Strange task behavior in openmp under openmpi - openmp

I have a stand with i7-5960X CPU with 8 cores + HT (16 threads). And here is a program that try to use both OpenMP and OpenMPI. It called as following:
# mpirun -np <NN1> -x OMP_NUM_THREADS=<NN2> <my_prog>
where NN1 and NN2 were varied. In the code I have this:
#pragma omp parallel
nOMP=omp_get_num_threads();
int maxOMP=omp_get_max_threads();
int procOMP=omp_get_num_procs();
printf("OMP version running on %d threads. Max threads=%d, available procs=%d\n", nOMP, maxOMP, procOMP);
Here is a result:
#1, NN1=2, NN2=2:
OMP version running on 2 threads. Max threads=2, available procs=2
#2, NN1=2, NN2=4:
OMP version running on 4 threads. Max threads=4, available procs=2
#3, NN1=3, NN2=4:
OMP version running on 4 threads. Max threads=4, available procs=16
So for 1 and 2 mpi threads omp_get_num_procs() returns "2" always and for 3 and above it returns "16".
The questions are: why and how to force it to return correct value for 1 and 2 mpi threads?
OpenMpi version is 1.10.3 and GCC version is 4.8.5, Centos 7 x86_64. Direct call without mpirun is correct too.
UPD1 Here is a relevant discussion: http://forum.abinit.org/viewtopic.php?f=2&t=2782, but no answer anyway.
UPD2 openmpi-2.x.x fix this.

The default binding is
- NUMA domain (e.g. socket) if > 2
- core otherwise
so if you mpirun -np 2 ..., there will be only one core per MPI task
but if you mpirun -np 3 ..., each MPI task is bound to a socket.
For example, on my VM (1 socket and 4 cores)
$ mpirun -np 2 grep Cpus_allowed_list /proc/self/status
Cpus_allowed_list: 0
Cpus_allowed_list: 1
$ mpirun -np 3 grep Cpus_allowed_list /proc/self/status
Cpus_allowed_list: 0-3
Cpus_allowed_list: 0-3
Cpus_allowed_list: 0-3
you can mpirun -bind-to socket or even mpirun -bind-to none in order to alter the default binding option.

Some error in 1.10.x version. Openmpi-2.x.x fix this.

Related

How many cores can I use when using **make -j**?

I'm using MacBook with M1 chip (10 CPU cores with 8 P cores and 2 E cores, 24 GPU cores) and want to compile some program, I wonder how I can know the number of cores I can use to compile?
Simply, what should x be in make -jx?
You can enter:
$ make -j `sysctl -n hw.ncpu`
so the answer is :
x = `sysctl -n hw.ncpu`
where the backstick characters means a command substitution, ie the result of the command inside the backsticks.

Problems with Orca and OpenMPI for parallel jobs

Hello to the community:
I recently started to use ORCA software for some quantum calculation but I have been having a lot of problems to lunch a parallel calculation in the cluster of my University.
To install Orca I used the static version:
orca_4_2_1_linux_x86-64_openmpi314.tar.xz.
In a shared direction of the cluster (/data/shared/opt/ORCA/).
And putted in my ~/.bash_profile:
export PATH="/data/shared/opt/ORCA/orca_4_2_1_linux_x86-64_openmpi314:$PATH"
export LD_LIBRARY_PATH="/data/shared/opt/ORCA/orca_4_2_1_linux_x86-64_openmpi314:$LD_LIBRARY_PATH"
For the installation of the corresponding OpenMPI version (3.1.4)
tar -xvf openmpi-3.1.4.tar.gz
cd openmpi-3.1.4
./configure --prefix="/data/shared/opt/ORCA/openmpi314/"
make -j 10
make install
When I use the frontend server all is wonderful:
With a .sh like this:
#! /bin/bash
export PATH="/data/shared/opt/ORCA/openmpi314/bin:$PATH"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/data/shared/opt/ORCA/openmpi314/lib"
$(which orca) test.inp > test.out
and an input like this:
# Computation of myjob at b3lyp/6-31+G(d,p)
%pal nprocs 10 end
%maxcore 8192
! RKS B3LYP 6-31+G(d,p)
! TightSCF Grid5 NoFinalGrid
! Opt
! Freq
%cpcm
smd true
SMDsolvent "water"
end
* xyz 0 1
C 0 0 0
O 0 0 1.5
*
The problem appears when I use the nodes:
.inp file:
#! Computation at RKS B3LYP/6-31+G(d,p) for cis1_bh267_m_Cell_152
%pal nprocs 12 end
%maxcore 8192
! RKS B3LYP 6-31+G(d,p)
! TightSCF Grid5 NoFinalGrid
! Opt
! Freq
%cpcm
smd true
SMDsolvent "water"
end
* xyz 0 1
C -4.38728130 0.21799058 0.17853303
C -3.02072869 0.82609890 -0.29733316
F -2.96869122 2.10937041 0.07179384
F -3.01136328 0.87651596 -1.63230798
C -1.82118365 0.05327804 0.23420220
O -2.26240947 -0.92805650 1.01540713
C -0.53557484 0.33394113 -0.05236121
C 0.54692198 -0.46942807 0.50027196
O 0.31128292 -1.43114232 1.22440290
C 1.93990391 -0.12927675 0.16510948
C 2.87355011 -1.15536140 -0.00858832
C 4.18738231 -0.82592189 -0.32880964
C 4.53045856 0.52514329 -0.45102225
N 3.63662927 1.52101319 -0.26705841
C 2.36381718 1.20228695 0.03146190
F -4.51788749 0.24084604 1.49796862
F -4.53935644 -1.04617745 -0.19111502
F -5.43718443 0.87033190 -0.30564680
H -1.46980819 -1.48461498 1.39034280
H -0.26291843 1.15748249 -0.71875720
H 2.57132559 -2.20300864 0.10283592
H 4.93858460 -1.60267627 -0.48060140
H 5.55483009 0.83859415 -0.70271364
H 1.67507560 2.05019549 0.17738396
*
.sh file (Slurm job):
#!/bin/bash
#SBATCH -p deflt #which partition I want
#SBATCH -o cis1_bh267_m_Cell_152_myjob.out #path for the slurm output
#SBATCH -e cis1_bh267_m_Cell_152_myjob.err #path for the slurm error output
#SBATCH -c 12 #number of cpu(logical cores)/task (task is normally an MPI process, default is one and the option to change it is -n)
#SBATCH -t 2-00:00 #how many time I want the resources (this impacts the job priority as well)
#SBATCH --job-name=cis1_bh267_m_Cell_152 #(to recognize your jobs when checking them with "squeue -u USERID")
#SBATCH -N 1 #number of node, usually 1 when no parallelization over nodes
#SBATCH --nice=0 #lowering your priority if >0
#SBATCH --gpus=0 #number of gpu you want
# This block is echoing some SLURM variables
echo "Jobid = $SLURM_JOBID"
echo "Host = $SLURM_JOB_NODELIST"
echo "Jobname = $SLURM_JOB_NAME"
echo "Subcwd = $SLURM_SUBMIT_DIR"
echo "SLURM_CPUS_PER_TASK = $SLURM_CPUS_PER_TASK"
# This block is for the execution of the program
export PATH="/data/shared/opt/ORCA/openmpi314/bin:$PATH"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/data/shared/opt/ORCA/openmpi314/lib"
$(which orca) ${SLURM_JOB_NAME}.inp > ${SLURM_JOB_NAME}.log --use-hwthread-cpus
I used the --use-hwthread-cpus flag as a recommendation but the same problem appears with and without this flag.
All the error is:
There are not enough slots available in the system to satisfy the 12 slots that were requested by the application: /data/shared/opt/ORCA/orca_4_2_1_linux_x86-64_openmpi314/orca_gtoint_mpi
Either request fewer slots for your application, or make more slots available for use. A "slot" is the Open MPI term for an allocatable unit where we can launch a process. The number of slots available are defined by the environment in which Open MPI processes are run:
1. Hostfile, via "slots=N" clauses (N defaults to number of processor cores if not provided)
2. The --host command line parameter, via a ":N" suffix on the hostname (N defaults to 1 if not provided)
3. Resource manager (e.g., SLURM, PBS/Torque, LSF, etc.)
4. If none of a hostfile, the --host command line parameter, or an RM is present, Open MPI defaults to the number of processor cores In all the above cases, if you want Open MPI to default to the number
of hardware threads instead of the number of processor cores, use the --use-hwthread-cpus option.
Alternatively, you can use the --oversubscribe option to ignore the number of available slots when deciding the number of processes to launch.
*[file orca_tools/qcmsg.cpp, line 458]:
.... aborting the run*
When I go to the output of the calculation, it looks like start to run but when launch the parallel jobs fail and give:
ORCA finished by error termination in GTOInt
Calling Command: mpirun -np 12 --use-hwthread-cpus /data/shared/opt/ORCA/orca_4_2_1_linux_x86-64_openmpi314/orca_gtoint_mpi cis1_bh267_m_Cell_448.int.tmp cis1_bh267_m_Cell_448
[file orca_tools/qcmsg.cpp, line 458]:
.... aborting the run
We have two kind of nodes on the cluster:
A punch of them are:
Xeon 6-core E-2136 # 3.30GHz (12 logical cores) and Nvidia GTX 1070Ti
And the other ones:
AMD Epyc 24-core (24 logical cores) and 4x Nvidia RTX 2080Ti
Using the command scontrol show node the details of one node of each group are:
First Group:
NodeName=fang1 Arch=x86_64 CoresPerSocket=6
CPUAlloc=12 CPUTot=12 CPULoad=12.00
AvailableFeatures=(null)
ActiveFeatures=(null)
Gres=gpu:gtx1070ti:1
NodeAddr=fang1 NodeHostName=fang1 Version=19.05.5
OS=Linux 5.7.12-arch1-1 #1 SMP PREEMPT Fri, 31 Jul 2020 17:38:22 +0000
RealMemory=15923 AllocMem=0 FreeMem=171 Sockets=1 Boards=1
State=ALLOCATED ThreadsPerCore=2 TmpDisk=7961 Weight=1 Owner=N/A MCS_label=N/A
Partitions=deflt,debug,long
BootTime=2020-10-27T09:56:18 SlurmdStartTime=2020-10-27T15:33:51
CfgTRES=cpu=12,mem=15923M,billing=12,gres/gpu=1,gres/gpu:gtx1070ti=1
AllocTRES=cpu=12,gres/gpu=1,gres/gpu:gtx1070ti=1
CapWatts=n/a
CurrentWatts=0 AveWatts=0
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s
Second Group
NodeName=fang50 Arch=x86_64 CoresPerSocket=24
CPUAlloc=48 CPUTot=48 CPULoad=48.00
AvailableFeatures=(null)
ActiveFeatures=(null)
Gres=gpu:rtx2080ti:4
NodeAddr=fang50 NodeHostName=fang50 Version=19.05.5
OS=Linux 5.7.12-arch1-1 #1 SMP PREEMPT Fri, 31 Jul 2020 17:38:22 +0000
RealMemory=64245 AllocMem=0 FreeMem=807 Sockets=1 Boards=1
State=ALLOCATED ThreadsPerCore=2 TmpDisk=32122 Weight=1 Owner=N/A MCS_label=N/A
Partitions=deflt,long
BootTime=2020-12-15T10:09:43 SlurmdStartTime=2020-12-15T10:14:17
CfgTRES=cpu=48,mem=64245M,billing=48,gres/gpu=4,gres/gpu:rtx2080ti=4
AllocTRES=cpu=48,gres/gpu=4,gres/gpu:rtx2080ti=4
CapWatts=n/a
CurrentWatts=0 AveWatts=0
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s
I use in the script of Slurm the flag -c, --cpus-per-task = integer; and in the input for Orca the command %pal nprocs integer end. I tested different combinations of this two parameters in order to see if I am using more CPU than the available:
-c, --cpus-per-task = integer
%pal nprocs integer end
None
6
None
3
None
2
1
2
1
12
2
6
3
4
12
12
With different amount of memories: 8000 MBi and 2000 MBi (my total memory is around 15 GBi). And in all the cases the same error appears. I am not an expert user neither in ORCA non in informatic (but maybe you guess this for the extension of the question), so maybe the solution is simple but I really don’t have it, Idon't know what's going on!
A lot of thanks in advance,
Alejandro.
Faced the same issue.
Explicit declaration --prefix ${OMPI_HOME} directly as ORCA parameter and using of static linked ORCA version helps me:
export RSH_COMMAND="/usr/bin/ssh"
export PARAMS="--mca routed direct --oversubscribe -machinefile ${HOSTS_FILE} --prefix ${OMPI_HOME}"
$ORCA_DIR/orca $WORKDIR/$JOBFILE.inp "$PARAMS" > $WORKDIR/$JOBFILE.out
Also, It's better to build OpenMPI 3.1.x with --disable-builtin-atomics flag.
Thank you #Alexey for your answer. And sorry for the wrong Tag, like I said, I am pretty rookie on this stuff.
The problem was not in the Orca or OpenMPI configuration but in the bash script used for scheduled the Slurm job.
I thought that the entire Orca job itself was what Slurm call a "task". For that reason I declared the flag --cpus-per-task equal to the number of parallel jobs that I want to do with Orca. But the problem is that each parallel Orca job (that is launch using OpenMPI) is a task for Slurm. Therefore with my Slurm script I was reserving a node with at least 12 CPU, but when Orca launch their parallel jobs, each one ask for 12 CPU, so: "There are not enough slots available ..." because I needed 144 CPU.
The rest of the cases in the table of my Question fails for another reason. I was launching at the same time 5 different Orca calculation. Now, because --cpus-per-task could be None, 1, 2 or 3; the five calculation might enter in the same node or in another node with this amount of free CPU, but when Orca ask for the parallel jobs, fail again because there are not this amount of CPU on the node.
The solution that I found is pretty simple. On the .sh script for Slurm I putted this:
#SBATCH --mincpus=n*m
#SBATCH --ntasks=n
#SBATCH --cpus-per-task m
Instead of only:
#SBATCH --cpus-per-task m
Where n will be equal to the number of parallel jobs specified on the Orca input (%pal nprocs n end) and m the number of CPU that you want to use for each parallel Orca job.
In my case I used n = 12, m = 1. With the flag --mincpus I ensured to take a node with at least 12 CPU and allocated them. With the --cpus-per-task is pretty evident what this flag do (even for me :-) ), which, by the way, has a default value of 1 and I don't know if more than 1 CPU for each OpenMPI Orca job improve the velocity of the calculation. And --ntasks gives the information to Slurm of how many task you will do.
Of course if you know the number of task and the CPU per task is easy to know how many CPU you need to reserve, but I don't know if this is easy to Slurm too :-). So, to be sure that I allocate the correct number of CPU i used --mincpus flag, but maybe is not needed. The thing is that it works now ^_^.
It is also important to take into account the amount of memory that you declare in the input of Orca in order of do not exceed the available memory. For example, if you have 12 task and a RAM of 15000 MBi, the right amount of memory to declared should be no more than 15000/12 = 1250 MBi
I had a similar problem with parallel jobs before. The slurm also output not enough slots error.
My solution is to change parallel threads into parallel processes. For my system is to change
#SBATCH -c 24
into
#SBATCH -n 24
and everything works just fine.

GNU Parallel with processes that further fork

Consider the file Processes.txt
./MyProcess 1 -nbThreads 2
./MyProcess 2 -nbThreads 2
./MyProcess 3 -nbThreads 2
, where each MyProcess will attempt to use two cores. Now consider running
parallel -j 3 :::: Processes.txt
The call to parallel specifically indicate to use no more than 3 cores. Will parallel allow MyProcess to further fork and the whole thing will use 6 cores or will it somehow enforce the three processes MyProcess to using one core each only?
It will run three processes at once and if they choose to create further processes it will neither know nor care.
(Hattip to: Mark Setchell)

Specifying number of slurm nodes

For a year my scheduling command with slurm was fine, but is now attempting to allocate N+1 nodes for my job now that someone else is scheduled on a node I'm running on.
I'm trying to run a job on 2 nodes that runs as 48 processes all with two cores. (so, 48 jobs with MPI, each using OMP_NUM_THREADS=2), so 96 all together.
In the past I've always run this with (using hostname as example since it illustrates the problem)
srun --partition=intel \
-N 2 \
--ntasks-per-node=24 \
--ntasks=48 \
--cpus-per-task=2 \
hostname
But now squeue is telling me that this is pending for resources awaiting 3 nodes instead of 2.
$ squeue
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
1282 intel hostname gmp13x64 PD 0:00 3 (Resources)
1229 intel bwd-pm25 shunliu R 5-12:51:18 1 dena5
The intel queue is composed of two nodes, dena5 and dena6
gmp13x64#dena:script_dev$ sinfo --Node --long
Sat Nov 5 10:49:51 2016
NODELIST NODES PARTITION STATE CPUS S:C:T MEMORY TMP_DISK WEIGHT FEATURES REASON
dena5 1 intel allocated 48 2:12:2 128833 1951 1 (null) none
dena6 1 intel idle 48 2:12:2 128833 1951 1 (null) none
My interpretation is the info that sinfo is giving is that my setup should be fine. Plus, in the past this has always worked.
Why is slurm all of a sudden saying that this requires 3 nodes? How would that even be allowed considering the intel partition only has 2 nodes? Am I mis-interpreting some of the flags I'm using?

Linpack sometimes starting, sometimes not, but nothing changed

I installed Linpack on a 2-Node cluster with Xeon processors. Sometimes if I start Linpack with this command:
mpiexec -np 28 -print-rank-map -f /root/machines.HOSTS ./xhpl_intel64
linpack starts and prints the output, sometimes I only see the mpi mappings printed and then nothing following. To me this seems like random behaviour because I don't change anything between the calls and as already mentioned, Linpack sometimes starts, sometimes not.
In top I can see that xhpl_intel64processes have been created and they are heavily using the CPU but when watching the traffic between the nodes, iftop is telling me that it nothing is sent.
I am using MPICH2 as MPI implementation. This is my HPL.dat:
# cat HPL.dat
HPLinpack benchmark input file
Innovative Computing Laboratory, University of Tennessee
HPL.out output file name (if any)
6 device out (6=stdout,7=stderr,file)
1 # of problems sizes (N)
10000 Ns
1 # of NBs
250 NBs
0 PMAP process mapping (0=Row-,1=Column-major)
1 # of process grids (P x Q)
2 Ps
14 Qs
16.0 threshold
1 # of panel fact
2 PFACTs (0=left, 1=Crout, 2=Right)
1 # of recursive stopping criterium
4 NBMINs (>= 1)
1 # of panels in recursion
2 NDIVs
1 # of recursive panel fact.
1 RFACTs (0=left, 1=Crout, 2=Right)
1 # of broadcast
1 BCASTs (0=1rg,1=1rM,2=2rg,3=2rM,4=Lng,5=LnM)
1 # of lookahead depth
1 DEPTHs (>=0)
2 SWAP (0=bin-exch,1=long,2=mix)
64 swapping threshold
0 L1 in (0=transposed,1=no-transposed) form
0 U in (0=transposed,1=no-transposed) form
1 Equilibration (0=no,1=yes)
8 memory alignment in double (> 0)
edit2:
I now just let the program run for a while and after 30min it tells me:
# mpiexec -np 32 -print-rank-map -f /root/machines.HOSTS ./xhpl_intel64
(node-0:0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
(node-1:16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31)
Assertion failed in file ../../socksm.c at line 2577: (it_plfd->revents & 0x008) == 0
internal ABORT - process 0
APPLICATION TERMINATED WITH THE EXIT STRING: Hangup (signal 1)
Is this a mpi problem?
Do you know what type of problem this could be?
I figured out what the problem was: MPICH2 uses different random ports each time it starts and if these are blocked your application wont start up correctly.
The solution for MPICH2 is to set the environment variable MPICH_PORT_RANGE to START:END, like this:
export MPICH_PORT_RANGE=50000:51000
Best,
heinrich

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