slurm超过了python多处理的作业内存限制

Question

我使用slurm来管理我们的一些计算，但有时任务会因为内存不足而被杀死，尽管事实并非如此。这个奇怪的问题特别是使用多处理的python作业。在

下面是一个简单的例子来重现这种行为

#!/usr/bin/python

from time import sleep

nmem = int(3e7) # this will amount to ~1GB of numbers
nprocs = 200    # will create this many workers later
nsleep = 5      # sleep seconds

array = list(range(nmem))  # allocate some memory

print("done allocating memory")
sleep(nsleep)
print("continuing with multiple processes (" + str(nprocs) + ")")

from multiprocessing import Pool

def f(i):
    sleep(nsleep)

# this will create a pool of workers, each of which "seem" to use 1GB
# even though the individual processes don't actually allocate any memory
p = Pool(nprocs)
p.map(f,list(range(nprocs)))

print("finished successfully")

尽管这可能在本地运行得很好，slurm memory acccounting似乎总结了每个进程的驻留内存，导致nprocs x 1GB的内存使用量，而不是1GB（实际内存使用量）。我认为这不是它应该做的，也不是操作系统正在做的，它看起来没有交换或任何东西。在

这是输出，如果我在本地运行代码

^{pr2}$

还有htop的截图

下面是我使用slurm运行相同命令的输出

> srun --nodelist=compute3 --mem=128G python test-slurm-mem.py 
srun: job 694697 queued and waiting for resources
srun: job 694697 has been allocated resources
done allocating memory
continuing with multiple processes (200)
slurmstepd: Step 694697.0 exceeded memory limit (193419088 > 131968000), being killed
srun: Exceeded job memory limit
srun: Job step aborted: Waiting up to 32 seconds for job step to finish.
slurmstepd: *** STEP 694697.0 ON compute3 CANCELLED AT 2018-09-20T10:22:53 ***
srun: error: compute3: task 0: Killed
> $ sacct --format State,ExitCode,JobName,ReqCPUs,MaxRSS,AveCPU,Elapsed -j 694697.0
     State ExitCode    JobName  ReqCPUS     MaxRSS     AveCPU    Elapsed 
---------- -------- ---------- -------- ---------- ---------- ---------- 
CANCELLED+      0:9     python        2 193419088K   00:00:04   00:00:13