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-rw-r--r--include/linux/win_minmax.h37
-rw-r--r--lib/Makefile2
-rw-r--r--lib/win_minmax.c98
3 files changed, 136 insertions, 1 deletions
diff --git a/include/linux/win_minmax.h b/include/linux/win_minmax.h
new file mode 100644
index 000000000000..56569604278f
--- /dev/null
+++ b/include/linux/win_minmax.h
@@ -0,0 +1,37 @@
+/**
+ * lib/minmax.c: windowed min/max tracker by Kathleen Nichols.
+ *
+ */
+#ifndef MINMAX_H
+#define MINMAX_H
+
+#include <linux/types.h>
+
+/* A single data point for our parameterized min-max tracker */
+struct minmax_sample {
+ u32 t; /* time measurement was taken */
+ u32 v; /* value measured */
+};
+
+/* State for the parameterized min-max tracker */
+struct minmax {
+ struct minmax_sample s[3];
+};
+
+static inline u32 minmax_get(const struct minmax *m)
+{
+ return m->s[0].v;
+}
+
+static inline u32 minmax_reset(struct minmax *m, u32 t, u32 meas)
+{
+ struct minmax_sample val = { .t = t, .v = meas };
+
+ m->s[2] = m->s[1] = m->s[0] = val;
+ return m->s[0].v;
+}
+
+u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas);
+u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas);
+
+#endif
diff --git a/lib/Makefile b/lib/Makefile
index 5dc77a8ec297..df747e5eeb7a 100644
--- a/lib/Makefile
+++ b/lib/Makefile
@@ -22,7 +22,7 @@ lib-y := ctype.o string.o vsprintf.o cmdline.o \
sha1.o chacha20.o md5.o irq_regs.o argv_split.o \
flex_proportions.o ratelimit.o show_mem.o \
is_single_threaded.o plist.o decompress.o kobject_uevent.o \
- earlycpio.o seq_buf.o nmi_backtrace.o nodemask.o
+ earlycpio.o seq_buf.o nmi_backtrace.o nodemask.o win_minmax.o
lib-$(CONFIG_MMU) += ioremap.o
lib-$(CONFIG_SMP) += cpumask.o
diff --git a/lib/win_minmax.c b/lib/win_minmax.c
new file mode 100644
index 000000000000..c8420d404926
--- /dev/null
+++ b/lib/win_minmax.c
@@ -0,0 +1,98 @@
+/**
+ * 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);
+}