Ghislain Durif
2017-Aug-21 14:13 UTC
[Rd] Control multi-threading in standard matrix product
Hi Tomas, Thanks for your answer. Indeed, I checked and my R-3.4.1 installed from the ubuntu repository use 'libopenblasp-r0.2.18.so' while my R-3.3.2 that I did compiled on my machine use 'libRblas.so' which explain the difference of behavior. I will use RhpcBLASctl to avoid issue when combining matrix product and other multi-threading package. Maybe this point regarding multi-threading with BLAS could be added in the R doc. Thanks again, Best, Ghislain Ghislain Durif -------------------------- Research engineer THOTH TEAM INRIA Grenoble Alpes (France) Le 21/08/2017 ? 15:53, Tomas Kalibera a ?crit :> Hi Ghislain, > > I think you might be comparing two versions of R with different BLAS > implementations, one that is single threaded (is your 3.3.2 used with > reference blas?) and one that is multi threaded (3.4.1 with openblas). > Could you check with "perf"? E.g. run your benchmark with "perf > record" in both cases and you should see the names of the hot BLAS > functions and this should reveal the BLAS implementation (look for > dgemm). > > In Ubuntu, if you install R from the package system, whenever you run > it it will use the BLAS currently installed via the package system. > However if you build R from source on Ubuntu, by default, it will use > the reference BLAS which is distributed with R. Section "Linear > algebra" of "R Installation and Administration" has details on how to > build R with different BLAS/LAPACK implementations. > > Sadly there is no standard way to specify the number of BLAS worker > threads. RhpcBLASctl has specific code for several existing > implementations, but R itself does not attempt to control BLAS multi > threading in any way. It is expected the user/system administrator > will configure their BLAS implementation of choice to use the number > of threads they need. A similar problem exists in other internally > multi-threaded third-party libraries, used by packages - R cannot > control how many threads they run. > > Best > Tomas > > On 08/21/2017 02:55 PM, Ghislain Durif wrote: >> Dear R Core Team, >> >> I wish to report what can be viewed as a bug or at least a strange >> behavior in R-3.4.1. I ask my question here (as recommended on >> https://www.r-project.org/bugs.html) since I am not member of the R's >> Bugzilla. >> >> When running 'R --vanilla' from the command line, the standard matrix >> product is by default based on BLAS and multi-threaded on all cores >> available on the machine, c.f. following examples: >> >> n=10000 >> p=1000 >> q=5000 >> A = matrix(runif(n*p),nrow=n, ncol=p) >> B = matrix(runif(p*q),nrow=p, ncol=q) >> C = A %*% B # multi-threaded matrix product >> >> >> However, the default behavior to use all available cores can be an >> issue, especially on shared computing resources or when the matrix >> product is used in parallelized section of codes (for instance with >> 'mclapply' from the 'parallel' package). For instance, the default >> matrix product is single-threaded in R-3.3.2 (I ran a test on my >> machine), this new features will deeply affect the behavior of existing >> R packages that use other multi-threading solutions. >> >> Thanks to this stackoverflow question >> (https://stackoverflow.com/questions/45794290/in-r-how-to-control-multi-threading-in-blas-parallel-matrix-product), >> >> I now know that it is possible to control the number of BLAS threads >> thanks to the package 'RhpcBLASctl'. However, being able to control the >> number of threads should maybe not require to use an additional package. >> >> In addition, the doc 'matmult' does not mention this point, it points to >> the 'options' doc page and especially the 'matprod' section, in which >> the multi-threading is not discussed. >> >> >> Here is the results of the 'sessionInfo()' function on my machine for >> R-3.4.1: >> R version 3.4.1 (2017-06-30) >> Platform: x86_64-pc-linux-gnu (64-bit) >> Running under: Ubuntu 16.04.3 LTS >> >> Matrix products: default >> BLAS: /usr/lib/openblas-base/libblas.so.3 >> LAPACK: /usr/lib/libopenblasp-r0.2.18.so >> >> locale: >> [1] LC_CTYPE=fr_FR.utf8 LC_NUMERIC=C >> [3] LC_TIME=fr_FR.utf8 LC_COLLATE=fr_FR.utf8 >> [5] LC_MONETARY=fr_FR.utf8 LC_MESSAGES=fr_FR.utf8 >> [7] LC_PAPER=fr_FR.utf8 LC_NAME=C >> [9] LC_ADDRESS=C LC_TELEPHONE=C >> [11] LC_MEASUREMENT=fr_FR.utf8 LC_IDENTIFICATION=C >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> >> loaded via a namespace (and not attached): >> [1] compiler_3.4.1 >> >> >> >> and for R-3.3.2: >> R version 3.3.2 (2016-10-31) >> Platform: x86_64-pc-linux-gnu (64-bit) >> Running under: Ubuntu 16.04.3 LTS >> >> locale: >> [1] LC_CTYPE=fr_FR.utf8 LC_NUMERIC=C >> [3] LC_TIME=fr_FR.utf8 LC_COLLATE=fr_FR.utf8 >> [5] LC_MONETARY=fr_FR.utf8 LC_MESSAGES=fr_FR.utf8 >> [7] LC_PAPER=fr_FR.utf8 LC_NAME=C >> [9] LC_ADDRESS=C LC_TELEPHONE=C >> [11] LC_MEASUREMENT=fr_FR.utf8 LC_IDENTIFICATION=C >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> >> >> Thanks in advance, >> Best regards >> || >> >
Hi Ghislain, The documentation at https://cran.r-project.org/doc/manuals/r-release/R-admin.html#BLAS provides a fair bit of information. What specifically would you like to see added? Best, Ista On Mon, Aug 21, 2017 at 10:13 AM, Ghislain Durif <ghislain.durif at inria.fr> wrote:> Hi Tomas, > > Thanks for your answer. > > Indeed, I checked and my R-3.4.1 installed from the ubuntu repository use > 'libopenblasp-r0.2.18.so' while my R-3.3.2 that I did compiled on my machine > use 'libRblas.so' which explain the difference of behavior. > > I will use RhpcBLASctl to avoid issue when combining matrix product and > other multi-threading package. > > Maybe this point regarding multi-threading with BLAS could be added in the R > doc. > > Thanks again, > Best, > > Ghislain > > Ghislain Durif > -------------------------- > Research engineer THOTH TEAM > INRIA Grenoble Alpes (France) > > Le 21/08/2017 ? 15:53, Tomas Kalibera a ?crit : >> >> Hi Ghislain, >> >> I think you might be comparing two versions of R with different BLAS >> implementations, one that is single threaded (is your 3.3.2 used with >> reference blas?) and one that is multi threaded (3.4.1 with openblas). Could >> you check with "perf"? E.g. run your benchmark with "perf record" in both >> cases and you should see the names of the hot BLAS functions and this should >> reveal the BLAS implementation (look for dgemm). >> >> In Ubuntu, if you install R from the package system, whenever you run it >> it will use the BLAS currently installed via the package system. However if >> you build R from source on Ubuntu, by default, it will use the reference >> BLAS which is distributed with R. Section "Linear algebra" of "R >> Installation and Administration" has details on how to build R with >> different BLAS/LAPACK implementations. >> >> Sadly there is no standard way to specify the number of BLAS worker >> threads. RhpcBLASctl has specific code for several existing implementations, >> but R itself does not attempt to control BLAS multi threading in any way. It >> is expected the user/system administrator will configure their BLAS >> implementation of choice to use the number of threads they need. A similar >> problem exists in other internally multi-threaded third-party libraries, >> used by packages - R cannot control how many threads they run. >> >> Best >> Tomas >> >> On 08/21/2017 02:55 PM, Ghislain Durif wrote: >>> >>> Dear R Core Team, >>> >>> I wish to report what can be viewed as a bug or at least a strange >>> behavior in R-3.4.1. I ask my question here (as recommended on >>> https://www.r-project.org/bugs.html) since I am not member of the R's >>> Bugzilla. >>> >>> When running 'R --vanilla' from the command line, the standard matrix >>> product is by default based on BLAS and multi-threaded on all cores >>> available on the machine, c.f. following examples: >>> >>> n=10000 >>> p=1000 >>> q=5000 >>> A = matrix(runif(n*p),nrow=n, ncol=p) >>> B = matrix(runif(p*q),nrow=p, ncol=q) >>> C = A %*% B # multi-threaded matrix product >>> >>> >>> However, the default behavior to use all available cores can be an >>> issue, especially on shared computing resources or when the matrix >>> product is used in parallelized section of codes (for instance with >>> 'mclapply' from the 'parallel' package). For instance, the default >>> matrix product is single-threaded in R-3.3.2 (I ran a test on my >>> machine), this new features will deeply affect the behavior of existing >>> R packages that use other multi-threading solutions. >>> >>> Thanks to this stackoverflow question >>> >>> (https://stackoverflow.com/questions/45794290/in-r-how-to-control-multi-threading-in-blas-parallel-matrix-product), >>> I now know that it is possible to control the number of BLAS threads >>> thanks to the package 'RhpcBLASctl'. However, being able to control the >>> number of threads should maybe not require to use an additional package. >>> >>> In addition, the doc 'matmult' does not mention this point, it points to >>> the 'options' doc page and especially the 'matprod' section, in which >>> the multi-threading is not discussed. >>> >>> >>> Here is the results of the 'sessionInfo()' function on my machine for >>> R-3.4.1: >>> R version 3.4.1 (2017-06-30) >>> Platform: x86_64-pc-linux-gnu (64-bit) >>> Running under: Ubuntu 16.04.3 LTS >>> >>> Matrix products: default >>> BLAS: /usr/lib/openblas-base/libblas.so.3 >>> LAPACK: /usr/lib/libopenblasp-r0.2.18.so >>> >>> locale: >>> [1] LC_CTYPE=fr_FR.utf8 LC_NUMERIC=C >>> [3] LC_TIME=fr_FR.utf8 LC_COLLATE=fr_FR.utf8 >>> [5] LC_MONETARY=fr_FR.utf8 LC_MESSAGES=fr_FR.utf8 >>> [7] LC_PAPER=fr_FR.utf8 LC_NAME=C >>> [9] LC_ADDRESS=C LC_TELEPHONE=C >>> [11] LC_MEASUREMENT=fr_FR.utf8 LC_IDENTIFICATION=C >>> >>> attached base packages: >>> [1] stats graphics grDevices utils datasets methods base >>> >>> loaded via a namespace (and not attached): >>> [1] compiler_3.4.1 >>> >>> >>> >>> and for R-3.3.2: >>> R version 3.3.2 (2016-10-31) >>> Platform: x86_64-pc-linux-gnu (64-bit) >>> Running under: Ubuntu 16.04.3 LTS >>> >>> locale: >>> [1] LC_CTYPE=fr_FR.utf8 LC_NUMERIC=C >>> [3] LC_TIME=fr_FR.utf8 LC_COLLATE=fr_FR.utf8 >>> [5] LC_MONETARY=fr_FR.utf8 LC_MESSAGES=fr_FR.utf8 >>> [7] LC_PAPER=fr_FR.utf8 LC_NAME=C >>> [9] LC_ADDRESS=C LC_TELEPHONE=C >>> [11] LC_MEASUREMENT=fr_FR.utf8 LC_IDENTIFICATION=C >>> >>> attached base packages: >>> [1] stats graphics grDevices utils datasets methods base >>> >>> >>> Thanks in advance, >>> Best regards >>> || >>> >> > > ______________________________________________ > R-devel at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel
Ghislain Durif
2017-Aug-21 15:40 UTC
[Rd] Control multi-threading in standard matrix product
Hi Ista,
Maybe a little comment in the 'matmult {base}' doc page or on the
'options {base}' in the field 'matprod' would be useful to
remind users
to be cautious regarding BLAS multi-threading?
I understand why this is a BLAS related issue and not directly an R
related issue. Nonetheless, my concern was for non-advanced R users,
that may don't even know what BLAS is. For instance, I have a package on
the CRAN that use 'mclapply' from the 'parallel' package and the
multi-threading from BLAS (when using OpenBLAS) totally messes up with
my multi-threading (regarding computing performance). Hence, I think
that some of the users of my package, if not aware of that, may
encounter severe issues, especially because this package is mainly used
to analyse bioinformatics data, which requires important computing
resources.
Anyway, it works well on my machine now, and I will modify my package to
ensure that users won't encounter this case of "multi"
multi-threading.
Thanks again,
Best,
Ghislain
Ghislain Durif
--------------------------
Research engineer THOTH TEAM
INRIA Grenoble Alpes (France)
Le 21/08/2017 ? 17:28, Ista Zahn a ?crit :> Hi Ghislain,
>
> The documentation at
> https://cran.r-project.org/doc/manuals/r-release/R-admin.html#BLAS
> provides a fair bit of information. What specifically would you like
> to see added?
>
> Best,
> Ista
>
> On Mon, Aug 21, 2017 at 10:13 AM, Ghislain Durif
> <ghislain.durif at inria.fr> wrote:
>> Hi Tomas,
>>
>> Thanks for your answer.
>>
>> Indeed, I checked and my R-3.4.1 installed from the ubuntu repository
use
>> 'libopenblasp-r0.2.18.so' while my R-3.3.2 that I did compiled
on my machine
>> use 'libRblas.so' which explain the difference of behavior.
>>
>> I will use RhpcBLASctl to avoid issue when combining matrix product and
>> other multi-threading package.
>>
>> Maybe this point regarding multi-threading with BLAS could be added in
the R
>> doc.
>>
>> Thanks again,
>> Best,
>>
>> Ghislain
>>
>> Ghislain Durif
>> --------------------------
>> Research engineer THOTH TEAM
>> INRIA Grenoble Alpes (France)
>>
>> Le 21/08/2017 ? 15:53, Tomas Kalibera a ?crit :
>>> Hi Ghislain,
>>>
>>> I think you might be comparing two versions of R with different
BLAS
>>> implementations, one that is single threaded (is your 3.3.2 used
with
>>> reference blas?) and one that is multi threaded (3.4.1 with
openblas). Could
>>> you check with "perf"? E.g. run your benchmark with
"perf record" in both
>>> cases and you should see the names of the hot BLAS functions and
this should
>>> reveal the BLAS implementation (look for dgemm).
>>>
>>> In Ubuntu, if you install R from the package system, whenever you
run it
>>> it will use the BLAS currently installed via the package system.
However if
>>> you build R from source on Ubuntu, by default, it will use the
reference
>>> BLAS which is distributed with R. Section "Linear
algebra" of "R
>>> Installation and Administration" has details on how to build R
with
>>> different BLAS/LAPACK implementations.
>>>
>>> Sadly there is no standard way to specify the number of BLAS worker
>>> threads. RhpcBLASctl has specific code for several existing
implementations,
>>> but R itself does not attempt to control BLAS multi threading in
any way. It
>>> is expected the user/system administrator will configure their BLAS
>>> implementation of choice to use the number of threads they need. A
similar
>>> problem exists in other internally multi-threaded third-party
libraries,
>>> used by packages - R cannot control how many threads they run.
>>>
>>> Best
>>> Tomas
>>>
>>> On 08/21/2017 02:55 PM, Ghislain Durif wrote:
>>>> Dear R Core Team,
>>>>
>>>> I wish to report what can be viewed as a bug or at least a
strange
>>>> behavior in R-3.4.1. I ask my question here (as recommended on
>>>> https://www.r-project.org/bugs.html) since I am not member of
the R's
>>>> Bugzilla.
>>>>
>>>> When running 'R --vanilla' from the command line, the
standard matrix
>>>> product is by default based on BLAS and multi-threaded on all
cores
>>>> available on the machine, c.f. following examples:
>>>>
>>>> n=10000
>>>> p=1000
>>>> q=5000
>>>> A = matrix(runif(n*p),nrow=n, ncol=p)
>>>> B = matrix(runif(p*q),nrow=p, ncol=q)
>>>> C = A %*% B # multi-threaded matrix product
>>>>
>>>>
>>>> However, the default behavior to use all available cores can be
an
>>>> issue, especially on shared computing resources or when the
matrix
>>>> product is used in parallelized section of codes (for instance
with
>>>> 'mclapply' from the 'parallel' package). For
instance, the default
>>>> matrix product is single-threaded in R-3.3.2 (I ran a test on
my
>>>> machine), this new features will deeply affect the behavior of
existing
>>>> R packages that use other multi-threading solutions.
>>>>
>>>> Thanks to this stackoverflow question
>>>>
>>>>
(https://stackoverflow.com/questions/45794290/in-r-how-to-control-multi-threading-in-blas-parallel-matrix-product),
>>>> I now know that it is possible to control the number of BLAS
threads
>>>> thanks to the package 'RhpcBLASctl'. However, being
able to control the
>>>> number of threads should maybe not require to use an additional
package.
>>>>
>>>> In addition, the doc 'matmult' does not mention this
point, it points to
>>>> the 'options' doc page and especially the
'matprod' section, in which
>>>> the multi-threading is not discussed.
>>>>
>>>>
>>>> Here is the results of the 'sessionInfo()' function on
my machine for
>>>> R-3.4.1:
>>>> R version 3.4.1 (2017-06-30)
>>>> Platform: x86_64-pc-linux-gnu (64-bit)
>>>> Running under: Ubuntu 16.04.3 LTS
>>>>
>>>> Matrix products: default
>>>> BLAS: /usr/lib/openblas-base/libblas.so.3
>>>> LAPACK: /usr/lib/libopenblasp-r0.2.18.so
>>>>
>>>> locale:
>>>> [1] LC_CTYPE=fr_FR.utf8 LC_NUMERIC=C
>>>> [3] LC_TIME=fr_FR.utf8 LC_COLLATE=fr_FR.utf8
>>>> [5] LC_MONETARY=fr_FR.utf8 LC_MESSAGES=fr_FR.utf8
>>>> [7] LC_PAPER=fr_FR.utf8 LC_NAME=C
>>>> [9] LC_ADDRESS=C LC_TELEPHONE=C
>>>> [11] LC_MEASUREMENT=fr_FR.utf8 LC_IDENTIFICATION=C
>>>>
>>>> attached base packages:
>>>> [1] stats graphics grDevices utils datasets methods
base
>>>>
>>>> loaded via a namespace (and not attached):
>>>> [1] compiler_3.4.1
>>>>
>>>>
>>>>
>>>> and for R-3.3.2:
>>>> R version 3.3.2 (2016-10-31)
>>>> Platform: x86_64-pc-linux-gnu (64-bit)
>>>> Running under: Ubuntu 16.04.3 LTS
>>>>
>>>> locale:
>>>> [1] LC_CTYPE=fr_FR.utf8 LC_NUMERIC=C
>>>> [3] LC_TIME=fr_FR.utf8 LC_COLLATE=fr_FR.utf8
>>>> [5] LC_MONETARY=fr_FR.utf8 LC_MESSAGES=fr_FR.utf8
>>>> [7] LC_PAPER=fr_FR.utf8 LC_NAME=C
>>>> [9] LC_ADDRESS=C LC_TELEPHONE=C
>>>> [11] LC_MEASUREMENT=fr_FR.utf8 LC_IDENTIFICATION=C
>>>>
>>>> attached base packages:
>>>> [1] stats graphics grDevices utils datasets methods
base
>>>>
>>>>
>>>> Thanks in advance,
>>>> Best regards
>>>> ||
>>>>
>> ______________________________________________
>> R-devel at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-devel
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