I am a mechanical engineering looking to do CFD simulations on HPC machines. Currently, I am programming my procedures within the framework of PARAMESH, which is a fortran library with MPI calls for handling data and workload distribution during parallel execution.
During parallel runs the application gives false results, where data between processes is not transmitted, or terminates with different kinds of errors. The bizarre thing is that the location of failure in the source code and the error itself depends on the number of processes running. In my opinion the problem lies with my MPI setup or the execution with mpirun as the library is still used for numerical simulations at other research institutions.
As I am familiar only with the basics on how MPI works and not the intricacies I hope that you might provide the insight I lack. Maybe I am overlooking something basic, which leads to these program failures.
Here is a summary of the errors depending on the process count N when the command mpirun -np N --hostfile hostfile --oversubscribe --report-bindings --display-map --display-allocation lsp is executed (hostfile contains: hostname and max_slots = 1):
N = 1: no errors;
N = 2: application terminates normally, invalid data in result arrays
- Data from process 0 not transmitted correctly to process 1
N = 4:
malloc(): invalid size (unsorted)
Program received signal SIGABRT: Process abort signal.
failure occurs on standard fortran allocate statement allocate (x, size (y, 2), size (z, 3), stat = istat)
- allocatable variable stored in separate module with save attribute
- allocatable variable deallocated on all processors before
- correct integer values determining size of array
N = 6:
Program received signal SIGSEGV: Segmentation fault - invalid memory reference.
failure occurs on standard fortran deallocate statement if (allocated(x)) deallocate(x)
- deallocatable variable local to subroutine
- deallocatable variable allocated on all processors prior to deallocation
N = 8; 10; 12; 14; 16; 32: Multiple errors
free(): invalid size
Program received signal SIGSEGV: Segmentation fault - invalid memory reference
malloc(): unaligned tcache chunk detected
Program received signal SIGABRT: Process abort signal.
failure occurs on call MPI_ALLTOALL (commatrix_recv, 1, MPI_INTEGER, commatrix_send, 1, MPI_INTEGER, MPI_COMM_WORLD, ierror)
- in a previous call to MPI_ALLTOALL,
commatrix_sendis allocated on all processors with valid values - directly before call, in which failure occurs,
allocated (commatrix_send)returns nothing andprint*, commatrix_sendreturns no values at all as if the two commands where not there. Also there is no error message when executingallocated (commatrix_send). Is this a memory leak?
I also tried running mpirun -use-hwthread-cpus --oversubscribe --report-bindings --display-map --display-allocation lsp and mpirun -use-hwthread-cpus --report-bindings --display-map --display-allocation lsp, which resulted in the same error as in the cases N = 8; 10; 12; 14; 16; 32.
Thanks in advance
I am running the application on my desktop:
- AMD Ryzen 9 7950X 16-Core Processor
- 64 GB of RAM
- Ubuntu 22.04.3 LTS
- OPEN MPI 4.1.5
- GCC 11.4.0
My Open MPI installation:
Package: Open MPI root@Workstation-001 Distribution
Open MPI: 4.1.5
Open MPI repo revision: v4.1.5
Open MPI release date: Feb 23, 2023
Open RTE: 4.1.5
Open RTE repo revision: v4.1.5
Open RTE release date: Feb 23, 2023
OPAL: 4.1.5
OPAL repo revision: v4.1.5
OPAL release date: Feb 23, 2023
MPI API: 3.1.0
Ident string: 4.1.5
Prefix: /usr/local
Configured architecture: x86_64-pc-linux-gnu
Configure host: Workstation-001
Configured by: root
Configured on: Thu Jul 27 15:08:14 UTC 2023
Configure host: Workstation-001
Configure command line: '--enable-mem-debug' '--enable-mem-profile'
'--enable-picky' '--enable-debug' '--enable-timing'
'--enable-ipv6' '--enable-peruse'
'--enable-mpi-fortran' '--enable-mpi-cxx'
'--enable-mpi1-compatibility'
'--enable-grequest-extensions' '--enable-spc'
'--enable-cxx-exceptions' '--enable-event-debug'
Built by: root
Built on: Thu 27 Jul 15:12:22 UTC 2023
Built host: Workstation-001
C bindings: yes
C++ bindings: yes
Fort mpif.h: yes (all)
Fort use mpi: yes (full: ignore TKR)
Fort use mpi size: deprecated-ompi-info-value
Fort use mpi_f08: yes
Fort mpi_f08 compliance: The mpi_f08 module is available, but due to
limitations in the gfortran compiler and/or Open
MPI, does not support the following: array
subsections, direct passthru (where possible) to
underlying Open MPI's C functionality
Fort mpi_f08 subarrays: no
Java bindings: no
Wrapper compiler rpath: runpath
C compiler: gcc
C compiler absolute: /usr/bin/gcc
C compiler family name: GNU
C compiler version: 11.3.0
C++ compiler: g++
C++ compiler absolute: /usr/bin/g++
Fort compiler: gfortran
Fort compiler abs: /usr/bin/gfortran
Fort ignore TKR: yes (!GCC$ ATTRIBUTES NO_ARG_CHECK ::)
Fort 08 assumed shape: yes
Fort optional args: yes
Fort INTERFACE: yes
Fort ISO_FORTRAN_ENV: yes
Fort STORAGE_SIZE: yes
Fort BIND(C) (all): yes
Fort ISO_C_BINDING: yes
Fort SUBROUTINE BIND(C): yes
Fort TYPE,BIND(C): yes
Fort T,BIND(C,name="a"): yes
Fort PRIVATE: yes
Fort PROTECTED: yes
Fort ABSTRACT: yes
Fort ASYNCHRONOUS: yes
Fort PROCEDURE: yes
Fort USE...ONLY: yes
Fort C_FUNLOC: yes
Fort f08 using wrappers: yes
Fort MPI_SIZEOF: yes
C profiling: yes
C++ profiling: yes
Fort mpif.h profiling: yes
Fort use mpi profiling: yes
Fort use mpi_f08 prof: yes
C++ exceptions: yes
Thread support: posix (MPI_THREAD_MULTIPLE: yes, OPAL support: yes,
OMPI progress: no, ORTE progress: yes, Event lib:
yes)
Sparse Groups: no
Internal debug support: yes
MPI interface warnings: yes
MPI parameter check: runtime
Memory profiling support: yes
Memory debugging support: yes
dl support: yes
Heterogeneous support: no
mpirun default --prefix: no
MPI_WTIME support: native
Symbol vis. support: yes
Host topology support: yes
IPv6 support: yes
MPI1 compatibility: yes
MPI extensions: affinity, cuda, pcollreq
FT Checkpoint support: no (checkpoint thread: no)
C/R Enabled Debugging: no
MPI_MAX_PROCESSOR_NAME: 256
MPI_MAX_ERROR_STRING: 256
MPI_MAX_OBJECT_NAME: 64
MPI_MAX_INFO_KEY: 36
MPI_MAX_INFO_VAL: 256
MPI_MAX_PORT_NAME: 1024
MPI_MAX_DATAREP_STRING: 128
MCA allocator: bucket (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA allocator: basic (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA backtrace: execinfo (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA btl: self (MCA v2.1.0, API v3.1.0, Component v4.1.5)
MCA btl: vader (MCA v2.1.0, API v3.1.0, Component v4.1.5)
MCA btl: tcp (MCA v2.1.0, API v3.1.0, Component v4.1.5)
MCA compress: bzip (MCA v2.1.0, API v2.0.0, Component v4.1.5)
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MCA grpcomm: direct (MCA v2.1.0, API v3.0.0, Component v4.1.5)
MCA iof: hnp (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA iof: orted (MCA v2.1.0, API v2.0.0, Component v4.1.5)
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MCA odls: default (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA odls: pspawn (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA oob: tcp (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA plm: slurm (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA plm: rsh (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA plm: isolated (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA ras: simulator (MCA v2.1.0, API v2.0.0, Component
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MCA ras: slurm (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA regx: naive (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA regx: fwd (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA regx: reverse (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA rmaps: ppr (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA rmaps: round_robin (MCA v2.1.0, API v2.0.0, Component
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MCA rmaps: mindist (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA rmaps: rank_file (MCA v2.1.0, API v2.0.0, Component
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MCA rmaps: resilient (MCA v2.1.0, API v2.0.0, Component
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MCA rmaps: seq (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA rml: oob (MCA v2.1.0, API v3.0.0, Component v4.1.5)
MCA routed: radix (MCA v2.1.0, API v3.0.0, Component v4.1.5)
MCA routed: binomial (MCA v2.1.0, API v3.0.0, Component v4.1.5)
MCA routed: direct (MCA v2.1.0, API v3.0.0, Component v4.1.5)
MCA rtc: hwloc (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA schizo: ompi (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA schizo: orte (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA schizo: slurm (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA schizo: jsm (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA schizo: flux (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA state: tool (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA state: hnp (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA state: orted (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA state: app (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA state: novm (MCA v2.1.0, API v1.0.0, Component v4.1.5)
MCA bml: r2 (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA coll: self (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA coll: adapt (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA coll: inter (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA coll: sm (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA coll: basic (MCA v2.1.0, API v2.0.0, Component v4.1.5)
MCA coll: monitoring (MCA v2.1.0, API v2.0.0, Component
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MCA coll: han (MCA v2.1.0, API v2.0.0, Component v4.1.5)
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UPDATE #1 Compiler Flags
FC := mpifort
FFLAGS := -cpp -freal-4-real-8 -fdefault-real-8 -fdefault-double-8 -ffloat-store -Wpedantic -Wall -Wextra -I$(HDRDIR) -I/usr/local/hdf5/include -Jbin/mod
# C compiler options. Check C compiler flags.
CC := mpicc
CFLAGS := -g -I$(HDRDIR) -I/usr/local/hdf5/include
# Libraries
LIBS := -lz -lm -lc -L/usr/local/hdf5/lib/ -lhdf5
UPDATE #2
REAL TYPE
PARAMESH can handle 4 byte and 8 byte REAL types by setting #DEFINE REAL4 or #DEFINE REAL8 in a header file. Depending on the choice in the header, a global variable of type integer amr_mpi_real is defined (see below) and accessible to all processes. This variable is used in all MPI calls where the a REAL datatype is used.
#ifdef REAL8
amr_mpi_real = MPI_DOUBLE_PRECISION
#else
amr_mpi_real = MPI_REAL
#endif
However, type declaration statements in PARAMESH do not specify the KIND attribute of the declared variables. Instead, the PARAMESH manual states that the compiler flags must be set to account for the type of REAL used; -fdefault-real-8 -fdefault-double-8 in my case as I set #DEFINE REAL8.
DATA REDISTRIBUTION
Regarding data redistribution, PARAMESH uses MPI_Type_vector, MPI_Type_create_hvector and MPI_IRECV calls, where the type of REAL used is also important. Depending on the type specified in the header file (REAL4 or REAL8), nbytes takes on different values, which is used then to specify the stride of the vector.
I put together a snippet of the subroutine responsible for data redistribution; the data object to be redistributed is the array real, dimension (:, :, :, :, :,), allocatable :: UNK. After allocation, the size of UNK is constant accros all processes at (nvar, nxb, nyb, nzb, maxblocks).
Do you see any possible pitfalls with the code displayed below?
#ifdef REAL8
nbytes = 8
#else
nbytes = 4
#endif
.
.
.
allocate (unk_test(nvar, nxb, nyb, nzb))
do i = 1, 4
udim_tot(i) = size (unk, dim = i)
udim(i) = size (unk_test, dim = i)
end do
deallocate (unk_test)
call MPI_TYPE_VECTOR ( &
& udim(2), &
& udim(1), &
& udim_tot(1), &
& amr_mpi_real, &
& type1, &
& ierr &
& )
call MPI_Type_create_hvector ( &
& udim(3), &
& 1, &
& int (udim_tot(1) * udim_tot(2) * nbytes, MPI_ADDRESS_KIND), &
& type1, &
& type2, &
& ierr &
& )
call MPI_Type_create_hvector ( &
& udim(4), &
& 1, &
& int (udim_tot(1) * udim_tot(2) * udim_tot(3) * nbytes, MPI_ADDRESS_KIND), &
& type2, &
& type3, &
& ierr &
& )
unk_int_type = type3
call MPI_TYPE_COMMIT (unk_int_type, ierr)
.
.
.
do lb = 1, new_lnblocks
if (.Not. newchild(lb)) Then
if (old_loc(2, lb) /= mype) Then
nrecv = nrecv + 1
call MPI_IRECV ( &
& unk(1, is_unk, js_unk, ks_unk, lb), &
& 1, &
& unk_int_type, &
& old_loc(2, lb), &
& lb, &
& MPI_COMM_WORLD, &
& reqr(nrecv), &
& ierr &
& )
end if
end if
end do
-fcheck=all?