The swap readahead is an important mechanism to reduce the swap in
latency.  Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.

In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory.  And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.

In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device.  This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally.  So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly.  The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.

The test and result is as follow,

Common test condition
=====================

Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk

Micro-benchmark with combined access pattern
============================================

vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds.  The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.

At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds.  This will trigger random swap-in
in the background.

This is a combined workload with sequential and random memory accessing
at the same time.  The result (for sequential workload) is as follow,

			Base		Optimized
			----		---------
throughput		345413 KB/s	414029 KB/s (+19.9%)
latency.average		97.14 us	61.06 us (-37.1%)
latency.50th		2 us		1 us
latency.60th		2 us		1 us
latency.70th		98 us		2 us
latency.80th		160 us		2 us
latency.90th		260 us		217 us
latency.95th		346 us		369 us
latency.99th		1.34 ms		1.09 ms
ra_hit%			52.69%		99.98%

The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower.  The VMA-base
readahead algorithm works much better.

Linpack
=======

The test memory size is bigger than RAM to trigger swapping.

			Base		Optimized
			----		---------
elapsed_time		393.49 s	329.88 s (-16.2%)
ra_hit%			86.21%		98.82%

The score of base and optimized kernel hasn't visible changes.  But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages.  And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.

Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.comSigned-off-by: N"Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: NAndrew Morton <akpm@linux-foundation.org>
Signed-off-by: NLinus Torvalds <torvalds@linux-foundation.org>