| // SPDX-License-Identifier: GPL-2.0 |
| // Copyright (C) 2016, Linaro Ltd - Daniel Lezcano <daniel.lezcano@linaro.org> |
| |
| #include <linux/kernel.h> |
| #include <linux/percpu.h> |
| #include <linux/slab.h> |
| #include <linux/static_key.h> |
| #include <linux/interrupt.h> |
| #include <linux/idr.h> |
| #include <linux/irq.h> |
| #include <linux/math64.h> |
| #include <linux/log2.h> |
| |
| #include <trace/events/irq.h> |
| |
| #include "internals.h" |
| |
| DEFINE_STATIC_KEY_FALSE(irq_timing_enabled); |
| |
| DEFINE_PER_CPU(struct irq_timings, irq_timings); |
| |
| static DEFINE_IDR(irqt_stats); |
| |
| void irq_timings_enable(void) |
| { |
| static_branch_enable(&irq_timing_enabled); |
| } |
| |
| void irq_timings_disable(void) |
| { |
| static_branch_disable(&irq_timing_enabled); |
| } |
| |
| /* |
| * The main goal of this algorithm is to predict the next interrupt |
| * occurrence on the current CPU. |
| * |
| * Currently, the interrupt timings are stored in a circular array |
| * buffer every time there is an interrupt, as a tuple: the interrupt |
| * number and the associated timestamp when the event occurred <irq, |
| * timestamp>. |
| * |
| * For every interrupt occurring in a short period of time, we can |
| * measure the elapsed time between the occurrences for the same |
| * interrupt and we end up with a suite of intervals. The experience |
| * showed the interrupts are often coming following a periodic |
| * pattern. |
| * |
| * The objective of the algorithm is to find out this periodic pattern |
| * in a fastest way and use its period to predict the next irq event. |
| * |
| * When the next interrupt event is requested, we are in the situation |
| * where the interrupts are disabled and the circular buffer |
| * containing the timings is filled with the events which happened |
| * after the previous next-interrupt-event request. |
| * |
| * At this point, we read the circular buffer and we fill the irq |
| * related statistics structure. After this step, the circular array |
| * containing the timings is empty because all the values are |
| * dispatched in their corresponding buffers. |
| * |
| * Now for each interrupt, we can predict the next event by using the |
| * suffix array, log interval and exponential moving average |
| * |
| * 1. Suffix array |
| * |
| * Suffix array is an array of all the suffixes of a string. It is |
| * widely used as a data structure for compression, text search, ... |
| * For instance for the word 'banana', the suffixes will be: 'banana' |
| * 'anana' 'nana' 'ana' 'na' 'a' |
| * |
| * Usually, the suffix array is sorted but for our purpose it is |
| * not necessary and won't provide any improvement in the context of |
| * the solved problem where we clearly define the boundaries of the |
| * search by a max period and min period. |
| * |
| * The suffix array will build a suite of intervals of different |
| * length and will look for the repetition of each suite. If the suite |
| * is repeating then we have the period because it is the length of |
| * the suite whatever its position in the buffer. |
| * |
| * 2. Log interval |
| * |
| * We saw the irq timings allow to compute the interval of the |
| * occurrences for a specific interrupt. We can reasonibly assume the |
| * longer is the interval, the higher is the error for the next event |
| * and we can consider storing those interval values into an array |
| * where each slot in the array correspond to an interval at the power |
| * of 2 of the index. For example, index 12 will contain values |
| * between 2^11 and 2^12. |
| * |
| * At the end we have an array of values where at each index defines a |
| * [2^index - 1, 2 ^ index] interval values allowing to store a large |
| * number of values inside a small array. |
| * |
| * For example, if we have the value 1123, then we store it at |
| * ilog2(1123) = 10 index value. |
| * |
| * Storing those value at the specific index is done by computing an |
| * exponential moving average for this specific slot. For instance, |
| * for values 1800, 1123, 1453, ... fall under the same slot (10) and |
| * the exponential moving average is computed every time a new value |
| * is stored at this slot. |
| * |
| * 3. Exponential Moving Average |
| * |
| * The EMA is largely used to track a signal for stocks or as a low |
| * pass filter. The magic of the formula, is it is very simple and the |
| * reactivity of the average can be tuned with the factors called |
| * alpha. |
| * |
| * The higher the alphas are, the faster the average respond to the |
| * signal change. In our case, if a slot in the array is a big |
| * interval, we can have numbers with a big difference between |
| * them. The impact of those differences in the average computation |
| * can be tuned by changing the alpha value. |
| * |
| * |
| * -- The algorithm -- |
| * |
| * We saw the different processing above, now let's see how they are |
| * used together. |
| * |
| * For each interrupt: |
| * For each interval: |
| * Compute the index = ilog2(interval) |
| * Compute a new_ema(buffer[index], interval) |
| * Store the index in a circular buffer |
| * |
| * Compute the suffix array of the indexes |
| * |
| * For each suffix: |
| * If the suffix is reverse-found 3 times |
| * Return suffix |
| * |
| * Return Not found |
| * |
| * However we can not have endless suffix array to be build, it won't |
| * make sense and it will add an extra overhead, so we can restrict |
| * this to a maximum suffix length of 5 and a minimum suffix length of |
| * 2. The experience showed 5 is the majority of the maximum pattern |
| * period found for different devices. |
| * |
| * The result is a pattern finding less than 1us for an interrupt. |
| * |
| * Example based on real values: |
| * |
| * Example 1 : MMC write/read interrupt interval: |
| * |
| * 223947, 1240, 1384, 1386, 1386, |
| * 217416, 1236, 1384, 1386, 1387, |
| * 214719, 1241, 1386, 1387, 1384, |
| * 213696, 1234, 1384, 1386, 1388, |
| * 219904, 1240, 1385, 1389, 1385, |
| * 212240, 1240, 1386, 1386, 1386, |
| * 214415, 1236, 1384, 1386, 1387, |
| * 214276, 1234, 1384, 1388, ? |
| * |
| * For each element, apply ilog2(value) |
| * |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, ? |
| * |
| * Max period of 5, we take the last (max_period * 3) 15 elements as |
| * we can be confident if the pattern repeats itself three times it is |
| * a repeating pattern. |
| * |
| * 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, 8, |
| * 15, 8, 8, 8, ? |
| * |
| * Suffixes are: |
| * |
| * 1) 8, 15, 8, 8, 8 <- max period |
| * 2) 8, 15, 8, 8 |
| * 3) 8, 15, 8 |
| * 4) 8, 15 <- min period |
| * |
| * From there we search the repeating pattern for each suffix. |
| * |
| * buffer: 8, 15, 8, 8, 8, 8, 15, 8, 8, 8, 8, 15, 8, 8, 8 |
| * | | | | | | | | | | | | | | | |
| * 8, 15, 8, 8, 8 | | | | | | | | | | |
| * 8, 15, 8, 8, 8 | | | | | |
| * 8, 15, 8, 8, 8 |
| * |
| * When moving the suffix, we found exactly 3 matches. |
| * |
| * The first suffix with period 5 is repeating. |
| * |
| * The next event is (3 * max_period) % suffix_period |
| * |
| * In this example, the result 0, so the next event is suffix[0] => 8 |
| * |
| * However, 8 is the index in the array of exponential moving average |
| * which was calculated on the fly when storing the values, so the |
| * interval is ema[8] = 1366 |
| * |
| * |
| * Example 2: |
| * |
| * 4, 3, 5, 100, |
| * 3, 3, 5, 117, |
| * 4, 4, 5, 112, |
| * 4, 3, 4, 110, |
| * 3, 5, 3, 117, |
| * 4, 4, 5, 112, |
| * 4, 3, 4, 110, |
| * 3, 4, 5, 112, |
| * 4, 3, 4, 110 |
| * |
| * ilog2 |
| * |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4 |
| * |
| * Max period 5: |
| * 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4, |
| * 0, 0, 0, 4 |
| * |
| * Suffixes: |
| * |
| * 1) 0, 0, 4, 0, 0 |
| * 2) 0, 0, 4, 0 |
| * 3) 0, 0, 4 |
| * 4) 0, 0 |
| * |
| * buffer: 0, 0, 4, 0, 0, 0, 4, 0, 0, 0, 4, 0, 0, 0, 4 |
| * | | | | | | X |
| * 0, 0, 4, 0, 0, | X |
| * 0, 0 |
| * |
| * buffer: 0, 0, 4, 0, 0, 0, 4, 0, 0, 0, 4, 0, 0, 0, 4 |
| * | | | | | | | | | | | | | | | |
| * 0, 0, 4, 0, | | | | | | | | | | | |
| * 0, 0, 4, 0, | | | | | | | |
| * 0, 0, 4, 0, | | | |
| * 0 0 4 |
| * |
| * Pattern is found 3 times, the remaining is 1 which results from |
| * (max_period * 3) % suffix_period. This value is the index in the |
| * suffix arrays. The suffix array for a period 4 has the value 4 |
| * at index 1. |
| */ |
| #define EMA_ALPHA_VAL 64 |
| #define EMA_ALPHA_SHIFT 7 |
| |
| #define PREDICTION_PERIOD_MIN 2 |
| #define PREDICTION_PERIOD_MAX 5 |
| #define PREDICTION_FACTOR 4 |
| #define PREDICTION_MAX 10 /* 2 ^ PREDICTION_MAX useconds */ |
| #define PREDICTION_BUFFER_SIZE 16 /* slots for EMAs, hardly more than 16 */ |
| |
| struct irqt_stat { |
| u64 last_ts; |
| u64 ema_time[PREDICTION_BUFFER_SIZE]; |
| int timings[IRQ_TIMINGS_SIZE]; |
| int circ_timings[IRQ_TIMINGS_SIZE]; |
| int count; |
| }; |
| |
| /* |
| * Exponential moving average computation |
| */ |
| static u64 irq_timings_ema_new(u64 value, u64 ema_old) |
| { |
| s64 diff; |
| |
| if (unlikely(!ema_old)) |
| return value; |
| |
| diff = (value - ema_old) * EMA_ALPHA_VAL; |
| /* |
| * We can use a s64 type variable to be added with the u64 |
| * ema_old variable as this one will never have its topmost |
| * bit set, it will be always smaller than 2^63 nanosec |
| * interrupt interval (292 years). |
| */ |
| return ema_old + (diff >> EMA_ALPHA_SHIFT); |
| } |
| |
| static int irq_timings_next_event_index(int *buffer, size_t len, int period_max) |
| { |
| int i; |
| |
| /* |
| * The buffer contains the suite of intervals, in a ilog2 |
| * basis, we are looking for a repetition. We point the |
| * beginning of the search three times the length of the |
| * period beginning at the end of the buffer. We do that for |
| * each suffix. |
| */ |
| for (i = period_max; i >= PREDICTION_PERIOD_MIN ; i--) { |
| |
| int *begin = &buffer[len - (i * 3)]; |
| int *ptr = begin; |
| |
| /* |
| * We look if the suite with period 'i' repeat |
| * itself. If it is truncated at the end, as it |
| * repeats we can use the period to find out the next |
| * element. |
| */ |
| while (!memcmp(ptr, begin, i * sizeof(*ptr))) { |
| ptr += i; |
| if (ptr >= &buffer[len]) |
| return begin[((i * 3) % i)]; |
| } |
| } |
| |
| return -1; |
| } |
| |
| static u64 __irq_timings_next_event(struct irqt_stat *irqs, int irq, u64 now) |
| { |
| int index, i, period_max, count, start, min = INT_MAX; |
| |
| if ((now - irqs->last_ts) >= NSEC_PER_SEC) { |
| irqs->count = irqs->last_ts = 0; |
| return U64_MAX; |
| } |
| |
| /* |
| * As we want to find three times the repetition, we need a |
| * number of intervals greater or equal to three times the |
| * maximum period, otherwise we truncate the max period. |
| */ |
| period_max = irqs->count > (3 * PREDICTION_PERIOD_MAX) ? |
| PREDICTION_PERIOD_MAX : irqs->count / 3; |
| |
| /* |
| * If we don't have enough irq timings for this prediction, |
| * just bail out. |
| */ |
| if (period_max <= PREDICTION_PERIOD_MIN) |
| return U64_MAX; |
| |
| /* |
| * 'count' will depends if the circular buffer wrapped or not |
| */ |
| count = irqs->count < IRQ_TIMINGS_SIZE ? |
| irqs->count : IRQ_TIMINGS_SIZE; |
| |
| start = irqs->count < IRQ_TIMINGS_SIZE ? |
| 0 : (irqs->count & IRQ_TIMINGS_MASK); |
| |
| /* |
| * Copy the content of the circular buffer into another buffer |
| * in order to linearize the buffer instead of dealing with |
| * wrapping indexes and shifted array which will be prone to |
| * error and extremelly difficult to debug. |
| */ |
| for (i = 0; i < count; i++) { |
| int index = (start + i) & IRQ_TIMINGS_MASK; |
| |
| irqs->timings[i] = irqs->circ_timings[index]; |
| min = min_t(int, irqs->timings[i], min); |
| } |
| |
| index = irq_timings_next_event_index(irqs->timings, count, period_max); |
| if (index < 0) |
| return irqs->last_ts + irqs->ema_time[min]; |
| |
| return irqs->last_ts + irqs->ema_time[index]; |
| } |
| |
| static inline void irq_timings_store(int irq, struct irqt_stat *irqs, u64 ts) |
| { |
| u64 old_ts = irqs->last_ts; |
| u64 interval; |
| int index; |
| |
| /* |
| * The timestamps are absolute time values, we need to compute |
| * the timing interval between two interrupts. |
| */ |
| irqs->last_ts = ts; |
| |
| /* |
| * The interval type is u64 in order to deal with the same |
| * type in our computation, that prevent mindfuck issues with |
| * overflow, sign and division. |
| */ |
| interval = ts - old_ts; |
| |
| /* |
| * The interrupt triggered more than one second apart, that |
| * ends the sequence as predictible for our purpose. In this |
| * case, assume we have the beginning of a sequence and the |
| * timestamp is the first value. As it is impossible to |
| * predict anything at this point, return. |
| * |
| * Note the first timestamp of the sequence will always fall |
| * in this test because the old_ts is zero. That is what we |
| * want as we need another timestamp to compute an interval. |
| */ |
| if (interval >= NSEC_PER_SEC) { |
| irqs->count = 0; |
| return; |
| } |
| |
| /* |
| * Get the index in the ema table for this interrupt. The |
| * PREDICTION_FACTOR increase the interval size for the array |
| * of exponential average. |
| */ |
| index = likely(interval) ? |
| ilog2((interval >> 10) / PREDICTION_FACTOR) : 0; |
| |
| /* |
| * Store the index as an element of the pattern in another |
| * circular array. |
| */ |
| irqs->circ_timings[irqs->count & IRQ_TIMINGS_MASK] = index; |
| |
| irqs->ema_time[index] = irq_timings_ema_new(interval, |
| irqs->ema_time[index]); |
| |
| irqs->count++; |
| } |
| |
| /** |
| * irq_timings_next_event - Return when the next event is supposed to arrive |
| * |
| * During the last busy cycle, the number of interrupts is incremented |
| * and stored in the irq_timings structure. This information is |
| * necessary to: |
| * |
| * - know if the index in the table wrapped up: |
| * |
| * If more than the array size interrupts happened during the |
| * last busy/idle cycle, the index wrapped up and we have to |
| * begin with the next element in the array which is the last one |
| * in the sequence, otherwise it is a the index 0. |
| * |
| * - have an indication of the interrupts activity on this CPU |
| * (eg. irq/sec) |
| * |
| * The values are 'consumed' after inserting in the statistical model, |
| * thus the count is reinitialized. |
| * |
| * The array of values **must** be browsed in the time direction, the |
| * timestamp must increase between an element and the next one. |
| * |
| * Returns a nanosec time based estimation of the earliest interrupt, |
| * U64_MAX otherwise. |
| */ |
| u64 irq_timings_next_event(u64 now) |
| { |
| struct irq_timings *irqts = this_cpu_ptr(&irq_timings); |
| struct irqt_stat *irqs; |
| struct irqt_stat __percpu *s; |
| u64 ts, next_evt = U64_MAX; |
| int i, irq = 0; |
| |
| /* |
| * This function must be called with the local irq disabled in |
| * order to prevent the timings circular buffer to be updated |
| * while we are reading it. |
| */ |
| lockdep_assert_irqs_disabled(); |
| |
| if (!irqts->count) |
| return next_evt; |
| |
| /* |
| * Number of elements in the circular buffer: If it happens it |
| * was flushed before, then the number of elements could be |
| * smaller than IRQ_TIMINGS_SIZE, so the count is used, |
| * otherwise the array size is used as we wrapped. The index |
| * begins from zero when we did not wrap. That could be done |
| * in a nicer way with the proper circular array structure |
| * type but with the cost of extra computation in the |
| * interrupt handler hot path. We choose efficiency. |
| * |
| * Inject measured irq/timestamp to the pattern prediction |
| * model while decrementing the counter because we consume the |
| * data from our circular buffer. |
| */ |
| |
| i = (irqts->count & IRQ_TIMINGS_MASK) - 1; |
| irqts->count = min(IRQ_TIMINGS_SIZE, irqts->count); |
| |
| for (; irqts->count > 0; irqts->count--, i = (i + 1) & IRQ_TIMINGS_MASK) { |
| irq = irq_timing_decode(irqts->values[i], &ts); |
| s = idr_find(&irqt_stats, irq); |
| if (s) |
| irq_timings_store(irq, this_cpu_ptr(s), ts); |
| } |
| |
| /* |
| * Look in the list of interrupts' statistics, the earliest |
| * next event. |
| */ |
| idr_for_each_entry(&irqt_stats, s, i) { |
| |
| irqs = this_cpu_ptr(s); |
| |
| ts = __irq_timings_next_event(irqs, i, now); |
| if (ts <= now) |
| return now; |
| |
| if (ts < next_evt) |
| next_evt = ts; |
| } |
| |
| return next_evt; |
| } |
| |
| void irq_timings_free(int irq) |
| { |
| struct irqt_stat __percpu *s; |
| |
| s = idr_find(&irqt_stats, irq); |
| if (s) { |
| free_percpu(s); |
| idr_remove(&irqt_stats, irq); |
| } |
| } |
| |
| int irq_timings_alloc(int irq) |
| { |
| struct irqt_stat __percpu *s; |
| int id; |
| |
| /* |
| * Some platforms can have the same private interrupt per cpu, |
| * so this function may be be called several times with the |
| * same interrupt number. Just bail out in case the per cpu |
| * stat structure is already allocated. |
| */ |
| s = idr_find(&irqt_stats, irq); |
| if (s) |
| return 0; |
| |
| s = alloc_percpu(*s); |
| if (!s) |
| return -ENOMEM; |
| |
| idr_preload(GFP_KERNEL); |
| id = idr_alloc(&irqt_stats, s, irq, irq + 1, GFP_NOWAIT); |
| idr_preload_end(); |
| |
| if (id < 0) { |
| free_percpu(s); |
| return id; |
| } |
| |
| return 0; |
| } |