I'm trying to use setrlimit
to limit my memory usage on a Linux system, in order to stop my process from crashing the machine (my code was crashing nodes on a high performance cluster, because a bug led to memory consumption in excess of 100 GiB). I can't seem to find the correct resource to pass to setrlimit
; I think it should be resident, which cannot be limited with setrlimit, but I am confused by resident, heap, stack. In the code below; if I uncomment only RLIMIT_AS
, the code fails with MemoryError
at numpy.ones(shape=(1000, 1000, 10), dtype="f8")
even though that array should be only 80 MB. If I uncomment only RLIMIT_DATA
, RLIMIT_RSS
, or RLIMIT_STACK
both arrays get allocated successfully, even though the total memory usage is 2 GB, or twice the desired maximum.
I would like to make make my program fail (no matter how) as soon as it tries to allocate too much RAM. Why do none of RLIMIT_DATA
, RLIMIT_RSS
, RLIMIT_STACK
and RLIMIT_AS
do what I mean, and what is the correct resource to pass to setrlimit
?
$ cat mwe.py
#!/usr/bin/env python3.5
import resource
import numpy
#rsrc = resource.RLIMIT_AS
#rsrc = resource.RLIMIT_DATA
#rsrc = resource.RLIMIT_RSS
#rsrc = resource.RLIMIT_STACK
soft, hard = resource.getrlimit(rsrc)
print("Limit starts as:", soft, hard)
resource.setrlimit(rsrc, (1e9, 1e9))
soft, hard = resource.getrlimit(rsrc)
print("Limit is now:", soft, hard)
print("Allocating 80 KB, should certainly work")
M1 = numpy.arange(100*100, dtype="u8")
print("Allocating 80 MB, should work")
M2 = numpy.arange(1000*1000*10, dtype="u8")
print("Allocating 2 GB, should fail")
M3 = numpy.arange(1000*1000*250, dtype="u8")
input("Still here…")
Output with the RLIMIT_AS
line uncommented:
$ ./mwe.py
Limit starts as: -1 -1
Limit is now: 1000000000 -1
Allocating 80 KB, should certainly work
Allocating 80 MB, should work
Traceback (most recent call last):
File "./mwe.py", line 22, in <module>
M2 = numpy.arange(1000*1000*10, dtype="u8")
MemoryError
Output when running with any of the other ones uncommented:
$ ./mwe.py
Limit starts as: -1 -1
Limit is now: 1000000000 -1
Allocating 80 KB, should certainly work
Allocating 80 MB, should work
Allocating 2 GB, should fail
Still here…
At the final line, top
reports that my process is using 379 GB VIRT, 2.0 GB RES.
System details:
$ uname -a
Linux host.somewhere.ac.uk 2.6.32-573.3.1.el6.x86_64 #1 SMP Mon Aug 10 09:44:54 EDT 2015 x86_64 x86_64 x86_64 GNU/Linux
$ cat /etc/redhat-release
Red Hat Enterprise Linux Server release 6.7 (Santiago)
$ free -h
total used free shared buffers cached
Mem: 2.0T 1.9T 37G 1.6G 3.4G 1.8T
-/+ buffers/cache: 88G 1.9T
Swap: 464G 4.8M 464G
$ python3.5 --version
Python 3.5.0
$ python3.5 -c "import numpy; print(numpy.__version__)"
1.11.1
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