Message ID | 20231110165314.1559285-1-visitorckw@gmail.com (mailing list archive) |
---|---|
State | Accepted |
Commit | d131f1f3b459980d38a59adc3598c96cc3a6ad5e |
Headers | show |
Series | [v2] platform/chrome: sensorhub: Implement quickselect for median calculation | expand |
Hello: This patch was applied to chrome-platform/linux.git (for-kernelci) by Tzung-Bi Shih <tzungbi@kernel.org>: On Sat, 11 Nov 2023 00:53:14 +0800 you wrote: > The cros_ec_sensor_ring_median function currently uses an inefficient > sorting algorithm (> O(n)) to find the median of an array. This patch > replaces the sorting approach with the quickselect algorithm, which > achieves an average time complexity of O(n). > > The algorithm employs the median-of-three rule to select the pivot, > mitigating worst-case scenarios and reducing the expected number of > necessary comparisons. This strategy enhances the algorithm's > efficiency and ensures a more balanced partitioning. > > [...] Here is the summary with links: - [v2] platform/chrome: sensorhub: Implement quickselect for median calculation https://git.kernel.org/chrome-platform/c/d131f1f3b459 You are awesome, thank you!
Hello: This patch was applied to chrome-platform/linux.git (for-next) by Tzung-Bi Shih <tzungbi@kernel.org>: On Sat, 11 Nov 2023 00:53:14 +0800 you wrote: > The cros_ec_sensor_ring_median function currently uses an inefficient > sorting algorithm (> O(n)) to find the median of an array. This patch > replaces the sorting approach with the quickselect algorithm, which > achieves an average time complexity of O(n). > > The algorithm employs the median-of-three rule to select the pivot, > mitigating worst-case scenarios and reducing the expected number of > necessary comparisons. This strategy enhances the algorithm's > efficiency and ensures a more balanced partitioning. > > [...] Here is the summary with links: - [v2] platform/chrome: sensorhub: Implement quickselect for median calculation https://git.kernel.org/chrome-platform/c/d131f1f3b459 You are awesome, thank you!
diff --git a/drivers/platform/chrome/cros_ec_sensorhub_ring.c b/drivers/platform/chrome/cros_ec_sensorhub_ring.c index 9e17f7483ca0..1205219515d6 100644 --- a/drivers/platform/chrome/cros_ec_sensorhub_ring.c +++ b/drivers/platform/chrome/cros_ec_sensorhub_ring.c @@ -133,33 +133,61 @@ int cros_ec_sensorhub_ring_fifo_enable(struct cros_ec_sensorhub *sensorhub, return ret; } -static int cros_ec_sensor_ring_median_cmp(const void *pv1, const void *pv2) +static void cros_ec_sensor_ring_median_swap(s64 *a, s64 *b) { - s64 v1 = *(s64 *)pv1; - s64 v2 = *(s64 *)pv2; - - if (v1 > v2) - return 1; - else if (v1 < v2) - return -1; - else - return 0; + s64 tmp = *a; + *a = *b; + *b = tmp; } /* * cros_ec_sensor_ring_median: Gets median of an array of numbers * - * For now it's implemented using an inefficient > O(n) sort then return - * the middle element. A more optimal method would be something like - * quickselect, but given that n = 64 we can probably live with it in the - * name of clarity. + * It's implemented using the quickselect algorithm, which achieves an + * average time complexity of O(n) the middle element. In the worst case, + * the runtime of quickselect could regress to O(n^2). To mitigate this, + * algorithms like median-of-medians exist, which can guarantee O(n) even + * in the worst case. However, these algorithms come with a higher + * overhead and are more complex to implement, making quickselect a + * pragmatic choice for our use case. * - * Warning: the input array gets modified (sorted)! + * Warning: the input array gets modified! */ static s64 cros_ec_sensor_ring_median(s64 *array, size_t length) { - sort(array, length, sizeof(s64), cros_ec_sensor_ring_median_cmp, NULL); - return array[length / 2]; + int lo = 0; + int hi = length - 1; + + while (lo <= hi) { + int mid = lo + (hi - lo) / 2; + int pivot, i; + + if (array[lo] > array[mid]) + cros_ec_sensor_ring_median_swap(&array[lo], &array[mid]); + if (array[lo] > array[hi]) + cros_ec_sensor_ring_median_swap(&array[lo], &array[hi]); + if (array[mid] < array[hi]) + cros_ec_sensor_ring_median_swap(&array[mid], &array[hi]); + + pivot = array[hi]; + i = lo - 1; + + for (int j = lo; j < hi; j++) + if (array[j] < pivot) + cros_ec_sensor_ring_median_swap(&array[++i], &array[j]); + + /* The pivot's index corresponds to i+1. */ + cros_ec_sensor_ring_median_swap(&array[i + 1], &array[hi]); + if (i + 1 == length / 2) + return array[i + 1]; + if (i + 1 > length / 2) + hi = i; + else + lo = i + 2; + } + + /* Should never reach here. */ + return -1; } /*
The cros_ec_sensor_ring_median function currently uses an inefficient sorting algorithm (> O(n)) to find the median of an array. This patch replaces the sorting approach with the quickselect algorithm, which achieves an average time complexity of O(n). The algorithm employs the median-of-three rule to select the pivot, mitigating worst-case scenarios and reducing the expected number of necessary comparisons. This strategy enhances the algorithm's efficiency and ensures a more balanced partitioning. In the worst case, the runtime of quickselect could regress to O(n^2). To address this, alternative algorithms like median-of-medians that can guarantee O(n) even in the worst case. However, due to higher overhead and increased complexity of implementation, quickselect remains a pragmatic choice for our use case. Signed-off-by: Kuan-Wei Chiu <visitorckw@gmail.com> --- v1 -> v2: * Separate patch series into two patches. * Modify the microbenchmark[1] to set n=64 and run 10000 repeated times. * Enhance coding style and comments. [1]: static void init_array(s64 *arr, size_t length, s64 seed) { for (int i = 0; i < length; i++) { seed = (seed * 725861) % 6599; arr[i] = seed; } } static int quickselect_test(void) { s64 *arr; s64 median_old, median_new; ktime_t start, end; s64 delta, time_old = 0, time_new = 0; const size_t array_length = 64; const size_t round = 10000; arr = kmalloc(array_length * sizeof(s64), GFP_KERNEL); if (!arr) return -ENOMEM; for(size_t i = 0; i < round; i++) { init_array(arr, array_length, i + 1); start = ktime_get(); median_old = cros_ec_sensor_ring_median(arr, array_length); end = ktime_get(); delta = ktime_us_delta(end, start); time_old += delta; init_array(arr, array_length, i + 1); start = ktime_get(); median_new = cros_ec_sensor_ring_median_new(arr, array_length); end = ktime_get(); delta = ktime_us_delta(end, start); time_new += delta; if(median_old != median_new) return 1; } printk(KERN_ALERT "Total time of original function: %lld\n", time_old); printk(KERN_ALERT "Total time of new function: %lld\n", time_new); kfree(arr); /* return 0 on success */ return 0; } /* Result: * Total time of original function: 157561 * Total time of new function: 1480 */ .../platform/chrome/cros_ec_sensorhub_ring.c | 62 ++++++++++++++----- 1 file changed, 45 insertions(+), 17 deletions(-)