profiling

问题 What tools are available to view the output of the built-in JVM profiler? For example, I'm starting my JVM with: -agentlib:hprof=cpu=times,thread=y,cutoff=0,format=a,file=someFile.hprof.txt This generates output in the hprof ("JAVA PROFILE 1.0.1") format. I have had success in the past using HPjmeter to view these output files in a reasonable way. However, for whatever reason the files that are generated using the current version of the Sun JVM fail to load in the current version of HPjmeter:

问题 I want to create a decorator that profiles a method and logs the result. How can this be done? 回答1: The decorator would look something like: import time import logging def profile(func): def wrap(*args, **kwargs): started_at = time.time() result = func(*args, **kwargs) logging.info(time.time() - started_at) return result return wrap @profile def foo(): pass Anyway, if you want to do some serious profiling I would suggest you use the profile or cProfile packages. 回答2: If you want proper

问题 According to perf tutorials, perf stat is supposed to report cache misses using hardware counters. However, on my system (up-to-date Arch Linux), it doesn't: [joel@panda goog]$ perf stat ./hash Performance counter stats for './hash': 869.447863 task-clock # 0.997 CPUs utilized 92 context-switches # 0.106 K/sec 4 cpu-migrations # 0.005 K/sec 1,041 page-faults # 0.001 M/sec 2,628,646,296 cycles # 3.023 GHz 819,269,992 stalled-cycles-frontend # 31.17% frontend cycles idle 132,355,435 stalled

问题 I am trying to optimize a c++ program's performance and reduce its run time. However, I am having trouble figuring out where is the bottleneck. time command shows that the program itself takes about 5 minutes to run, and about the 5 minutes, user cpu time takes 4.5 minutes. CPU profiler (both gcc profiler and google perftool) shows that the function calls only take 60 seconds in total in CPU time. I also tried to use the profiler to sample real time instead of cpu time, and it gives me

问题 I am trying to optimize a c++ program's performance and reduce its run time. However, I am having trouble figuring out where is the bottleneck. time command shows that the program itself takes about 5 minutes to run, and about the 5 minutes, user cpu time takes 4.5 minutes. CPU profiler (both gcc profiler and google perftool) shows that the function calls only take 60 seconds in total in CPU time. I also tried to use the profiler to sample real time instead of cpu time, and it gives me

问题 First, a bit of a background. There are many various comparisons of distributed version control systems (DVCS) which compare size of repository, or benchmark speed of operations. I haven't found any that would benchmark network performance of various DVCS, and various protocols used... beside measuring speed of operations (commands) involving network like 'clone', 'pull'/'fetch' or 'push'. I'd like to know then how would you make such comparison; how to measure network performance of an

问题 What is the correct option for measuring bandwidth using nvprof --metrics from the command line? I am using flop_dp_efficiency to get the percentage of peak FLOPS, but there seems to be many options for bandwidth measurement in the manual that I don't really understand what I am measuring. e.g. dram_read, dram_write, gld_read, gld_write all look the same to me. Also, should I report bandwdith as a sum of read+write throughput by assuming both happen simultaneously ? Edit: Based on the

问题 I am using a SQLite database and would like to speed up my queries, perhaps with indexes or by restructuring them altogether. Is there a tool to profile queries, that might help me decide where things are slowing down? I know I could just enter queries into a tool like SQLite Administrator to time them, but I'm looking for something a bit more systematic than that -- perhaps something that sits in the background and looks at all the queries that I enter over a period, giving a breakdown of

问题 I have a dataframe of the following form (for example) shopper_num,is_martian,number_of_items,count_pineapples,birth_country,tranpsortation_method 1,FALSE,0,0,MX, 2,FALSE,1,0,MX, 3,FALSE,0,0,MX, 4,FALSE,22,0,MX, 5,FALSE,0,0,MX, 6,FALSE,0,0,MX, 7,FALSE,5,0,MX, 8,FALSE,0,0,MX, 9,FALSE,4,0,MX, 10,FALSE,2,0,MX, 11,FALSE,0,0,MX, 12,FALSE,13,0,MX, 13,FALSE,0,0,CA, 14,FALSE,0,0,US, How can I use Pandas to calculate summary statistics of each column (column data types are variable, some columns have

问题 I want to know how to profile my code. I have gone through the docs, but as there were no examples given I could not get anything from it. I have a large code and it is taking so much time, hence I want to profile and increase its speed. I havent written my code in method, there are few in between but not completely. I don't have any main in my code. I want to know how to use profiling. I'm looking for some example or sample code of about how to profile. I tried psyco, i.e just addded two