>> ./configure --download-fblaslapack --with-cc=cc
>>>> --with-clib-autodetect=0 --with-cxx=CC --with-cxxlib-autodetect=0
>>>> --with-debugging=0 --with-fc=ftn --with-fortranlib-autodetect=0
>>>> --with-mpiexec=srun --with-64-bit-indices=1 COPTFLAGS=-O3 CXXOPTFLAGS=-O3
>>>> FOPTFLAGS=-O3 PETSC_ARCH=arch-cori-opt
>>>>
>>>> Where I swapped out the default Intel programming environment with that
>>>> of Cray (e.g., 'module switch PrgEnv-intel/6.0.3 PrgEnv-cray/6.0.3'). I
>>>> want to document the performance difference between Cori's Haswell and KNL
>>>> processors.
>>>>
>>>> When I run a PETSc example like SNES ex48 on 1024 cores (32 Haswell and
>>>> 16 KNL nodes), the simulations are almost twice as fast on Haswell nodes.
>>>> Which leads me to suspect that I am not doing something right for KNL. Does
>>>> anyone know what are some "optimal" configure options for running PETSc on
>>>> KNL?
>>>>
>>>> Thanks,
>>>> Justin
>>>>
>>>
>>>
>>
>>
>
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