benchmarkme fails #2
Description
I can't get this to run in a container. benchmarkmefails :(
sessionInfo(); library("benchmarkme"); benchmark_std(runs = 1)
R version 3.4.4 (2018-03-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.3 LTS
Matrix products: default
BLAS/LAPACK: /opt/intel/compilers_and_libraries_2018.2.199/linux/mkl/lib/intel64_lin/libmkl_rt.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_3.4.4
# Programming benchmarks (5 tests):
3,500,000 Fibonacci numbers calculation (vector calc): 0.867 (sec).
Grand common divisors of 1,000,000 pairs (recursion): 1.38 (sec).
Creation of a 3500x3500 Hilbert matrix (matrix calc): 0.66 (sec).
Creation of a 3000x3000 Toeplitz matrix (loops): 15.4 (sec).
Escoufier's method on a 60x60 matrix (mixed): 1.61 (sec).
# Matrix calculation benchmarks (5 tests):
Creation, transp., deformation of a 5000x5000 matrix: 1.15 (sec).
2500x2500 normal distributed random matrix ^1000: 0.659 (sec).
Sorting of 7,000,000 random values: 0.892 (sec).
2500x2500 cross-product matrix (b = a' * a): 0.992 (sec).
Error in solve(crossprod(a), crossprod(a, b)) :
the leading minor of order 1421 is not positive definite
Calls: benchmark_std ... bm_matrix_cal_lm -> system.time -> solve -> solve -> .Call
Timing stopped at: 1.064 0.032 0.553It's a ubuntu 16.04 container and here's the mkl part that I use:
# install mkl
RUN wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB -P /tmp \
&& apt-key add /tmp/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB \
&& sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list' \
&& apt-get update \
&& apt-get install -y intel-mkl-64bit-2018.2-046 \
&& update-alternatives --install /usr/lib/x86_64-linux-gnu/libblas.so \
libblas.so-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50 \
&& update-alternatives --install /usr/lib/x86_64-linux-gnu/libblas.so.3 \
libblas.so.3-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50 \
&& update-alternatives --install /usr/lib/x86_64-linux-gnu/liblapack.so \
liblapack.so-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50 \
&& update-alternatives --install /usr/lib/x86_64-linux-gnu/liblapack.so.3 \
liblapack.so.3-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50 \
&& echo "/opt/intel/lib/intel64" > /etc/ld.so.conf.d/mkl.conf \
&& echo "/opt/intel/mkl/lib/intel64" >> /etc/ld.so.conf.d/mkl.conf \
&& ldconfig
Any ideas /hints? Can you share the Dockerfile you used?
openblas works fine:
sessionInfo(); library("benchmarkme"); benchmark_std(runs = 1)
R version 3.4.4 (2018-03-15)
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=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_3.4.4
# Programming benchmarks (5 tests):
3,500,000 Fibonacci numbers calculation (vector calc): 0.874 (sec).
Grand common divisors of 1,000,000 pairs (recursion): 1.31 (sec).
Creation of a 3500x3500 Hilbert matrix (matrix calc): 0.23 (sec).
Creation of a 3000x3000 Toeplitz matrix (loops): 16.9 (sec).
Escoufier's method on a 60x60 matrix (mixed): 1.28 (sec).
# Matrix calculation benchmarks (5 tests):
Creation, transp., deformation of a 5000x5000 matrix: 1.31 (sec).
2500x2500 normal distributed random matrix ^1000: 0.769 (sec).
Sorting of 7,000,000 random values: 0.918 (sec).
2500x2500 cross-product matrix (b = a' * a): 0.558 (sec).
Linear regr. over a 3000x3000 matrix (c = a \ b'): 0.396 (sec).
# Matrix function benchmarks (5 tests):
Cholesky decomposition of a 3000x3000 matrix: 0.773 (sec).
Determinant of a 2500x2500 random matrix: 1.03 (sec).
Eigenvalues of a 640x640 random matrix: 0.865 (sec).
FFT over 2,500,000 random values: 0.536 (sec).
Inverse of a 1600x1600 random matrix: 0.81 (sec).
user system elapsed test test_group cores
1 0.856 0.016 0.874 fib prog 0
2 1.220 0.088 1.309 gcd prog 0
3 0.176 0.056 0.230 hilbert prog 0
4 16.824 0.032 16.947 toeplitz prog 0
5 1.236 0.040 1.278 escoufier prog 0
6 1.232 0.048 1.314 manip matrix_cal 0
7 0.768 0.000 0.769 power matrix_cal 0
8 0.892 0.024 0.918 sort matrix_cal 0
9 0.952 0.536 0.558 cross_product matrix_cal 0
10 0.848 0.468 0.396 lm matrix_cal 0
11 0.812 0.784 0.773 cholesky matrix_fun 0
12 1.516 0.384 1.027 determinant matrix_fun 0
13 0.936 1.608 0.865 eigen matrix_fun 0
14 0.536 0.000 0.536 fft matrix_fun 0
15 1.264 0.732 0.810 inverse matrix_fun 0