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Rank-1 update to LU matrices

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Hi,

I have a matrix Y for which I need LU factors that I can get using DSS interface Routines like dss_factor_complex. However, the diagonal entries of this matrix need to be updated after each iteration of a loop that gets me LU factors.

Since Y is very large, and LU factorization will take a lot of computational effort. Is there a way to update LU factors when Y updates without having to do LU factorization on every iteration?

I am trying to do this:

iteration1: Y (original) > reorder > factor (LU)> solve

iteration2: Y' (updated) > update LU (from iteration1) > solve

Iteration3: Y"(updated) > update LU (from iteration2) > solve

Thanks.

Sunny


Eigenvalue routine heevr goes wrong very weirdly

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I am trying to make use of the official example code of heevr routine in LAPACK. Once I changed the range parameter from 'V' to 'A' and commented out il and iu, the first two eigenvalues wrongly showed zero. Below is my tinily modified example code. I used icpc 13.1.3 and run in Linux. Thanks in advance.

#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"

/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, MKL_INT m, MKL_INT n, MKL_Complex16* a, MKL_INT lda );
extern void print_rmatrix( char* desc, MKL_INT m, MKL_INT n, double* a, MKL_INT lda );

/* Parameters */
#define N 4
#define LDA N
#define LDZ N

/* Main program */
int main() {
        /* Locals */
        MKL_INT n = N, lda = LDA, ldz = LDZ, il, iu, m, info;
        double abstol, vl, vu;
        /* Local arrays */
        MKL_INT isuppz[N];
        double w[N];
        MKL_Complex16 z[LDZ*N];
        MKL_Complex16 a[LDA*N] = {
           {-2.16,  0.00}, {-0.16,  4.86}, {-7.23,  9.38}, {-0.04, -6.86},
           { 0.00,  0.00}, { 7.45,  0.00}, { 4.39, -6.29}, {-8.11,  4.41},
           { 0.00,  0.00}, { 0.00,  0.00}, {-9.03,  0.00}, {-6.89,  7.66},
           { 0.00,  0.00}, { 0.00,  0.00}, { 0.00,  0.00}, { 7.76,  0.00}
        };
        /* Executable statements */
        printf( "LAPACKE_zheevr (column-major, high-level) Example Program Results\n" );
        /* Negative abstol means using the default value */
        abstol = -1.0;
        /* Set VL, VU to compute eigenvalues in half-open (VL,VU] interval */
        //vl = -5.0;
        //vu = 5.0;
        /* Solve eigenproblem */
        info = LAPACKE_zheevr( LAPACK_COL_MAJOR, 'V', 'A', 'L', n, a, lda,
                        vl, vu, il, iu, abstol, &m, w, z, ldz, isuppz );
        /* Check for convergence */
        if( info > 0 ) {
                printf( "The algorithm failed to compute eigenvalues.\n" );
                exit( 1 );
        }
        /* Print the number of eigenvalues found */
        printf( "\n The total number of eigenvalues found:%2i\n", m );
        /* Print eigenvalues */
        print_rmatrix( "Selected eigenvalues", 1, m, w, 1 );
        /* Print eigenvectors */
        print_matrix( "Selected eigenvectors (stored columnwise)", n, m, z, ldz );
        exit( 0 );
} /* End of LAPACKE_zheevr Example */

/* Auxiliary routine: printing a matrix */
void print_matrix( char* desc, MKL_INT m, MKL_INT n, MKL_Complex16* a, MKL_INT lda ) {
        MKL_INT i, j;
        printf( "\n %s\n", desc );
        for( i = 0; i < m; i++ ) {
                for( j = 0; j < n; j++ )
                        printf( " (%6.2f,%6.2f)", a[i+j*lda].real, a[i+j*lda].imag );
                printf( "\n" );
        }
}

/* Auxiliary routine: printing a real matrix */
void print_rmatrix( char* desc, MKL_INT m, MKL_INT n, double* a, MKL_INT lda ) {
        MKL_INT i, j;
        printf( "\n %s\n", desc );
        for( i = 0; i < m; i++ ) {
                for( j = 0; j < n; j++ ) printf( " %6.2f", a[i+j*lda] );
                printf( "\n" );
        }
}

FFT error - DftiFreeDescriptor / DftiCommitDescriptor (Fortran)

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I'm having an error using the DftiFreeDescriptor command on the FFT computation. I'm using Intel Parallel Studio XE Cluster Edition (2016 - Student download) with Visual Studio Community 2015. And here is the code:

seqc = CMPLX(seq)
Status1 = DftiCreateDescriptor(My_Desc2_Handle, DFTI_DOUBLE, DFTI_COMPLEX, 1, npts)
Status1 = DftiCommitDescriptor(My_Desc2_Handle)
Status1 = DftiComputeForward(My_Desc2_Handle, seqc)
Status1 = DftiFreeDescriptor(My_Desc2_Handle)

I start with this real(8)::seq(npts) and convert it to the complex seqc(npts), where npts is something between 2000 and 6000.

Debuging each step I have the following values for Status1  and My_Desc2_Handle:

Status1 = 0 / My_Desc2_Handle: Undefined address

Status1 = DftiCreateDescriptor(My_Desc2_Handle, DFTI_DOUBLE, DFTI_COMPLEX, 1, npts)

Status1 = 0 / My_Desc2_Handle = 0

Status1 = DftiCommitDescriptor(My_Desc2_Handle)

Status1 = 0 / My_Desc2_Handle = -620492544

Status1 = DftiComputeForward(My_Desc2_Handle, seqc)

Status1 = 0 / My_Desc2_Handle = -620492544

Status1 = DftiFreeDescriptor(My_Desc2_Handle)

Error, where in the output i get this:  Invalid address specified to RtlValidateHeap( 0000000011FA0000, 0000000014312970 )

So, I've tested changing npts to values around 100, than My_desc2_Handle receives a positive value and I don't get errors with the DftiFreeDescriptor command. But if I put it up to 200, My_Desc2_Handle gets negative and the error happens again. So I guess it is something with the DftiCommitDescriptor, where it can't allocate/address the memory correctly. If I don't add the DftiFreeDescriptor command, I just get my FFT normaly, but I'm not sure if the memory is leaking each time I run it.

Question about Parallel thread number of Pardiso

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Hi all,

In my program, I am not set restriction of OpenMP thread number, but I found it only using 4 OpenMP threads on my machine. Why?

 

My CPU configuration is (reported by Intel VTune ):
Name: Intel(R) Core(TM) Processor 2xxx Series
Frequency: 2.2 GHz
Logical CPU Count: 8 

 

OS is windows 10.

 

Following is console output by pardiso and openmp while setting KMP_SETTINGS=1 and pardiso message level parameter to 1:

User settings:

   KMP_SETTINGS=1

Effective settings:

   KMP_ABORT_DELAY=0
   KMP_ABORT_IF_NO_IRML=false
   KMP_ADAPTIVE_LOCK_PROPS='1,1024'
   KMP_ALIGN_ALLOC=64
   KMP_ALL_THREADPRIVATE=128
   KMP_ALL_THREADS=32768
   KMP_ATOMIC_MODE=1
   KMP_BLOCKTIME=200
   KMP_CPUINFO_FILE: value is not defined
   KMP_DETERMINISTIC_REDUCTION=false
   KMP_DUPLICATE_LIB_OK=false
   KMP_FORCE_REDUCTION: value is not defined
   KMP_FOREIGN_THREADS_THREADPRIVATE=true
   KMP_FORKJOIN_BARRIER='2,2'
   KMP_FORKJOIN_BARRIER_PATTERN='hyper,hyper'
   KMP_FORKJOIN_FRAMES=true
   KMP_FORKJOIN_FRAMES_MODE=3
   KMP_GTID_MODE=2
   KMP_HANDLE_SIGNALS=false
   KMP_HOT_TEAMS_MAX_LEVEL=1
   KMP_HOT_TEAMS_MODE=0
   KMP_INIT_AT_FORK=true
   KMP_INIT_WAIT=2048
   KMP_ITT_PREPARE_DELAY=0
   KMP_LIBRARY=throughput
   KMP_LOCK_KIND=queuing
   KMP_MALLOC_POOL_INCR=1M
   KMP_MONITOR_STACKSIZE: value is not defined
   KMP_NEXT_WAIT=1024
   KMP_NUM_LOCKS_IN_BLOCK=1
   KMP_PLAIN_BARRIER='2,2'
   KMP_PLAIN_BARRIER_PATTERN='hyper,hyper'
   KMP_REDUCTION_BARRIER='1,1'
   KMP_REDUCTION_BARRIER_PATTERN='hyper,hyper'
   KMP_SCHEDULE='static,balanced;guided,iterative'
   KMP_SETTINGS=true
   KMP_STACKOFFSET=64
   KMP_STACKPAD=0
   KMP_STACKSIZE=4M
   KMP_STORAGE_MAP=false
   KMP_TASKING=2
   KMP_TASK_STEALING_CONSTRAINT=1
   KMP_USE_IRML=false
   KMP_VERSION=false
   KMP_WARNINGS=true
   OMP_CANCELLATION=false
   OMP_DISPLAY_ENV=false
   OMP_DYNAMIC=false
   OMP_MAX_ACTIVE_LEVELS=2147483647
   OMP_NESTED=false
   OMP_NUM_THREADS: value is not defined
   OMP_PLACES: value is not defined
   OMP_PROC_BIND='false'
   OMP_SCHEDULE='static'
   OMP_STACKSIZE=4M
   OMP_THREAD_LIMIT=32768
   OMP_WAIT_POLICY=PASSIVE
   KMP_AFFINITY='noverbose,warnings,respect,granularity=core,duplicates,none'


Mesh statistics:
     nodes     :  4419
     edges     :  13078
     triangles :  8660
Rotate mesh alpha = 0
Rotate mesh alpha = 8

=== PARDISO: solving a real nonsymmetric system ===
0-based array is turned ON
PARDISO double precision computation is turned ON
Parallel METIS algorithm at reorder step is turned ON
Scaling is turned ON


Summary: ( reordering phase )
================

Times:
======
Time spent in calculations of symmetric matrix portrait (fulladj): 0.000803 s
Time spent in reordering of the initial matrix (reorder)         : 0.009233 s
Time spent in symbolic factorization (symbfct)                   : 0.002040 s
Time spent in data preparations for factorization (parlist)      : 0.000264 s
Time spent in allocation of internal data structures (malloc)    : 0.006886 s
Time spent in additional calculations                            : 0.002166 s
Total time spent                                                 : 0.021393 s

Statistics:
===========
Parallel Direct Factorization is running on 4 OpenMP

< Linear system Ax = b >
             number of equations:           4754
             number of non-zeros in A:      32740
             number of non-zeros in A (%): 0.144864

             number of right-hand sides:    1

< Factors L and U >
             number of columns for each panel: 96
             number of independent subgraphs:  0
             number of supernodes:                    3260
             size of largest supernode:               110
             number of non-zeros in L:                101444
             number of non-zeros in U:                75684
             number of non-zeros in L+U:              177128

Reordering completed ...
Number of nonzeros in factors = 177128
Number of factorization MFLOPS = 6=== PARDISO is running in In-Core mode, because iparam(60)=0 ===

=== PARDISO: solving a real nonsymmetric system ===
Two-level factorization algorithm is turned ON

 

 

 

 

 

The difference in the common sparse solver function result and cluster sparse solver function result

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Hello.

I'm Using MKL Pardiso Sparse Solver (PARDISO).

 

Some time ago, I Using Intel Parallel Studio 2013 Version (MKL 11.2).

Recently, I'm Update Intel Parallel Studio 2016 (MKL 11.3).

This Version Support Cluster Sparse Solver. so I using this Function.

But Solving result is difference. (about 0.02)

 

 

Originally does the other result come out?

Or is there the condition getting the little more exact result?

Linking Lapack 95 in a DLL

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 I cant seem to figure out how to set the Properties to compile and link MKL95 in a DLL.

Here is the code:

SUBROUTINE GET_ROOTS(phi, philen, side, output)
!DEC$ ATTRIBUTES DLLEXPORT::GET_ROOTS
    USE mkl95_precision
    USE mkl95_lapack, ONLY: HSEQR
    INTEGER, INTENT(IN) :: philen
    REAL(8), INTENT(IN) :: side
    REAL(8), DIMENSION(philen), INTENT(INOUT) :: phi
    COMPLEX(16), DIMENSION(philen-1), INTENT(INOUT) :: output
    COMPLEX(16), DIMENSION(:,:), ALLOCATABLE :: matrixA
    COMPLEX(16), DIMENSION(:), ALLOCATABLE :: roots
    INTEGER :: status, dim, i
    dim = philen-1
    ALLOCATE(matrixA(dim,dim), STAT = status)
    ALLOCATE(roots(dim), STAT = status)
    roots = 0.0_8
    matrixA = 0.0_8
     DO i = 1, dim-1
        matrixA(1,i) = -1.0_8 * phi(philen-i)/phi(philen)
        matrixA(i+1,i) = 1.0_8
    END DO
    matrixA(1,dim) = -1.0_8 * phi(1)/phi(philen)
    CALL HSEQR(matrixA,roots)
    output = roots
    DEALLOCATE(matrixA)
    DEALLOCATE(roots)
    return
END SUBROUTINE GET_ROOTS

Here are the compilers errors:

>GET_ROOTS.f90
GET_ROOTS\GET_ROOTS\GET_ROOTS.f90(8): error #7002: Error in opening the compiled module file.  Check INCLUDE paths.   [MKL95_PRECISION]
GET_ROOTS\GET_ROOTS\GET_ROOTS.f90(9): error #7002: Error in opening the compiled module file.  Check INCLUDE paths.   [MKL95_LAPACK]
GET_ROOTS\GET_ROOTS\GET_ROOTS.f90(27): error #6406: Conflicting attributes or multiple declaration of name.   [HSEQR]
GET_ROOTS\GET_ROOTS\GET_ROOTS.f90(9): error #6580: Name in only-list does not exist.   [HSEQR]
1>compilation aborted for C:\Users\FrankM\documents\visual studio 2012\Projects\GET_ROOTS\GET_ROOTS\GET_ROOTS.f90 (code 1)

of course the first thing I tried was to set

Sequential (/Qmkl:sequential)

I 've also tried using the advisor and get the same messages.

Help.

 

 

Intel MKL WARNING: Library mkl_avx.dll (MKL type 7) is not suitable for this processor (MKL type 6).

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One of our clients is getting the warning in the subject, followed by the program failing, running our software.  Any ideas what is causing this or how to resolve it?

The user is using a 32-bit version of Windows.

The processor is

Our software is built with “Intel(R) Parallel Studio XE 2015 Update 1 Composer Edition for Fortran Windows” .

 

ILP64 and LP64 in the same application for sparse matrix operations

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Hi,

I am working on a c++ application which does solves and operations with sparse matrices. Because the matrices are large, I am using pardiso_64 rather than pardiso. (I am using the LP64 interface.)

The problem is that I also do other things with the matrices, such as mkl_dcsrsymv for matrix-vector products. However there is no "mkl_dcsrsymv_64" and hence I must copy the 64-bit integer matrix index arrays (used in pardiso_64) to 32-bit integer arrays.

In my application matrix-vector products are used extensively, and I do not wish to duplicate the index data permanently. It is also not an option to switch to the ILP64 interface, because my application links in legacy fortran libraries which also links in mkl using the LP64 interface.

I am using the single-layer linking (mkl_rt.dll), mkl 11.2 (parallel studio xe2015) and the visual studio 2010 c++ compiler.

Is there an obvious solution to this, for example by switching between the ILP64 and LP64 interfaces runtime? 

 

Thanks in advance!

Jens

 

 


Typos in documentation

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Hello,

I hope I am not polluting this forum with the following trivialities:

  1. Is this the right place to report issues with MKL ?
  2. There is a typo in the documentation of the page "v?LinearFrac" (in Section Vector Mathematical Functions).
    The types of scalea, scaleb, shifta and shiftb are wrong, it should be "float" instead of "float *" (and "double" instead of "double *").
  3. Finally, is it really pertinent to put a "const" in front on non-pointers values (eg. MKL_INT) ?

Source: https://software.intel.com/en-us/node/521774

Best regards,

Marc Lasson.

mkl_?csrcoo -- description of parameter nnz

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Hello,

is the description of parameter nnz in function mkl_?csrcoo correct?

The manual states that nnz is an output parameter specifying the number of non-zero elements in matrix A. However, I feel like nnz is an input parameter.

A minimal example (conversion of a unit matrix of size 10 from COO to CSR format in C++) only works if I define nnz = 10 before calling the function. If I set, say, nnz = 5, then only the first 5 elements are set in the CSR arrays.

Could someone check or disprove that?

 

Pardisoinit

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I guess this is another bug: the function pardisoinit resets iparm[34] to zero.

I must reset iparm[34] = 1 between calling pardisoinit() and pardiso().

PARDISO: iterate for LU factors from the originial LU factors

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Hi,

I have a problem in which I do not want to iterate for LU factors using PARDISO from the last iteration of factorisation. Instead, I want the new LU factors to be derived from the original LU factors. This is what I mean:

PARDISO Iteration 1: Y0 (matrix) -> L0U0 -> X0 (solution)

Iteration 2: Y1 (Y0 updated) -> L1U1 (derived from L0U0) -> X1

Iteration 3: Y2 (Y0 updated) -> L2U2 (derived from L0U0) -> X2

Iteration 4: Y3(Y0 updated) -> L3U3 (derived from L0U0) -> X3

and so on...

I know using param(4) will get new LU factors from the LU factors from the last iteration; however, what I need is somewhat different as my starting point to find new LU factors remains constant.

Thanks.

Modification of Makefile for Parallel Studio XE 2015

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Dear smart MKL friends,
I have a very large C++ code written by someone else in MS visual studio. I converted the code in a way that it worked perfectly on UNIX clusters. Now, I want it to work on my Laptop’s Kubuntu Kernel. However, I couldn’t make it work and I decided to seek some online help.
Here is my software environment on my laptop:
•    Kubuntu 14.04 LTS
•    Compiler: Mpic++
•    Intel® Parallel Studio XE 2015 Composer Edition for Linux
•    Terminal (no Eclipse)

Necessary part of the makefile and how I linked the libraries can be found below:

#compiler
CC=mpic++
CFLAGS=-c -g -O0 -I./ParaSails
LFLAGS= -L/usr/global/intel/mkl/2011.4/lib/intel64/
-L/usr/global/intel/mkl/10.3.1.107/mkl/lib/intel64 -L./ParaSails
-lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lpthread -lguide
-openmp -lParaSails

all : cbm.x
cbm.x : frprop.o gmres.o input.o  mtxslv.o resvoir.o ccoal.o
$(CC) $(LFLAGS) -fPIC frprop.o gmres.o input.o resvoir.o mtxslv.o ccoal.o -o cbm.x -lParaSails

Linking part of the makefile for the solver (Parasails) can be found below:

BLASLIBFLAGS = -L/usr/global/intel/mkl/2011.4/lib/intel64/
-L/usr/global/intel/mkl/10.3.1.107/mkl/lib/intel64
-lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lpthread –openmp

When I make my executable on my laptop, I receive the following fatal error:

./Parasails.c 1319: undefined reference to `dgels_'

I believe it is a problem with Lapack or Blas libraries. I tried different linkings to make it work but I couldn’t solve the problem. I spent good 4 days on this issue, searched every possible answer on the Internet, but I think it is time to seek for some help. I was wondering, maybe, someone could create sometime for my problem and help me to modify the links on my makefile for the given software environment above.
Thanks you in advance and best regards,
Burak

 

Which MKL files to ship?

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I am using the latest Fortran Parallel Studio XE 2016 Update 1, and the only MKL functions I'm using are Pardiso and Feast (compiling for 32-bit and 64-bit). Is there any way to find out which MKL files to ship if I want to support all Windows platforms?

I know this question has been asked before, but I have never seen a definitive answer other than "ship them all". I don't really want to ship them all because they are making the build file unnecessarily large, and I'm pretty sure most of them aren't being used seeing as I'm only using two MKL functions.

Intel Math Kernel Library - TerminateProcess on some hardware

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We have encountered an odd behavior.

Software that uses MKL runs on a HP620 E5-1650 (C602 chipset).  

It closes the application (TerminateProcess) when run on a HP640 E5-1650v3 (C612 chipset).

We tried the newest MKL DLLs, but the behavior was not changed.


equivalent of Matlabs conv2(A,B,'same') using VSL

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I need to implement the equivalent of Matlabs conv2(A,B,'same') using VSL as part of a conversion of some Matlab code to C++. I am not a signal processing expert and am struggling a bit with this. Some pointers would be very helpful and much appreciated...

default MKL reference documentation

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I am using Fortran Compiler 16.0.1.146 with VS2010.  I noticed that the default MKL reference documentation is for C instead for Fortran.  For example, if am editing a source file, and if I press F1 on an MKL call, a browser opens up with C documentation:

file:///C:/Program Files (x86)/IntelSWTools/documentation_2016/en/mkl/common/mklman_c/index.htm

Instead, it should be Fortran documentation:

file:///C:/Program Files (x86)/IntelSWTools/documentation_2016/en/mkl/common/mklman_f/index.htm

 

Roman

 

Question about DGEMM

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I am using DGEMM from MKL to do multiplication between matrix and vectors.

I found when I test in simple program, just calling DGEMM 200000 times to compute 256*256 matrix times 256*1 vector, it takes only about 7 seconds (nthreads=8).

I my real poisson solver, which need this multiplication 200000 times, still 256*256 matrix times 256*1 vector, it takes 2 min, which is much much slower than in simple test. 

Could anyone suggest any reason about this low performance? My poisson solver is openmp code.

Thanks in advance!

Sincerely,

Xuan

 

MKL giving different results for different argument alignments

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We're seeing DSYEVX in MKL give different results when the A matrix is aligned on a 16-byte boundary or not.  A very simple test case is available at https://github.com/tomkcook/dsyevx_bug.

We're using the following product versions:

  • Microsoft Visual Studio 2013 Version 12.0.40629.00 Update 5
  • Intel(R) Visual Fortran Composer XE 2013 SP1 Update 2 Integration for Microsoft Visual Studio* 2013, 14.0.0086.12
  • MKL 11.1 Update 2

We've got some more info on this, but before I waste anyone's time with that, I'd appreciate if someone could confirm this is actually a bug an not just me doing something daft!

Issue with license for MKL and C-compile

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Hello,

I am trying to install the Math Kernel Library for some days now, but with no hope.

Currently, I am stuck in what seems to be like a license-related issue. The issue is this:

icc: _configtest.c

 

Error: A license for Comp-CL could not be obtained (-1,359,2).

 

Is your license file in the right location and readable?
The location of your license file should be specified via

the $INTEL_LICENSE_FILE environment variable.

 

License file(s) used were (in this order):
    1.  Trusted Storage
**  2.  /opt/intel/licenses/NCOM_L__CPPFOR_3ZCK-47GJKR88_1.lic
**  3.  /opt/intel/licenses/NCOM____3JZX-3VRGRXTP_1.lic
**  4.  /opt/intel/compilers_and_libraries_2016.1.150/linux/bin/intel64/../../Licenses
**  5.  /home/[user]/Licenses
**  6.  /Users/Shared/Library/Application Support/Intel/Licenses
**  7.  /opt/intel/compilers_and_libraries_2016.1.150/linux/bin/intel64/*.lic

 

Please visit http://software.intel.com/sites/support/ if you require technical assistance.

 

icc: error #10052: could not checkout FLEXlm license

 

Error: A license for Comp-CL could not be obtained (-1,359,2).

Is your license file in the right location and readable?
The location of your license file should be specified via
the $INTEL_LICENSE_FILE environment variable.

 

License file(s) used were (in this order):
    1.  Trusted Storage
**  2.  /opt/intel/licenses/NCOM_L__CPPFOR_3ZCK-47GJKR88_1.lic
**  3.  /opt/intel/licenses/NCOM____3JZX-3VRGRXTP_1.lic
**  4.  /opt/intel/compilers_and_libraries_2016.1.150/linux/bin/intel64/../../Licenses
**  5.  /home/[user]/Licenses
**  6.  /Users/Shared/Library/Application Support/Intel/Licenses
**  7.  /opt/intel/compilers_and_libraries_2016.1.150/linux/bin/intel64/*.lic

Please visit http://software.intel.com/sites/support/ if you require technical assistance.

 

 

I have licenses for both MKL and Parallel Studio, and I am using a x86-64 linux. I also need to mention that in the serial activation step that a MAC address is needed, I provided my Wireless card's MAC beacuse of the absence of an ethernet card on my system.

Any help will be appreciated, thanks.

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