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
||
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