examples: Clarify thread usage
[fio.git] / examples / libpmem.fio
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1[global]
2bs=4k
3size=8g
4ioengine=libpmem
5norandommap
cd041bf4 6time_based
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7group_reporting
8invalidate=1
9disable_lat=1
10disable_slat=1
11disable_clat=1
12clat_percentiles=0
13
14iodepth=1
15iodepth_batch=1
2d21a787 16thread
ae0db592 17numjobs=1
67719e13 18runtime=300
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19
20#
21# In case of 'scramble_buffers=1', the source buffer
2057aedd 22# is rewritten with a random value every write operations.
ae0db592 23#
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24# But when 'scramble_buffers=0' is set, the source buffer isn't
25# rewritten. So it will be likely that the source buffer is in CPU
26# cache and it seems to be high performance.
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27#
28scramble_buffers=0
29
30#
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31# depends on direct option, flags are set for pmem_memcpy() call:
32# direct=1 - PMEM_F_MEM_NONTEMPORAL,
33# direct=0 - PMEM_F_MEM_TEMPORAL.
ae0db592 34#
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35direct=1
36
37#
38# sync=1 means that pmem_drain() is executed for each write operation.
ae0db592 39#
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40sync=1
41
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42
43#
44# Setting for fio process's CPU Node and Memory Node
45#
46numa_cpu_nodes=0
47numa_mem_policy=bind:0
48
49#
50# split means that each job will get a unique CPU from the CPU set
51#
52cpus_allowed_policy=split
53
54#
67719e13 55# The libpmem engine does IO to files in a DAX-mounted filesystem.
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56# The filesystem should be created on an NVDIMM (e.g /dev/pmem0)
57# and then mounted with the '-o dax' option. Note that the engine
58# accesses the underlying NVDIMM directly, bypassing the kernel block
59# layer, so the usual filesystem/disk performance monitoring tools such
60# as iostat will not provide useful data.
61#
62directory=/mnt/pmem0
63
64[libpmem-seqwrite]
65rw=write
66stonewall
67
68#[libpmem-seqread]
69#rw=read
70#stonewall
71
72#[libpmem-randwrite]
73#rw=randwrite
74#stonewall
75
76#[libpmem-randread]
77#rw=randread
78#stonewall