You can get a great deal of useful information from the strace output. Although it doesn't tell you what the os did with the I/O requests, it does tell you what the application is sending to the. The second lesson is that paying attention to how the application does I/O can be very important. In the c examples, i went from a number of 4,096-byte writes to much larger sized writes. In sequential streaming of I/O to the os, larger writes can improve throughput performance. This kind of input also helps the os, because it can tell the filesystem to open a file with a large number of allocated blocks, hopefully sequential, that can then be written to the underlying storage media in a streaming fashion, which is what hard.
C can switch between fread and
For 256 elements, only 1,097 bytes were written (again, much smaller than either C 4,096 or Fortran4,104). In the strace output excerpt for 500 elements, you can see that only 2,073 bytes were written.00029 seconds. Because essay the output is still below the buffer limit, only a single write was used. Finally, ill finish with the 2,000-element case (Figure 8P). Figure 8P: Strace excerpt with Python array code; 2,000 elements. This time python had to use two writes to output all the data. The first write hit the buffer limit of 4,096 bytes, leaving only 3,981 bytes for the second write. Once again, the total number of bytes written is smaller than for c or Fortran. The python pickle example wrote essay 8,077 bytes, whereas C wrote 32,000 bytes and Fortran 32,008 bytes. Summary This series of three articles on tracking I/O patterns with strace using three languages yielded a few lessons. The first is that strace can help you understand the I/O pattern of an application from the applications perspective.
Dump(my_record, f 27 ose 28 29 # end main First Ill run the pdf array code using 100 elements and gather the strace output. Because these runs produce quite a bit of output, i'm not going to show it all, but one thing I did discover is that the version of Python I'm using with CentOS.2 uses the cStringIO module to do the pickling. CStringio is a much faster way to write and read when using a c library, so it should improve the code I/O. Figure 5P: Strace excerpt with Python array code; 100 elements. One of the most remarkable things about this output is that only 471 bytes were written for 100 elements (compression perhaps?). This is much less than either C (1,600) or Fortran (1,608). Next Ill try 256 (Figure 6P) and 500 elements (Figure 7P) to see whether they also produce less output than expected. Figure 6P: Strace excerpt with Python array code; 256 elements. Figure 7P: Strace excerpt with Python array code; 500 elements.
I changed the python code in Listing 2P to use pickle instead of fwrite (Listing 3P). The defensive code around the pickle module import is a habit of mine. Additionally, i use a list of dictionaries and add them using the append method for the list class. To mirror the discussions in the previous articles for c and F90, i refer to this version of the python code as the array method. Listing 3P : Python Code e xample with o utput in l oop ( A rray) 1 #!/usr/bin/python 2 3 try: 4 import pickle; 5 except ImportError: 6 print "Cannot import pickle module - this is needed for this application. 7 print "Exiting." 8 sys. Exit 9 10 11 if _name_ main 12 13 local_dict 'x 0, 'y 0, 'z 0 value.0; 14 my_record ; # define list 15 16 counter_limit 2000; 17 18 f open n management 'r 19 for counter in range(1,counter_limit 20 local_dict'x' float(counter 21 local_dict'y' float(counter. Append(local_dict 25 # end for 26 pickle.
For completeness, i show the 2,000-iteration case in Figure. Figure 4P: Strace excerpt with Python one-by-one code; 2,000 iterations. This number of iterations used 27 write functions, with a total of 109,524 bytes of data written. Contrast this with the c code, which wrote 32,000 bytes, and Fortran 90 code, which wrote 52,124 bytes. Python has more than doubled the I/O of Fortran and trebled that. However, as with c and Fortran, you rely on the os to combine writes to increase throughput performance. Perhaps a better way to do I/O is to use an array, called a list in Python, to store the data and then do all of the I/O in a single function call. One of the better kept I/O secrets in Python is something called a pickle, which is an object serialization module. Basically, it allows you to write out objects, such as a list or a dictionary, with a single write statement.
Issue 1653416: os x print f, hello produces
The first write hits the 4,096-byte buffer limit, leaving 725 bytes for the second write. Remember that the fwrite function in Python wants the data to be written as a character string, so this will likely increase pdf the amount of data written by the application. A total of 4,821 bytes was written for only 100 iterations quite a bit more than for C (1,600) or Fortran (2,400). A quick computation of the throughput of the first write shows it to be 136.5GBps, which is in line with the c and F90 code examples london for the same algorithm. In Figure 2P, the strace output excerpt for 256 iterations, you can see four write function calls, with the first three hitting the buffer limit of 4,096 bytes.
A total of 13,089 bytes are written. Figure 2P: Strace excerpt with Python one-by-one code; 256 iterations. In the next two examples, i increase the number of iterations to 500 (Figure 3P) then 2,000 to see whether the trend of increasing buffer-limit writes continues. Figure 3P: Strace excerpt with Python one-by-one code; 500 iterations. Five hundred iterations produces seven writes, with the first six reaching the 4,096-byte buffer limit, so it appears that the buffer limit trend continues until fewer than 4,096 bytes are left to write.
Y counter 1; 29 my_record. Z counter 2; 30 my_lue (float) counter *.0; 31 fwrite( my_record, sizeof(struct rec 1, ptr_myfile 32 33 fclose(ptr_myfile 34 return 0; 35, although my python is not likely to be pythonic enough for some people, i'm just looking at the I/O portion of the. Listing 2P : Python Code, e xample with o utput in l oop ( O ne-by- o ne) 1 #!/usr/bin/python 2 3 if _name_ main 4 5 local_dict 'x 0, 'y 0, 'z 0 value.0; 6 7 counter_limit 100; 8 9 f open. Write(str(local_dict 16 # end for 17 ose 18 19 # end main I'm using the standard fwrite python function to perform the output. This function requires string data, hence the transformation of the dictionary into a string with the str function in line.
Python is an interpreted language, so gathering the strace output of a script means you have to gather the strace of the python interpreter itself. Consequently, you get a great deal of output about loading modules and getting the interpreter ready to run a script (including loading the script itself). In the strace output that follows, i have limited the lines of output shown to those that open the output file n, do the I/o, and close the file. This greatly cuts down on the amount of output in this article for the python runs. Even when using only 100 iterations (Figure 1P notice the two write calls in the strace output. Figure 1P: Strace excerpt with Python one-by-one code; 100 iterations.
Message 31195, python tracker
Python, one of metamorphosis the up and coming languages in hpc. Python, which is being used increasingly in hpc for real computations. For example, many genomic pipelines are being written in Python, as are many data analysis tools. I will begin by taking the c code in Listing 2C of the first article (reproduced as Listing 1P here) and rewrite it in Python. Initially, i just write out the data structure in the loop once it's vietnamese populated, which I refer to as one-by-one. Listing 1P: c code Example with Output in loop (One-by-One) 1 #include stdio. H 2 3 our structure 4 struct rec 5 6 int x,y, z; 7 float value; 8 ; 9 10 int main 11 12 int counter; 13 struct rec my_record; 14 int counter_limit; 15 file *ptr_myfile; 16 17 counter_limit 100; 18 19 ptr_myfilefopen. 23 return 1; 24 25 for ( counter1; counter counter_limit; counter) 26 27 my_record. X counter; 28 my_record.
With the use of a simple example in each language, ill vary the number of data type elements to get route an increasing amount of I/O. The strace output captured when the application is executed will be examined for the resulting I/O. By varying the number of elements, my goal is to see how the I/O pattern changes and perhaps better understand what is happening. In previous articles, i used strace to help understand the write I/O patterns of an application written. C and, fortran. Now, i want to do the same thing with an application written in Python. My goal is to understand what is happening in regard to the I/O and even how I might improve it by rewriting the application (tuning).
on them, returning a result to the application. Understanding the I/O pattern from an application's perspective allows you to focus on that application. You can then switch platforms or operating systems or distributions, or even tune the os with an understanding of what your application requests from the. The choice of language and compiler or interpreter have a great deal of influence on the resulting I/O pattern, which will be different when using C than when using Fortran, python, and. In a series of three articles, i use three languages that are fairly common in hpc to illustrate these differences: c, fortran 90, and Python (2.x series). I run the examples on a single 64-bit system with. CentOS.2 using the default gcc compilers, gcc and gfortran (4.4.6 and the default Python (2.6.6).
The following example shows the usage of fwrite function. H int main file *fp; moliere char str "This is m fp fopen( "file. Txt", "w" fwrite(str, 1, sizeof(str), fp fclose(fp return(0 let us compile and run the above program that will create a file file. Txt which will have following content, this is m, now let's see the content of the above file using the following program #include stdio. H int main file *fp; int c; fp fopen file. Txt r while(1) c fgetc(fp if( feof(fp) ) break ; printf c c fclose(fp return(0 let us compile and run the above program to produce the following result. This is m, previous Page, print, next Page stdio_m).
Python : 3 Steps
Advertisements, previous Page, next Page, description, the c library function size_t fwrite(const void *ptr, size_t size, size_t nmemb, file *stream) writes data from the array pointed to, by ptr to the given stream. Following is the declaration for fwrite function. Size_t fwrite(const void *ptr, size_t size, size_t nmemb, file *stream). Parameters ptr, this is the pointer to the array of elements to be written. Size, this is the size in bytes of each element to be written. Nmemb, this is the number thesis of elements, each one with a size of size bytes. Stream, this is the pointer to a file object that specifies an output stream. Return Value, this function returns the total number of elements successfully returned as a size_t object, which is an integral data type. If this number differs from the nmemb parameter, it will show an error.