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• What's a good algorithm for searching arrays N and M, in order to find elements in N that also exist

  - by GenTiradentes

  I have two arrays, N and M. they are both arbitrarily sized, though N is usually smaller than M. I want to find out what elements in N also exist in M, in the fastest way possible. To give you an example of one possible instance of the program, N is an array 12 units in size, and M is an array 1,000 units in size. I want to find which elements in N also exist in M. (There may not be any matches.) The more parallel the solution, the better. I used to use a hash map for this, but it's not quite as efficient as I'd like it to be. Typing this out, I just thought of running a binary search of M on sizeof(N) independent threads. (Using CUDA) I'll see how this works, though other suggestions are welcome.

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• Physical Cores vs Virtual Cores in Parallelism

  - by Code Curiosity

  When it comes to virtualization, I have been deliberating on the relationship between the physical cores and the virtual cores, especially in how it effects applications employing parallelism. For example, in a VM scenario, if there are less physical cores than there are virtual cores, if that's possible, what's the effect or limits placed on the application's parallel processing? I'm asking, because in my environment, it's not disclosed as to what the physical architecture is. Is there still much advantage to parallelizing if the application lives on a dual core VM hosted on a single core physical machine?

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• Updating files with a Perforce trigger before submit [migrated]

  - by phantom-99w

  I understand that this question has, in essence, already been asked, but that question did not have an unequivocal answer, so please bear with me. Background: In my company, we use Perforce submission numbers as part of our versioning. Regardless of whether this is a correct method or not, that is how things are. Currently, many developers do separate submissions for code and documentation: first the code and then the documentation to update the client-facing docs with what the new version numbers should be. I would like to streamline this process. My thoughts are as follows: create a Perforce trigger (which runs on the server side) which scans the submitted documentation files (such as .txt) for a unique term (such as #####PERFORCE##CHANGELIST##NUMBER###ROFL###LOL###WHATEVER#####) and then replaces it with the value of what the change list would be when submitted. I already know how to determine this value. What I cannot figure out, is how or where to update the files. I have already determined that using the change-content trigger (whether possible or not), which "fire[s] after changelist creation and file transfer, but prior to committing the submit to the database", is the way to go. At this point the files need to exist somewhere on the server. How do I determine the (temporary?) location of these files from within, say, a Python script so that I can update or sed to replace the placeholder value with the intended value? The online documentation for Perforce which I have found so far have not been very explicit on whether this is possible or how the mechanics of a submission at this stage would work.

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• What's the safest way to kick off a root-level process via cgi on an Apache server?

  - by MartyMacGyver

  The problem: I have a script that runs periodically via a cron job as root, but I want to give people a way to kick it off asynchronously too, via a webpage. (The script will be written to ensure it doesn't run overlapping instances or such.) I don't need the users to log in or have an account, they simply click a button and if the script is ready to be run it'll run. The users may select arguments for the script (heavily filtered as inputs) but for simplicity we'll say they just have the button to choose to press. As a simple test, I've created a Python script in cgi-bin. chown-ing it to root:root and then applying "chmod ug+" to it didn't have the desired results: it still thinks it has the effective group of the web server account... from what I can tell this isn't allowed. I read that wrapping it with a compiled cgi program would do the job, so I created a C wrapper that calls my script (its permissions restored to normal) and gave the executable the root permissions and setuid bit. That worked... the script ran as if root ran it. My main question is, is this normal (the need for the binary wrapper to get the job done) and is this the secure way to do this? It's not world-facing but still, I'd like to learn best practices. More broadly, I often wonder why a compiled binary is more "trusted" than a script in practice? I'd think you'd trust a file that was human-readable over a cryptic binaryy. If an attacker can edit a file then you're already in trouble, more so if it's one you can't easily examine. In short, I'd expect it to be the other way 'round on that basis. Your thoughts?

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• Activate thread synchronically

  - by mayap

  Hi All, I'm using .Net 4.0 parallel library. The tasks I execute, ask to run some other task, sometimes synchronically and somethimes asynchronically, dependending on some conditions which are not known in advanced. For async call, i simply create new tasks and that's it. I don't know how to handly sync call: how to run it from the same thread, maybe that sync tasks will also ask to execute sync tasks recursively. all this issue is pretty new to me. thanks in advance.

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• Which scripting language to use to asynchronously ssh into equipment, run several commands, parse the output, and save to a file on my computer?

  - by Fujin

  There are several points I'd like to stress in my question. I'd like to login by asynchronously ssh'ing into our infrastructure equipment. Meaning, I do not want to connect to only one device, do all the tasks I need, disconnect, then connect to the next device. I want to connect to several devices at once in order to make the process as fast as possible. By equipment I mean 'infrastructure equipment' and not servers. I say this because I will not have the luxury of saving files to the device then transferring them to myself with scp or another method. The output of the scripts that are run will have to be saved directly to my computer. The output of the commands that are run will need to be cleaned up and parsed. Also I want the outputs of each device to be combined into one nice and neat file, not a separate file for each device. This will all be done from a linux box, using ssh, into devices that all use linux'ish proprietary OSes. My guess is the answer to my question will either be a Bash, Perl, or Python script but I figured it wouldn't hurt to ask and to hear the reasons why one way is better than another. Thanks everyone. EXTRA CREDIT: With you answer, include links to resources that will help create the script I described in the language that you suggested.

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• Building an interleaved buffer for pyopengl and numpy

  - by Nick Sonneveld

  I'm trying to batch up a bunch of vertices and texture coords in an interleaved array before sending it to pyOpengl's glInterleavedArrays/glDrawArrays. The only problem is that I'm unable to find a suitably fast enough way to append data into a numpy array. Is there a better way to do this? I would have thought it would be quicker to preallocate the array and then fill it with data but instead, generating a python list and converting it to a numpy array is "faster". Although 15ms for 4096 quads seems slow. I have included some example code and their timings. #!/usr/bin/python import timeit import numpy import ctypes import random USE_RANDOM=True USE_STATIC_BUFFER=True STATIC_BUFFER = numpy.empty(4096*20, dtype=numpy.float32) def render(i): # pretend these are different each time if USE_RANDOM: tex_left, tex_right, tex_top, tex_bottom = random.random(), random.random(), random.random(), random.random() left, right, top, bottom = random.random(), random.random(), random.random(), random.random() else: tex_left, tex_right, tex_top, tex_bottom = 0.0, 1.0, 1.0, 0.0 left, right, top, bottom = -1.0, 1.0, 1.0, -1.0 ibuffer = ( tex_left, tex_bottom, left, bottom, 0.0, # Lower left corner tex_right, tex_bottom, right, bottom, 0.0, # Lower right corner tex_right, tex_top, right, top, 0.0, # Upper right corner tex_left, tex_top, left, top, 0.0, # upper left ) return ibuffer # create python list.. convert to numpy array at end def create_array_1(): ibuffer = [] for x in xrange(4096): data = render(x) ibuffer += data ibuffer = numpy.array(ibuffer, dtype=numpy.float32) return ibuffer # numpy.array, placing individually by index def create_array_2(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) for v in data: ibuffer[index] = v index += 1 return ibuffer # using slicing def create_array_3(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) ibuffer[index:index+20] = data index += 20 return ibuffer # using numpy.concat on a list of ibuffers def create_array_4(): ibuffer_concat = [] for x in xrange(4096): data = render(x) # converting makes a diff! data = numpy.array(data, dtype=numpy.float32) ibuffer_concat.append(data) return numpy.concatenate(ibuffer_concat) # using numpy array.put def create_array_5(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) ibuffer.put( xrange(index, index+20), data) index += 20 return ibuffer # using ctype array CTYPES_ARRAY = ctypes.c_float*(4096*20) def create_array_6(): ibuffer = [] for x in xrange(4096): data = render(x) ibuffer += data ibuffer = CTYPES_ARRAY(*ibuffer) return ibuffer def equals(a, b): for i,v in enumerate(a): if b[i] != v: return False return True if __name__ == "__main__": number = 100 # if random, don't try and compare arrays if not USE_RANDOM and not USE_STATIC_BUFFER: a = create_array_1() assert equals( a, create_array_2() ) assert equals( a, create_array_3() ) assert equals( a, create_array_4() ) assert equals( a, create_array_5() ) assert equals( a, create_array_6() ) t = timeit.Timer( "testing2.create_array_1()", "import testing2" ) print 'from list:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_2()", "import testing2" ) print 'array: indexed:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_3()", "import testing2" ) print 'array: slicing:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_4()", "import testing2" ) print 'array: concat:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_5()", "import testing2" ) print 'array: put:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_6()", "import testing2" ) print 'ctypes float array:', t.timeit(number)/number*1000.0, 'ms' Timings using random numbers: $ python testing2.py from list: 15.0486779213 ms array: indexed: 24.8184704781 ms array: slicing: 50.2214789391 ms array: concat: 44.1691994667 ms array: put: 73.5879898071 ms ctypes float array: 20.6674289703 ms edit note: changed code to produce random numbers for each render to reduce object reuse and to simulate different vertices each time. edit note2: added static buffer and force all numpy.empty() to use dtype=float32 note 1/Apr/2010: still no progress and I don't really feel that any of the answers have solved the problem yet.

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• Psychology researcher wants to learn new language

  - by user273347

  I'm currently considering R, matlab, or python, but I'm open to other options. Could you help me pick the best language for my needs? Here are the criteria I have in mind (not in order): Simple to learn. I don't really have a lot of free time, so I'm looking for something that isn't extremely complicated and/or difficult to pick up. I know some C, FWIW. Good for statistics/psychometrics. I do a ton of statistics and psychometrics analysis. A lot of it is basic stuff that I can do with SPSS, but I'd like to play around with the more advanced stuff too (bootstrapping, genetic programming, data mining, neural nets, modeling, etc). I'm looking for a language/environment that can help me run my simpler analyses faster and give me more options than a canned stat package like SPSS. If it can even make tables for me, then it'll be perfect. I also do a fair bit of experimental psychology. I use a canned experiment "programming" software (SuperLab) to make most of my experiments, but I want to be able to program executable programs that I can run on any computer and that can compile the data from the experiments in a spreadsheet. I know python has psychopy and pyepl and matlab has psychtoolbox, but I don't know which one is best. If R had something like this, I'd probably be sold on R already. I'm looking for something regularly used in academe and industry. Everybody else here (including myself, so far) uses canned stat and experiment programming software. One of the reasons I'm trying to learn a programming language is so that I can keep up when I move to another lab. Looking forward to your comments and suggestions. Thank you all for your kind and informative replies. I appreciate it. It's still a tough choice because of so many strong arguments for each language. Python - Thinking about it, I've forgotten so much about C already (I don't even remember what to do with an array) that it might be better for me to start from scratch with a simple program that does what it's supposed to do. It looks like it can do most of the things I'll need it to do, though not as cleanly as R and MATLAB. R - I'm really liking what I'm reading about R. The packages are perfect for my statistical work now. Given the purpose of R, I don't think it's suited to building psychological experiments though. To clarify, what I mean is making a program that presents visual and auditory stimuli to my specifications (hundreds of them in a preset and/or randomized sequence) and records the response data gathered from participants. MATLAB - It's awesome that cognitive and neuro folk are recommending MATLAB, because I'm preparing for the big leap from social and personality psychology to cognitive neuro. The problem is the Uni where I work doesn't have MATLAB licenses (and 3750 GBP for a compiler license is not an option for me haha). Octave looks like a good alternative. PsychToolbox is compatible with Octave, thankfully. SQL - Thanks for the tip. I'll explore that option, too. Python will be the least backbreaking and most useful in the short term. R is well suited to my current work. MATLAB is well suited to my prospective work. It's a tough call, but I think I am now equipped to make a more well-informed decision about where to go next. Thanks again!

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• numpy calling sse2 via ctypes

  - by Daniel

  Hello, In brief, I am trying to call into a shared library from python, more specifically, from numpy. The shared library is implemented in C using sse2 instructions. Enabling optimisation, i.e. building the library with -O2 or –O1, I am facing strange segfaults when calling into the shared library via ctypes. Disabling optimisation (-O0), everything works out as expected, as is the case when linking the library to a c-program directly (optimised or not). Attached you find a snipped which exhibits the delineated behaviour on my system. With optimisation enabled, gdb reports a segfault in __builtin_ia32_loadupd (__P) at emmintrin.h:113. The value of __P is reported as optimised out. test.c: #include <emmintrin.h> #include <complex.h> void test(const int m, const double* x, double complex* y) { int i; __m128d _f, _x, _b; double complex f __attribute__( (aligned(16)) ); double complex b __attribute__( (aligned(16)) ); __m128d* _p; b = 1; _b = _mm_loadu_pd( (double *) &b ); _p = (__m128d*) y; for(i=0; i<m; ++i) { f = cexp(-I*x[i]); _f = _mm_loadu_pd( (double *) &f ); _x = _mm_loadu_pd( (double *) &x[i] ); _f = _mm_shuffle_pd(_f, _f, 1); *_p = _mm_add_pd(*_p, _f); *_p = _mm_add_pd(*_p, _x); *_p = _mm_mul_pd(*_p,_b); _p++; } return; } Compiler flags: gcc -o libtest.so -shared -std=c99 -msse2 -fPIC -O2 -g -lm test.c test.py: import numpy as np import os def zerovec_aligned(nr, dtype=np.float64, boundary=16): '''Create an aligned array of zeros. ''' size = nr * np.dtype(dtype).itemsize tmp = np.zeros(size + boundary, dtype=np.uint8) address = tmp.__array_interface__['data'][0] offset = boundary - address % boundary return tmp[offset:offset + size].view(dtype=dtype) lib = np.ctypeslib.load_library('libtest', '.' ) lib.test.restype = None lib.test.argtypes = [np.ctypeslib.ctypes.c_int, np.ctypeslib.ndpointer(np.float64, flags=('C', 'A') ), np.ctypeslib.ndpointer(np.complex128, flags=('C', 'A', 'W') )] n = 13 y = zerovec_aligned(n, dtype=np.complex128) x = np.ones(n, dtype=np.float64) # x = zerovec_aligned(n, dtype=np.float64) # x[:] = 1. lib.test(n,x,y) My system: Ubuntu Linux i686 2.6.31-22-generic Compiler: gcc (Ubuntu 4.4.1-4ubuntu9) Python: Python 2.6.4 (r264:75706, Dec 7 2009, 18:45:15) [GCC 4.4.1] Numpy: 1.4.0 I have taken provisions (cf. python code) that y is aligned and the alignment of x should not matter (I think; explicitly aligning x does not solve the problem though). Note also that i use _mm_loadu_pd instead of _mm_load_pd when loading b and f. For the C-only version _mm_load_pd works (as expected). However, when calling the function via ctypes using _mm_load_pd always segfaults (independent of optimisation). I have tried several days to sort out this issue without success ... and I am on the verge beating my monitor to death. Any input welcome. Daniel

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• 500 internal server error on certain page after a few hours

  - by Brian Leach

  I am getting a 500 Internal Server Error on a certain page of my site after a few hours of being up. I restart uWSGI instance with uwsgi --ini /home/metheuser/webapps/ers_portal/ers_portal_uwsgi.ini and it works again for a few hours. The rest of the site seems to be working. When I navigate to my_table, I am directed to the login page. But, I get the 500 error on my table page on login. I followed the instructions here to set up my nginx and uwsgi configs. That is, I have ers_portal_nginx.conf located i my app folder that is symlinked to /etc/nginx/conf.d/. I start my uWSGI "instance" (not sure what exactly to call it) in a Screen instance as mentioned above, with the .ini file located in my app folder My ers_portal_nginx.conf: server { listen 80; server_name www.mydomain.com; location / { try_files $uri @app; } location @app { include uwsgi_params; uwsgi_pass unix:/home/metheuser/webapps/ers_portal/run_web_uwsgi.sock; } } My ers_portal_uwsgi.ini: [uwsgi] #user info uid = metheuser gid = ers_group #application's base folder base = /home/metheuser/webapps/ers_portal #python module to import app = run_web module = %(app) home = %(base)/ers_portal_venv pythonpath = %(base) #socket file's location socket = /home/metheuser/webapps/ers_portal/%n.sock #permissions for the socket file chmod-socket = 666 #uwsgi varible only, does not relate to your flask application callable = app #location of log files logto = /home/metheuser/webapps/ers_portal/logs/%n.log Relevant parts of my views.py data_modification_time = None data = None def reload_data(): global data_modification_time, data, sites, column_names filename = '/home/metheuser/webapps/ers_portal/app/static/' + ec.dd_filename mtime = os.stat(filename).st_mtime if data_modification_time != mtime: data_modification_time = mtime with open(filename) as f: data = pickle.load(f) return data @a bunch of authentication stuff... @app.route('/') @app.route('/index') def index(): return render_template("index.html", title = 'Main',) @app.route('/login', methods = ['GET', 'POST']) def login(): login stuff... @app.route('/my_table') @login_required def my_table(): print 'trying to access data table...' data = reload_data() return render_template("my_table.html", title = "Rundata Viewer", sts = sites, cn = column_names, data = data) # dictionary of data I installed nginx via yum as described here (yesterday) I am using uWSGI installed in my venv via pip I am on CentOS 6 My uwsgi log shows: Wed Jun 11 17:20:01 2014 - uwsgi_response_writev_headers_and_body_do(): Broken pipe [core/writer.c line 287] during GET /whm-server-status (127.0.0.1) IOError: write error [pid: 9586|app: 0|req: 135/135] 127.0.0.1 () {24 vars in 292 bytes} [Wed Jun 11 17:20:01 2014] GET /whm-server-status => generated 0 bytes in 3 msecs (HTTP/1.0 404) 2 headers in 0 bytes (0 switches on core 0) When its working, the print statement in the views "my_table" route prints into the log file. But not once it stops working. Any ideas?

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• Error installing scipy on Mountain Lion with Xcode 4.5.1

  - by Xster

  Environment: Mountain Lion 10.8.2, Xcode 4.5.1 command line tools, Python 2.7.3, virtualenv 1.8.2 and numpy 1.6.2 When installing scipy with pip install -e "git+https://github.com/scipy/scipy#egg=scipy-dev" on a fresh virtualenv. llvm-gcc: scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:51:23: error: immintrin.h: No such file or directory In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vceilf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:53: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vfloorf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:54: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: ‘_MM_FROUND_TRUNC’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: (Each undeclared identifier is reported only once /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: for each function it appears in.) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vnintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: ‘_MM_FROUND_NINT’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: incompatible types in return In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:51:23: error: immintrin.h: No such file or directory In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vceilf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:53: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vfloorf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:54: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: ‘_MM_FROUND_TRUNC’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: (Each undeclared identifier is reported only once /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: for each function it appears in.) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vnintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: ‘_MM_FROUND_NINT’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: incompatible types in return error: Command "/usr/bin/llvm-gcc -fno-strict-aliasing -Os -w -pipe -march=core2 -msse4 -fwrapv -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -Iscipy/sparse/linalg/eigen/arpack/ARPACK/SRC -I/Users/xiao/.virtualenv/lib/python2.7/site-packages/numpy/core/include -c scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c -o build/temp.macosx-10.4-x86_64-2.7/scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.o" failed with exit status 1 Is it supposed to be looking for headers from my system frameworks? Is the development version of scipy no longer good for the latest version of Mountain Lion/Xcode?

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• Django + gunicorn + virtualenv + Supervisord issue

  - by Florian Le Goff

  Dear all, I have a strange issue with my virtualenv + gunicorn setup, only when gunicorn is launched via supervisord. I do realize that it may very well be an issue with my supervisord and I would appreciate any feedback on a better place to ask for help... In a nutshell : when I run gunicorn from my user shell, inside my virtualenv, everything is working flawlessly. I'm able to access all the views of my Django project. When gunicorn is launched by supervisord at the system startup, everything is OK. But, if I have to kill the gunicorn_django processes, or if I perform a supervisord restart, once that gunicorn_django has relaunched, every request is answered with a weird Traceback : (...) File "/home/hc/prod/venv/lib/python2.6/site-packages/Django-1.2.5-py2.6.egg/django/db/__init__.py", line 77, in connection = connections[DEFAULT_DB_ALIAS] File "/home/hc/prod/venv/lib/python2.6/site-packages/Django-1.2.5-py2.6.egg/django/db/utils.py", line 92, in __getitem__ backend = load_backend(db['ENGINE']) File "/home/hc/prod/venv/lib/python2.6/site-packages/Django-1.2.5-py2.6.egg/django/db/utils.py", line 50, in load_backend raise ImproperlyConfigured(error_msg) TemplateSyntaxError: Caught ImproperlyConfigured while rendering: 'django.db.backends.postgresql_psycopg2' isn't an available database backend. Try using django.db.backends.XXX, where XXX is one of: 'dummy', 'mysql', 'oracle', 'postgresql', 'postgresql_psycopg2', 'sqlite3' Error was: cannot import name utils Full stack available here : http://pastebin.com/BJ5tNQ2N I'm running... Ubuntu/maverick (up-to-date) Python = 2.6.6 virtualenv = 1.5.1 gunicorn = 0.12.0 Django = 1.2.5 psycopg2 = '2.4-beta2 (dt dec pq3 ext)' gunicorn configuration : backlog = 2048 bind = "127.0.0.1:8000" pidfile = "/tmp/gunicorn-hc.pid" daemon = True debug = True workers = 3 logfile = "/home/hc/prod/log/gunicorn.log" loglevel = "info" supervisord configuration : [program:gunicorn] directory=/home/hc/prod/hc command=/home/hc/prod/venv/bin/gunicorn_django -c /home/hc/prod/hc/gunicorn.conf.py user=hc umask=022 autostart=True autorestart=True redirect_stderr=True Any advice ? I've been stuck on this one for quite a while. It seems like some weird memory limit, as I'm not enforcing anything special : $ ulimit -a core file size (blocks, -c) 0 data seg size (kbytes, -d) unlimited scheduling priority (-e) 20 file size (blocks, -f) unlimited pending signals (-i) 16382 max locked memory (kbytes, -l) 64 max memory size (kbytes, -m) unlimited open files (-n) 1024 pipe size (512 bytes, -p) 8 POSIX message queues (bytes, -q) 819200 real-time priority (-r) 0 stack size (kbytes, -s) 8192 cpu time (seconds, -t) unlimited max user processes (-u) unlimited virtual memory (kbytes, -v) unlimited file locks (-x) unlimited Thank you.

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• Slow Memcached: Average 10ms memcached `get`

  - by Chris W.

  We're using Newrelic to measure our Python/Django application performance. Newrelic is reporting that across our system "Memcached" is taking an average of 12ms to respond to commands. Drilling down into the top dozen or so web views (by # of requests) I can see that some Memcache get take up to 30ms; I can't find a single use of Memcache get that returns in less than 10ms. More details on the system architecture: Currently we have four application servers each of which has a memcached member. All four memcached members participate in a memcache cluster. We're running on a cloud hosting provider and all traffic is running across the "internal" network (via "internal" IPs) When I ping from one application server to another the responses are in ~0.5ms Isn't 10ms a slow response time for Memcached? As far as I understand if you think "Memcache is too slow" then "you're doing it wrong". So am I doing it wrong? Here's the output of the memcache-top command: memcache-top v0.7 (default port: 11211, color: on, refresh: 3 seconds) INSTANCE USAGE HIT % CONN TIME EVICT/s GETS/s SETS/s READ/s WRITE/s cache1:11211 37.1% 62.7% 10 5.3ms 0.0 73 9 3958 84.6K cache2:11211 42.4% 60.8% 11 4.4ms 0.0 46 12 3848 62.2K cache3:11211 37.5% 66.5% 12 4.2ms 0.0 75 17 6056 170.4K AVERAGE: 39.0% 63.3% 11 4.6ms 0.0 64 13 4620 105.7K TOTAL: 0.1GB/ 0.4GB 33 13.9ms 0.0 193 38 13.5K 317.2K (ctrl-c to quit.) ** Here is the output of the top command on one machine: ** (Roughly the same on all cluster machines. As you can see there is very low CPU utilization, because these machines only run memcache.) top - 21:48:56 up 1 day, 4:56, 1 user, load average: 0.01, 0.06, 0.05 Tasks: 70 total, 1 running, 69 sleeping, 0 stopped, 0 zombie Cpu(s): 0.0%us, 0.0%sy, 0.0%ni, 99.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.3%st Mem: 501392k total, 424940k used, 76452k free, 66416k buffers Swap: 499996k total, 13064k used, 486932k free, 181168k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 6519 nobody 20 0 384m 74m 880 S 1.0 15.3 18:22.97 memcached 3 root 20 0 0 0 0 S 0.3 0.0 0:38.03 ksoftirqd/0 1 root 20 0 24332 1552 776 S 0.0 0.3 0:00.56 init 2 root 20 0 0 0 0 S 0.0 0.0 0:00.00 kthreadd 4 root 20 0 0 0 0 S 0.0 0.0 0:00.00 kworker/0:0 5 root 20 0 0 0 0 S 0.0 0.0 0:00.02 kworker/u:0 6 root RT 0 0 0 0 S 0.0 0.0 0:00.00 migration/0 7 root RT 0 0 0 0 S 0.0 0.0 0:00.62 watchdog/0 8 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 cpuset 9 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 khelper ...output truncated...

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• 10.6.4 Apple Wiki: New just created users can do nothing?

  - by beefon

  Hello, After update to 10.6.4 there's an issue: any new users that I create in Server Prefs/WGM can't post to their blogs, comment, create wiki pages... They can't do anything! There's log from Wiki errors (when user DURAK tries to create new blog entry): [HTTPChannel,5,127.0.0.1] Traceback (most recent call last): [HTTPChannel,5,127.0.0.1] File "/usr/share/caldavd/lib/python/twisted/web/server.py", line 126, in process self.render(resrc) [HTTPChannel,5,127.0.0.1] File "/usr/share/caldavd/lib/python/twisted/web/server.py", line 133, in render body = resrc.render(self) [HTTPChannel,5,127.0.0.1] File "/usr/share/wikid/lib/python/apple_xmlrpc_server/WebAppServer.py", line 90, in render d = defer.maybeDeferred(function, *args) [HTTPChannel,5,127.0.0.1] File "/usr/share/caldavd/lib/python/twisted/internet/defer.py", line 104, in maybeDeferred result = f(*args, **kw) [HTTPChannel,5,127.0.0.1] --- <exception caught here> --- [HTTPChannel,5,127.0.0.1] File "/usr/share/wikid/lib/python/apple_xmlrpc_server/ContentServiceBase.py", line 121, in xmlrpc_addEntry aPage = ContentEntry.newBundleBasedContentEntry (path = path, content = content, author = author, title = title, uid = uid, type = kind, versioned = self.versioned, templateName = template) [HTTPChannel,5,127.0.0.1] File "/usr/share/wikid/lib/python/apple_wlt/ContentEntry.py", line 794, in newBundleBasedContentEntry aPage.save('First created', 'created') [HTTPChannel,5,127.0.0.1] File "/usr/share/wikid/lib/python/apple_wlt/ContentEntry.py", line 445, in save revisions.addRevision(self.serializeEntry(revisionAttributes), inComment = comment, inAuthor = updateAuthor, inChangeType = editType) [HTTPChannel,5,127.0.0.1] File "/usr/share/wikid/lib/python/apple_utilities/sqlitersion.py", line 36, in _func result = f(self, *args, **kwargs) [HTTPChannel,5,127.0.0.1] File "/usr/share/wikid/lib/python/apple_utilities/sqlitersion.py", line 49, in addRevision contentPlistStr = plistlib.writePlistToString(inContentDict).decode("utf-8") [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 110, in writePlistToString [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 94, in writePlist [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 251, in writeValue [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 280, in writeDict [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 238, in writeValue [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 171, in simpleElement [HTTPChannel,5,127.0.0.1] File "/S-m/Lib-ry/Fr-ks/Python.fr-k/Ver-s/2.6/lib/pyth-2.6/plistlib.py", line 221, in _escapeAndEncode [HTTPChannel,5,127.0.0.1] exceptions.UnicodeDecodeError: 'ascii' codec can't decode byte 0xd0 in position 0: ordinal not in range(128) [HTTPChannel,5,127.0.0.1] 'Unparseable html in page, removing whatever was already written.' [HTTPChannel,5,127.0.0.1] Removing /Library/Collaboration/Users/durak/weblog/27133.page Any "old" user CAN create, modify, comment, etc. What can you recommend to fix this issue? Hope for your help...

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• Nginx reverse proxy with separate aliases

  - by gabeDel

  Interesting question I have this python code: import sys, bottle, gevent from bottle import * from gevent import * from gevent.wsgi import WSGIServer @route("/") def index(): yield "/" application=bottle.default_app() WSGIServer(('', port), application, spawn=None).serve_forever() that runs standalone with nignx infront of it as a reverse proxy. Now each of these pieces of code run separately but I run multiple of these per domain per project(directory) but the code thinks for some reason that it is top level and its not so when you go to mydomain.com/something it works but if you go to mydomain.com/something/ you will get an error. No I have tested and figured out that nginx is stripping the "something" from the request/query so that when you go to mydomain.com/something/ the code thinks you are going to mydomain.com// how do I get nginx to stop removing this information? Nginx site code: upstream mydomain { server 127.0.0.1:10100 max_fails=5 fail_timeout=10s; } upstream subdirectory { server 127.0.0.1:10199 max_fails=5 fail_timeout=10s; } server { listen 80; server_name mydomain.com; access_log /var/log/nginx/access.log; location /sub { proxy_pass http://subdirectory/; proxy_redirect off; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_max_temp_file_size 0; client_max_body_size 10m; client_body_buffer_size 128k; proxy_connect_timeout 90; proxy_send_timeout 90; proxy_read_timeout 90; proxy_buffer_size 4k; proxy_buffers 4 32k; proxy_busy_buffers_size 64k; proxy_temp_file_write_size 64k; } location /subdir { proxy_pass http://subdirectory/; proxy_redirect off; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_max_temp_file_size 0; client_max_body_size 10m; client_body_buffer_size 128k; proxy_connect_timeout 90; proxy_send_timeout 90; proxy_read_timeout 90; proxy_buffer_size 4k; proxy_buffers 4 32k; proxy_busy_buffers_size 64k; proxy_temp_file_write_size 64k; } }

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• How can I build pyv8 from source on FreeBSD against the v8 port?

  - by Utkonos

  I am unable to build pyv8 from source on FreeBSD. I have installed the /usr/ports/lang/v8 port, and I'm running into the following error. It seems that pyv8 wants to build v8 itself even though v8 is already built and installed. How can I point pyv8 to the already installed location of v8? # python setup.py build Found Google v8 base on V8_HOME , update it to the latest SVN trunk at running build ==================== INFO: Installing or updating GYP... -------------------- INFO: Check out GYP from SVN ... DEBUG: make dependencies ERROR: Check out GYP from SVN failed: code=2 DEBUG: "Makefile", line 43: Missing dependency operator "Makefile", line 45: Need an operator "Makefile", line 46: Need an operator "Makefile", line 48: Need an operator "Makefile", line 50: Need an operator "Makefile", line 52: Need an operator "Makefile", line 54: Missing dependency operator "Makefile", line 56: Need an operator "Makefile", line 58: Missing dependency operator "Makefile", line 60: Need an operator "Makefile", line 62: Missing dependency operator "Makefile", line 64: Need an operator "Makefile", line 66: Missing dependency operator "Makefile", line 68: Need an operator "Makefile", line 70: Missing dependency operator "Makefile", line 72: Need an operator "Makefile", line 73: Missing dependency operator "Makefile", line 75: Need an operator "Makefile", line 77: Missing dependency operator "Makefile", line 79: Need an operator "Makefile", line 81: Missing dependency operator "Makefile", line 83: Need an operator "Makefile", line 85: Missing dependency operator "Makefile", line 87: Need an operator "Makefile", line 89: Need an operator "Makefile", line 91: Missing dependency operator "Makefile", line 93: Need an operator "Makefile", line 95: Need an operator "Makefile", line 97: Need an operator "Makefile", line 99: Missing dependency operator "Makefile", line 101: Need an operator "Makefile", line 103: Missing dependency operator "Makefile", line 105: Need an operator "Makefile", line 107: Missing dependency operator "Makefile", line 109: Need an operator "Makefile", line 111: Missing dependency operator "Makefile", line 113: Need an operator "Makefile", line 115: Missing dependency operator "Makefile", line 117: Need an operator Error expanding embedded variable. ==================== INFO: Patching the GYP scripts INFO: patch the Google v8 build/standalone.gypi file to enable RTTI and C++ Exceptions ==================== INFO: building Google v8 with GYP for x64 platform with release mode -------------------- INFO: build v8 from SVN ... DEBUG: make verifyheap=off component=shared_library visibility=on gdbjit=off liveobjectlist=off regexp=native disassembler=off objectprint=off debuggersupport=on extrachecks=off snapshot=on werror=on x64.release ERROR: build v8 from SVN failed: code=2 DEBUG: "Makefile", line 43: Missing dependency operator "Makefile", line 45: Need an operator "Makefile", line 46: Need an operator "Makefile", line 48: Need an operator "Makefile", line 50: Need an operator "Makefile", line 52: Need an operator "Makefile", line 54: Missing dependency operator "Makefile", line 56: Need an operator "Makefile", line 58: Missing dependency operator "Makefile", line 60: Need an operator "Makefile", line 62: Missing dependency operator "Makefile", line 64: Need an operator "Makefile", line 66: Missing dependency operator "Makefile", line 68: Need an operator "Makefile", line 70: Missing dependency operator "Makefile", line 72: Need an operator "Makefile", line 73: Missing dependency operator "Makefile", line 75: Need an operator "Makefile", line 77: Missing dependency operator "Makefile", line 79: Need an operator "Makefile", line 81: Missing dependency operator "Makefile", line 83: Need an operator "Makefile", line 85: Missing dependency operator "Makefile", line 87: Need an operator "Makefile", line 89: Need an operator "Makefile", line 91: Missing dependency operator "Makefile", line 93: Need an operator "Makefile", line 95: Need an operator "Makefile", line 97: Need an operator "Makefile", line 99: Missing dependency operator "Makefile", line 101: Need an operator "Makefile", line 103: Missing dependency operator "Makefile", line 105: Need an operator "Makefile", line 107: Missing dependency operator "Makefile", line 109: Need an operator "Makefile", line 111: Missing dependency operator "Makefile", line 113: Need an operator "Makefile", line 115: Missing dependency operator "Makefile", line 117: Need an operator Error expanding embedded variable. The files that are installed by the v8 port are the following (in /usr/local): bin/d8 include/v8.h include/v8-debug.h include/v8-preparser.h include/v8-profiler.h include/v8-testing.h include/v8stdint.h lib/libv8.so lib/libv8.so.1

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• Why can't I build Deluge?

  - by hugemeow

  Deluge is a BitTorrent Client. I am trying to build it from source, since I don't have privilege to install it as root. I am using python setup.py build. But, it failed following message, why? copying deluge/ui/web/themes/images/gray/slider/slider-v-thumb.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/gray/slider copying deluge/ui/web/themes/images/gray/slider/slider-thumb.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/gray/slider copying deluge/ui/web/themes/images/gray/panel/top-bottom.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/gray/panel copying deluge/ui/web/themes/images/gray/tabs/tab-strip-bg.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/gray/tabs copying deluge/ui/web/themes/images/yourtheme/window/right-corners.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/window copying deluge/ui/web/themes/images/yourtheme/window/left-corners.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/window copying deluge/ui/web/themes/images/yourtheme/window/left-right.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/window copying deluge/ui/web/themes/images/yourtheme/window/top-bottom.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/window creating build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/slider copying deluge/ui/web/themes/images/yourtheme/slider/slider-v-thumb.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/slider copying deluge/ui/web/themes/images/yourtheme/slider/slider-thumb.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/slider copying deluge/ui/web/themes/images/yourtheme/slider/slider-bg.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/slider copying deluge/ui/web/themes/images/yourtheme/slider/slider-v-bg.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/slider copying deluge/ui/web/themes/images/yourtheme/panel/top-bottom.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/panel copying deluge/ui/web/themes/images/yourtheme/grid/hmenu-lock.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/grid copying deluge/ui/web/themes/images/yourtheme/grid/hmenu-unlock.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/grid copying deluge/ui/web/themes/images/yourtheme/tabs/tab-strip-bg.png -> build/lib.linux-x86_64-2.4/deluge/ui/web/themes/images/yourtheme/tabs running build_ext building 'libtorrent' extension gcc -pthread -shared -L/usr/lib64 -L/opt/local/lib -lboost_filesystem -lboost_date_time -lboost_iostreams -lboost_python -lboost_thread -lpthread -lssl -lz -o build/lib.linux-x86_64-2.4/deluge/libtorrent.so /usr/bin/ld: cannot find -lboost_filesystem collect2: ld returned 1 exit status error: command 'gcc' failed with exit status 1 [mirror@innov deluge-1.3.5]$ echo $? 1 Edit 1: gcc version and os information $(which gcc) --version gcc (GCC) 4.1.2 20080704 (Red Hat 4.1.2-52) Copyright (C) 2006 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. cat /etc/issue CentOS release 5.7 (Final) Kernel \r on an \m Edit 2: boost is referenced by setup.py in deluge 114 if OS == "linux": 115 if os.path.exists(os.path.join(sysconfig.get_config_vars()['LIBDIR'], \ 116 'libboost_filesystem-mt.so')): 117 boost_filesystem = "boost_filesystem-mt" 118 elif os.path.exists(os.path.join(sysconfig.get_config_vars()['LIBDIR'], \ 119 'libboost_filesystem.so')): 120 boost_filesystem = "boost_filesystem" 121 if os.path.exists(os.path.join(sysconfig.get_config_vars()['LIBDIR'], \ 122 'libboost_date_time-mt.so')): 123 boost_date_time = "boost_date_time-mt" 124 elif os.path.exists(os.path.join(sysconfig.get_config_vars()['LIBDIR'], \ 125 'libboost_date_time.so')): 126 boost_date_time = "boost_date_time" 127 if os.path.exists(os.path.join(sysconfig.get_config_vars()['LIBDIR'], \ 128 'libboost_thread-mt.so')): 129 boost_thread = "boost_thread-mt" 130 elif os.path.exists(os.path.join(sysconfig.get_config_vars()['LIBDIR'], \ 131 'libboost_thread.so')): 132 boost_thread = "boost_thread" 133 134 if 'boost_filesystem' not in vars(): 135 boost_filesystem = "boost_filesystem-mt" 136 if 'boost_date_time' not in vars(): 137 boost_date_time = "boost_date_time-mt" 138 if 'boost_thread' not in vars(): 139 boost_thread = "boost_thread-mt" 140 141 elif OS == "freebsd": 142 boost_filesystem = "boost_filesystem" 143 boost_date_time = "boost_date_time" 144 boost_thread = "boost_thread" 145 else: 146 boost_filesystem = "boost_filesystem-mt" 147 boost_date_time = "boost_date_time-mt" 148 boost_thread = "boost_thread-mt" 149 150 librariestype = [boost_filesystem, boost_date_time, 151 boost_thread, 'z', 'pthread', 'ssl', 'crypto']

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• How to configure emacs by using this file?

  - by Andy Leman

  From http://public.halogen-dg.com/browser/alex-emacs-settings/.emacs?rev=1346 I got: (setq load-path (cons "/home/alex/.emacs.d/" load-path)) (setq load-path (cons "/home/alex/.emacs.d/configs/" load-path)) (defconst emacs-config-dir "~/.emacs.d/configs/" "") (defun load-cfg-files (filelist) (dolist (file filelist) (load (expand-file-name (concat emacs-config-dir file))) (message "Loaded config file:%s" file) )) (load-cfg-files '("cfg_initsplit" "cfg_variables_and_faces" "cfg_keybindings" "cfg_site_gentoo" "cfg_conf-mode" "cfg_mail-mode" "cfg_region_hooks" "cfg_apache-mode" "cfg_crontab-mode" "cfg_gnuserv" "cfg_subversion" "cfg_css-mode" "cfg_php-mode" "cfg_tramp" "cfg_killbuffer" "cfg_color-theme" "cfg_uniquify" "cfg_tabbar" "cfg_python" "cfg_ack" "cfg_scpaste" "cfg_ido-mode" "cfg_javascript" "cfg_ange_ftp" "cfg_font-lock" "cfg_default_face" "cfg_ecb" "cfg_browser" "cfg_orgmode" ; "cfg_gnus" ; "cfg_cyrillic" )) ; enable disabled advanced features (put 'downcase-region 'disabled nil) (put 'scroll-left 'disabled nil) (put 'upcase-region 'disabled nil) ; narrow cursor ;(setq-default cursor-type 'hbar) (cua-mode) ; highlight current line (global-hl-line-mode 1) ; AV: non-aggressive scrolling (setq scroll-conservatively 100) (setq scroll-preserve-screen-position 't) (setq scroll-margin 0) (custom-set-variables ;; custom-set-variables was added by Custom. ;; If you edit it by hand, you could mess it up, so be careful. ;; Your init file should contain only one such instance. ;; If there is more than one, they won't work right. '(ange-ftp-passive-host-alist (quote (("redbus2.chalkface.com" . "on") ("zope.halogen-dg.com" . "on") ("85.119.217.50" . "on")))) '(blink-cursor-mode nil) '(browse-url-browser-function (quote browse-url-firefox)) '(browse-url-new-window-flag t) '(buffers-menu-max-size 30) '(buffers-menu-show-directories t) '(buffers-menu-show-status nil) '(case-fold-search t) '(column-number-mode t) '(cua-enable-cua-keys nil) '(user-mail-address "[email protected]") '(cua-mode t nil (cua-base)) '(current-language-environment "UTF-8") '(file-name-shadow-mode t) '(fill-column 79) '(grep-command "grep --color=never -nHr -e * | grep -v .svn --color=never") '(grep-use-null-device nil) '(inhibit-startup-screen t) '(initial-frame-alist (quote ((width . 80) (height . 40)))) '(initsplit-customizations-alist (quote (("tabbar" "configs/cfg_tabbar.el" t) ("ecb" "configs/cfg_ecb.el" t) ("ange\\-ftp" "configs/cfg_ange_ftp.el" t) ("planner" "configs/cfg_planner.el" t) ("dired" "configs/cfg_dired.el" t) ("font\\-lock" "configs/cfg_font-lock.el" t) ("speedbar" "configs/cfg_ecb.el" t) ("muse" "configs/cfg_muse.el" t) ("tramp" "configs/cfg_tramp.el" t) ("uniquify" "configs/cfg_uniquify.el" t) ("default" "configs/cfg_font-lock.el" t) ("ido" "configs/cfg_ido-mode.el" t) ("org" "configs/cfg_orgmode.el" t) ("gnus" "configs/cfg_gnus.el" t) ("nnmail" "configs/cfg_gnus.el" t)))) '(ispell-program-name "aspell") '(jabber-account-list (quote (("[email protected]")))) '(jabber-nickname "AVK") '(jabber-password nil) '(jabber-server "halogen-dg.com") '(jabber-username "alex") '(remember-data-file "~/Plans/remember.org") '(safe-local-variable-values (quote ((dtml-top-element . "body")))) '(save-place t nil (saveplace)) '(scroll-bar-mode (quote right)) '(semantic-idle-scheduler-idle-time 432000) '(show-paren-mode t) '(svn-status-hide-unmodified t) '(tool-bar-mode nil nil (tool-bar)) '(transient-mark-mode t) '(truncate-lines f) '(woman-use-own-frame nil)) ; ?? ????? ??????? y ??? n? (fset 'yes-or-no-p 'y-or-n-p) (custom-set-faces ;; custom-set-faces was added by Custom. ;; If you edit it by hand, you could mess it up, so be careful. ;; Your init file should contain only one such instance. ;; If there is more than one, they won't work right. '(compilation-error ((t (:foreground "tomato" :weight bold)))) '(cursor ((t (:background "red1")))) '(custom-variable-tag ((((class color) (background dark)) (:inherit variable-pitch :foreground "DarkOrange" :weight bold)))) '(hl-line ((t (:background "grey24")))) '(isearch ((t (:background "orange" :foreground "black")))) '(message-cited-text ((((class color) (background dark)) (:foreground "SandyBrown")))) '(message-header-name ((((class color) (background dark)) (:foreground "DarkGrey")))) '(message-header-other ((((class color) (background dark)) (:foreground "LightPink2")))) '(message-header-subject ((((class color) (background dark)) (:foreground "yellow2")))) '(message-separator ((((class color) (background dark)) (:foreground "thistle")))) '(region ((t (:background "brown")))) '(tooltip ((((class color)) (:inherit variable-pitch :background "IndianRed1" :foreground "black"))))) The above is a python emacs configure file. Where should I put it to use it? And, are there any other changes I need to make?

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• Stack usage with MMX intrinsics and Microsoft C++

  - by arik-funke

  I have an inline assembler loop that cumulatively adds elements from an int32 data array with MMX instructions. In particular, it uses the fact that the MMX registers can accommodate 16 int32s to calculate 16 different cumulative sums in parallel. I would now like to convert this piece of code to MMX intrinsics but I am afraid that I will suffer a performance penalty because one cannot explicitly intruct the compiler to use the 8 MMX registers to accomulate 16 independent sums. Can anybody comment on this and maybe propose a solution on how to convert the piece of code below to use intrinsics? == inline assembler (only part within the loop) == paddd mm0, [esi+edx+8*0] ; add first & second pair of int32 elements paddd mm1, [esi+edx+8*1] ; add third & fourth pair of int32 elements ... paddd mm2, [esi+edx+8*2] paddd mm3, [esi+edx+8*3] paddd mm4, [esi+edx+8*4] paddd mm5, [esi+edx+8*5] paddd mm6, [esi+edx+8*6] paddd mm7, [esi+edx+8*7] ; add 15th & 16th pair of int32 elements esi points to the beginning of the data array edx provides the offset in the data array for the current loop iteration the data array is arranged such that the elements for the 16 independent sums are interleaved.

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• Ideas on frameworks in .NET that can be used for job processing and notifications

  - by Rajat Mehta

  Scenario: We have one instance of WCF windows service which exposes contracts like: AddNewJob(Job job), GetJobs(JobQuery query) etc. This service is consumed by 70-100 instances of client which is Windows Form based .NET app. Typically the service has 50-100 inward calls/minute to add or query jobs that are stored in a table on Sql Server. The same service is also responsible for processing these jobs in real time. It queries database every 5 seconds picks up the queued jobs and starts processing them. A job has 6 states. Queued, Pre-processing, Processing, Post-processing, Completed, Failed, Locked. Another responsibility on this service is to update all clients on every state change of every job. This means almost 200+ callbacks to clients per second. Question: This whole implementation is done using WCF Duplex bindings and works perfectly fine on small number of parallel jobs. Problem arises when we scale it up to 1000 jobs at a time. The notifications don't work as expected, it leads to memory overflow etc. Is there any standard framework that can provide a clean infrastructure for handling this scenario?? Apologies for the long explanation!

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• Thread management advice - Is TPL a good idea?

  - by Ian

  I'm hoping to get some advice on the use of thread managment and hopefully the task parallel library, because I'm not sure I've been going down the correct route. Probably best is that I give an outline of what I'm trying to do. Given a Problem I need to generate a Solution using a heuristic based algorithm. I start of by calculating a base solution, this operation I don't think can be parallelised so we don't need to worry about. Once the inital solution has been generated, I want to trigger n threads, which attempt to find a better solution. These threads need to do a couple of things: They need to be initalized with a different 'optimization metric'. In other words they are attempting to optimize different things, with a precedence level set within code. This means they all run slightly different calculation engines. I'm not sure if I can do this with the TPL.. If one of the threads finds a better solution that the currently best known solution (which needs to be shared across all threads) then it needs to update the best solution, and force a number of other threads to restart (again this depends on precedence levels of the optimization metrics). I may also wish to combine certain calculations across threads (e.g. keep a union of probabilities for a certain approach to the problem). This is probably more optional though. The whole system needs to be thread safe obviously and I want it to be running as fast as possible. I tried quite an implementation that involved managing my own threads and shutting them down etc, but it started getting quite complicated, and I'm now wondering if the TPL might be better. I'm wondering if anyone can offer any general guidance? Thanks...

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• What hash algorithms are paralellizable? Optimizing the hashing of large files utilizing on mult-co

  - by DanO

  I'm interested in optimizing the hashing of some large files (optimizing wall clock time). The I/O has been optimized well enough already and the I/O device (local SSD) is only tapped at about 25% of capacity, while one of the CPU cores is completely maxed-out. I have more cores available, and in the future will likely have even more cores. So far I've only been able to tap into more cores if I happen to need multiple hashes of the same file, say an MD5 AND a SHA256 at the same time. I can use the same I/O stream to feed two or more hash algorithms, and I get the faster algorithms done for free (as far as wall clock time). As I understand most hash algorithms, each new bit changes the entire result, and it is inherently challenging/impossible to do in parallel. Are any of the mainstream hash algorithms parallelizable? Are there any non-mainstream hashes that are parallelizable (and that have at least a sample implementation available)? As future CPUs will trend toward more cores and a leveling off in clock speed, is there any way to improve the performance of file hashing? (other than liquid nitrogen cooled overclocking?) or is it inherently non-parallelizable?

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• OpenMP: Get total number of running threads

  - by Konrad Rudolph

  I need to know the total number of threads that my application has spawned via OpenMP. Unfortunately, the omp_get_num_threads() function does not work here since it only yields the number of threads in the current team. However, my code runs recursively (divide and conquer, basically) and I want to spawn new threads as long as there are still idle processors, but no more. Is there a way to get around the limitations of omp_get_num_threads and get the total number of running threads? If more detail is required, consider the following pseudo-code that models my workflow quite closely: function divide_and_conquer(Job job, int total_num_threads): if job.is_leaf(): # Recurrence base case. job.process() return left, right = job.divide() current_num_threads = omp_get_num_threads() if current_num_threads < total_num_threads: # (1) #pragma omp parallel num_threads(2) #pragma omp section divide_and_conquer(left, total_num_threads) #pragma omp section divide_and_conquer(right, total_num_threads) else: divide_and_conquer(left, total_num_threads) divide_and_conquer(right, total_num_threads) job = merge(left, right) If I call this code with a total_num_threads value of 4, the conditional annotated with (1) will always evaluate to true (because each thread team will contain at most two threads) and thus the code will always spawn two new threads, no matter how many threads are already running at a higher level. I am searching for a platform-independent way of determining the total number of threads that are currently running in my application.

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• What hash algorithms are parallelizable? Optimizing the hashing of large files utilizing on multi-co

  - by DanO

  I'm interested in optimizing the hashing of some large files (optimizing wall clock time). The I/O has been optimized well enough already and the I/O device (local SSD) is only tapped at about 25% of capacity, while one of the CPU cores is completely maxed-out. I have more cores available, and in the future will likely have even more cores. So far I've only been able to tap into more cores if I happen to need multiple hashes of the same file, say an MD5 AND a SHA256 at the same time. I can use the same I/O stream to feed two or more hash algorithms, and I get the faster algorithms done for free (as far as wall clock time). As I understand most hash algorithms, each new bit changes the entire result, and it is inherently challenging/impossible to do in parallel. Are any of the mainstream hash algorithms parallelizable? Are there any non-mainstream hashes that are parallelizable (and that have at least a sample implementation available)? As future CPUs will trend toward more cores and a leveling off in clock speed, is there any way to improve the performance of file hashing? (other than liquid nitrogen cooled overclocking?) or is it inherently non-parallelizable?

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• The best way to predict performance without actually porting the code?

  - by ardiyu07

  I believe there are people with the same experience with me, where he/she must give a (estimated) performance report of porting a program from sequential to parallel with some designated multicore hardwares, with a very few amount of time given. For instance, if a 10K LoC sequential program was given and executes on Intel i7-3770k (not vectorized) in 100 ms, how long would it take to run if one parallelizes the code to a Tesla C2075 with NVIDIA CUDA, given that all kinds of parallelizing optimization techniques were done? (but you're only given 2-4 days to report the performance? assume that you didn't know the algorithm at all. Or perhaps it'd be safer if we just assume that it's an impossible situation to finish the job) Therefore, I'm wondering, what most likely be the fastest way to give such performance report? Is it safe to calculate solely by the hardware's capability, such as GFLOPs peak and memory bandwidth rate? Is there a mathematical way to calculate it? If there is, please prove your method with the corresponding problem description and the algorithm, and also the target hardwares' specifications. Or perhaps there already exists such tool to (roughly) estimate code porting? (Please don't the answer: 'kill yourself is the fastest way.')

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