timing | 易学教程

Correct way of portably timing code using C++11

阅读更多关于 Correct way of portably timing code using C++11

问题 I'm in the midst of writing some timing code for a part of a program that has a low latency requirement. Looking at whats available in the std::chrono library, I'm finding it a bit difficult to write timing code that is portable. std::chrono::high_resolution_clock std::chrono::steady_clock std::chrono::system_clock The system_clock is useless as it's not steady, the remaining two clocks are problematic. The high_resolution_clock isn't necessarily stable on all platforms. The steady_clock does

What does CPU Time for a Hadoop Job signify?

阅读更多关于 What does CPU Time for a Hadoop Job signify?

问题 I am afraid I do not understand the timing results of a Map-Reduce job. For example, a job I am running gives me the following results from the job tracker. Finished in: 1mins, 39sec CPU time spent (ms) 150,460 152,030 302,490 The entries in CPU time spent (ms) are for Map, Reduce and Total respectively. But, then how is "CPU time spent" being measured and what does it signify? Is this the total cumulative time spent in each of the mappers and reducers assigned for the job? Is it possible to

How to estimate SQL query timing?

阅读更多关于 How to estimate SQL query timing?

I'm trying to get an rough (order-of-magnitude) estimate of how long time the following query could take: mysql> EXPLAIN SELECT t1.col1, t1_col4 FROM t1 LEFT JOIN t2 ON t1.col1=t2.col1 WHERE col2=0 AND col3 IS NULL; +----+-------------+--------------------+------+---------------+------------+---------+-----------------------------+---------+--------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+--------------------+------+---------------+------------+---------+-----------------------------+---------+-------------

Microsecond accurate (or better) process timing in Linux

阅读更多关于 Microsecond accurate (or better) process timing in Linux

问题 I need a very accurate way to time parts of my program. I could use the regular high-resolution clock for this, but that will return wallclock time, which is not what I need: I needthe time spent running only my process. I distinctly remember seeing a Linux kernel patch that would allow me to time my processes to nanosecond accuracy, except I forgot to bookmark it and I forgot the name of the patch as well :(. I remember how it works though: On every context switch, it will read out the value

How to get millisecond and microsecond-resolution timestamps in Python [duplicate]

阅读更多关于 How to get millisecond and microsecond-resolution timestamps in Python [duplicate]

This question already has an answer here: High-precision clock in Python 13 answers I finally figured this out and would like to share the knowledge and save someone a bunch of time, so see my answer below. However, I still need answers for Linux, so please answer if you know, as my code in my answer is for Windows only. UPDATE: I've figured it out for Linux too, including for pre-Python 3.3 (ex: for the Raspberry Pi), and I've posted my new module/code in my answer below. My original question: How do I get millisecond and microsecond-resolution timestamps in Python? I'd also like the Arduino

Monotonic clock on OSX

阅读更多关于 Monotonic clock on OSX

CLOCK_MONOTONIC does not seem available, so clock_gettime is out. I've read in some places that mach_absolute_time() might be the right way to go, but after reading that it was a 'cpu dependent value', it instantly made me wonder if it is using rtdsc underneath. Thus, the value could drift over time even if it is monotonic. Also, issues with thread affinity could result in meaningfully different results from calling the function (making it not monotonic across all cores). Of course, that is just speculation. Does anyone know how mach_absolute_time actually works? I'm actually looking for a

pygame.time.set_timer confusion?

阅读更多关于 pygame.time.set_timer confusion?

问题 So, I have a problem, I don't fully understand the event that is needed to be given to a timer command anyway, it doesn't say anywhere online, to where I searched for hours. So I just used what most people seemed to be using 'USEREVENT + 1'. I'm not sure if it is correct, but my timer is not working. Am I using it correctly? Here is my code: nyansecond=462346 nyanint=0 spin=0 aftin=452345 def nyanmusic(nyansecond,nyanint,spin): if nyanint == 0: nyansound.play() nyanint= 1 elif nyanint == 1:

c++ Implementing Timed Callback function

阅读更多关于 c++ Implementing Timed Callback function

问题 I want to implement some system in c++ so that I can call a function and ask for another function to be called in X milliseconds. Something like this: callfunctiontimed(25, funcName); 25 being the amount of milliseconds before the function should be called. I would like to know if multithreading is required for this and then use some delay function? Other than using function pointer how would a feature like this work? 回答1: Many folks have contributed good answers here on the matter, but I

Multi-threading benchmarking issues

阅读更多关于 Multi-threading benchmarking issues

I have written a code that randomly generates two matrices from dimensions 2x2 up to 50x50. I am then recording the time it takes for each matrix multiplication from dimensions 2 up to 50. I record this time 100 times to get a good average for each case 2 -50. The program first starts off by multiplying the matrices sequentially and records the average execution time in a csv file. It then moves on to parallel matrix multiplication using pthreads and records the average execution times in a separate csv file. My issue is that the average execution time for the sequential multiplication is a

What happens when QueryPerformanceCounter is called?

阅读更多关于 What happens when QueryPerformanceCounter is called?

问题 I'm looking into the exact implications of using QueryPerformanceCounter in our system and am trying to understand it's impact on the application. I can see from running it on my 4-core single cpu machine that it takes around 230ns to run. When I run it on a 24-core 4 cpu xeon it takes around 1.4ms to run. More interestingly on my machine when running it in multiple threads they don't impact each other. But on the multi-cpu machine the threads cause some sort of interaction that causes them