diff options
| author | Kees Cook <kees+treewide@kernel.org> | 2026-09-02 15:31:14 -0700 |
|---|---|---|
| committer | Kees Cook <kees@kernel.org> | 2026-09-04 21:37:00 -0700 |
| commit | 3a2c4d55e32ad65efebdb6de44eef3bfa08bb49d (patch) | |
| tree | c65086f9bdcd48c6360fb7cb4598bca084da1f32 /lib/win_minmax.c | |
| download | linux-stable-3a2c4d55e32ad65efebdb6de44eef3bfa08bb49d.tar.gz linux-stable-3a2c4d55e32ad65efebdb6de44eef3bfa08bb49d.zip | |
treewide: refresh kmalloc_obj() conversionsgrafted
This is another run of the Coccinelle script for converting kmalloc()
family of allocations to kmalloc_obj() via the existing rules in
scripts/coccinelle/api/kmalloc_objs.cocci
This catches both the set of kmalloc() uses added since the first
kmalloc_obj() conversions in v7.0 and adds a large group missed in the
first pass due to Coccinelle not interacting well with the cleanup.h
scoped_...() family of macros[1]. I worked around this with spatch's
"--macro-file" argument to a file with all the scoped_...() macros mapped
to Coccinelle's YACFE_ITERATOR[2] as that was the closest viable control
flow indicator I could find.
Build tested allmodconfig on x86, arm64, arm, loongarch, mips, powerpc,
riscv, and s390 with no new warnings.
Link: https://lore.kernel.org/lkml/202609021314.8A9C0B8@keescook/ [1]
Link: https://github.com/coccinelle/coccinelle/blob/master/standard.h [2]
Signed-off-by: Kees Cook <kees+treewide@kernel.org>
Diffstat (limited to 'lib/win_minmax.c')
| -rw-r--r-- | lib/win_minmax.c | 100 |
1 files changed, 100 insertions, 0 deletions
diff --git a/lib/win_minmax.c b/lib/win_minmax.c new file mode 100644 index 000000000..1682e6143 --- /dev/null +++ b/lib/win_minmax.c @@ -0,0 +1,100 @@ +// SPDX-License-Identifier: GPL-2.0 +/* + * lib/minmax.c: windowed min/max tracker + * + * Kathleen Nichols' algorithm for tracking the minimum (or maximum) + * value of a data stream over some fixed time interval. (E.g., + * the minimum RTT over the past five minutes.) It uses constant + * space and constant time per update yet almost always delivers + * the same minimum as an implementation that has to keep all the + * data in the window. + * + * The algorithm keeps track of the best, 2nd best & 3rd best min + * values, maintaining an invariant that the measurement time of + * the n'th best >= n-1'th best. It also makes sure that the three + * values are widely separated in the time window since that bounds + * the worse case error when that data is monotonically increasing + * over the window. + * + * Upon getting a new min, we can forget everything earlier because + * it has no value - the new min is <= everything else in the window + * by definition and it's the most recent. So we restart fresh on + * every new min and overwrites 2nd & 3rd choices. The same property + * holds for 2nd & 3rd best. + */ +#include <linux/module.h> +#include <linux/win_minmax.h> + +/* As time advances, update the 1st, 2nd, and 3rd choices. */ +static u32 minmax_subwin_update(struct minmax *m, u32 win, + const struct minmax_sample *val) +{ + u32 dt = val->t - m->s[0].t; + + if (unlikely(dt > win)) { + /* + * Passed entire window without a new val so make 2nd + * choice the new val & 3rd choice the new 2nd choice. + * we may have to iterate this since our 2nd choice + * may also be outside the window (we checked on entry + * that the third choice was in the window). + */ + m->s[0] = m->s[1]; + m->s[1] = m->s[2]; + m->s[2] = *val; + if (unlikely(val->t - m->s[0].t > win)) { + m->s[0] = m->s[1]; + m->s[1] = m->s[2]; + m->s[2] = *val; + } + } else if (unlikely(m->s[1].t == m->s[0].t) && dt > win/4) { + /* + * We've passed a quarter of the window without a new val + * so take a 2nd choice from the 2nd quarter of the window. + */ + m->s[2] = m->s[1] = *val; + } else if (unlikely(m->s[2].t == m->s[1].t) && dt > win/2) { + /* + * We've passed half the window without finding a new val + * so take a 3rd choice from the last half of the window + */ + m->s[2] = *val; + } + return m->s[0].v; +} + +/* Check if new measurement updates the 1st, 2nd or 3rd choice max. */ +u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas) +{ + struct minmax_sample val = { .t = t, .v = meas }; + + if (unlikely(val.v >= m->s[0].v) || /* found new max? */ + unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ + return minmax_reset(m, t, meas); /* forget earlier samples */ + + if (unlikely(val.v >= m->s[1].v)) + m->s[2] = m->s[1] = val; + else if (unlikely(val.v >= m->s[2].v)) + m->s[2] = val; + + return minmax_subwin_update(m, win, &val); +} +EXPORT_SYMBOL(minmax_running_max); + +/* Check if new measurement updates the 1st, 2nd or 3rd choice min. */ +u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas) +{ + struct minmax_sample val = { .t = t, .v = meas }; + + if (unlikely(val.v <= m->s[0].v) || /* found new min? */ + unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ + return minmax_reset(m, t, meas); /* forget earlier samples */ + + if (unlikely(val.v <= m->s[1].v)) + m->s[2] = m->s[1] = val; + else if (unlikely(val.v <= m->s[2].v)) + m->s[2] = val; + + return minmax_subwin_update(m, win, &val); +} +EXPORT_SYMBOL(minmax_running_min); |
