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99 lines
3.4 KiB
99 lines
3.4 KiB
// SPDX-License-Identifier: GPL-2.0 |
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/** |
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* lib/minmax.c: windowed min/max tracker |
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* |
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* Kathleen Nichols' algorithm for tracking the minimum (or maximum) |
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* value of a data stream over some fixed time interval. (E.g., |
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* the minimum RTT over the past five minutes.) It uses constant |
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* space and constant time per update yet almost always delivers |
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* the same minimum as an implementation that has to keep all the |
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* data in the window. |
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* |
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* The algorithm keeps track of the best, 2nd best & 3rd best min |
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* values, maintaining an invariant that the measurement time of |
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* the n'th best >= n-1'th best. It also makes sure that the three |
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* values are widely separated in the time window since that bounds |
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* the worse case error when that data is monotonically increasing |
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* over the window. |
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* |
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* Upon getting a new min, we can forget everything earlier because |
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* it has no value - the new min is <= everything else in the window |
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* by definition and it's the most recent. So we restart fresh on |
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* every new min and overwrites 2nd & 3rd choices. The same property |
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* holds for 2nd & 3rd best. |
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*/ |
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#include <linux/module.h> |
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#include <linux/win_minmax.h> |
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/* As time advances, update the 1st, 2nd, and 3rd choices. */ |
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static u32 minmax_subwin_update(struct minmax *m, u32 win, |
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const struct minmax_sample *val) |
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{ |
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u32 dt = val->t - m->s[0].t; |
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if (unlikely(dt > win)) { |
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/* |
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* Passed entire window without a new val so make 2nd |
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* choice the new val & 3rd choice the new 2nd choice. |
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* we may have to iterate this since our 2nd choice |
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* may also be outside the window (we checked on entry |
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* that the third choice was in the window). |
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*/ |
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m->s[0] = m->s[1]; |
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m->s[1] = m->s[2]; |
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m->s[2] = *val; |
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if (unlikely(val->t - m->s[0].t > win)) { |
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m->s[0] = m->s[1]; |
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m->s[1] = m->s[2]; |
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m->s[2] = *val; |
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} |
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} else if (unlikely(m->s[1].t == m->s[0].t) && dt > win/4) { |
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/* |
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* We've passed a quarter of the window without a new val |
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* so take a 2nd choice from the 2nd quarter of the window. |
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*/ |
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m->s[2] = m->s[1] = *val; |
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} else if (unlikely(m->s[2].t == m->s[1].t) && dt > win/2) { |
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/* |
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* We've passed half the window without finding a new val |
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* so take a 3rd choice from the last half of the window |
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*/ |
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m->s[2] = *val; |
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} |
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return m->s[0].v; |
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} |
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/* Check if new measurement updates the 1st, 2nd or 3rd choice max. */ |
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u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas) |
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{ |
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struct minmax_sample val = { .t = t, .v = meas }; |
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if (unlikely(val.v >= m->s[0].v) || /* found new max? */ |
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unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ |
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return minmax_reset(m, t, meas); /* forget earlier samples */ |
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if (unlikely(val.v >= m->s[1].v)) |
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m->s[2] = m->s[1] = val; |
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else if (unlikely(val.v >= m->s[2].v)) |
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m->s[2] = val; |
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return minmax_subwin_update(m, win, &val); |
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} |
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EXPORT_SYMBOL(minmax_running_max); |
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/* Check if new measurement updates the 1st, 2nd or 3rd choice min. */ |
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u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas) |
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{ |
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struct minmax_sample val = { .t = t, .v = meas }; |
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if (unlikely(val.v <= m->s[0].v) || /* found new min? */ |
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unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ |
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return minmax_reset(m, t, meas); /* forget earlier samples */ |
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if (unlikely(val.v <= m->s[1].v)) |
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m->s[2] = m->s[1] = val; |
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else if (unlikely(val.v <= m->s[2].v)) |
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m->s[2] = val; |
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return minmax_subwin_update(m, win, &val); |
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}
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