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  • How many layers are between my program and the hardware?

    - by sub
    I somehow have the feeling that modern systems, including runtime libraries, this exception handler and that built-in debugger build up more and more layers between my (C++) programs and the CPU/rest of the hardware. I'm thinking of something like this: 1 + 2 OS top layer Runtime library/helper/error handler a hell lot of DLL modules OS kernel layer Do you really want to run 1 + 2?-Windows popup (don't take this serious) OS kernel layer Hardware abstraction Hardware Go through at least 100 miles of circuits Eventually arrive at the CPU ADD 1, 2 Go all the way back to my program Nearly all technical things are simply wrong and in some random order, but you get my point right? How much longer/shorter is this chain when I run a C++ program that calculates 1 + 2 at runtime on Windows? How about when I do this in an interpreter? (Python|Ruby|PHP) Is this chain really as dramatic in reality? Does Windows really try "not to stand in the way"? e.g.: Direct connection my binary < hardware?

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  • Computationally intensive scala process using actors hangs uncooperatively

    - by Chick Markley
    I have a computationally intensive scala application that hangs. By hangs I means it is sitting in the process stack using 1% CPU but does not respond to kill -QUIT nor can it be attached via jdb attach. Runs 2-12 hours at 800-900% CPU before it gets stuck The application is using ~10 scala.actors. Until now I have had great success with kill -QUIT but I am bit stumped as to how to proceed. The actors write a fair amount to stdout using println which is redirected to a text file but has not been helpful so far diagnostically. I am just hoping there is some obvious technique when kill -QUIT fails that I am ignorant of. Or just confirmation that having multiple actors println asynchronously is a real bad idea (though I've been doing it for a long time only recently with these results) Details scala 2.8.1 & 2.8.0 mac osx 10.6.5 java version "1.6.0_22" Thanks

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  • Limiting the maximum number of concurrent requests django/apache

    - by Johan
    Hi, I have a django site that demonstrates the usage of a tool. One of my views takes a file as input and runs some fairly heavy computation trough an external python script and returns some output to the user. The tool runs fast enough to return the output in the same request though. I would however want to limit how many concurrent requests to this URL/view to keep the server from getting congested. Any tips on how i would go about doing this? The page in itself is very simple and the usage will be low.

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  • Criteria for selecting software for embedded device

    - by Suresh Kumar
    We are currently evaluating Web servers for an embedded device. We have laid down the evaluation criteria for things like HTTP version, Security, Compression etc. On the embeddable side, we have identified the following criteria: Memory footprint Memory management (support for plugging in a custom memory manager) CPU usage Thread usage (support for thread pool) Portability What I want inputs on is: Are there any other criteria that an embeddable software should meet? What exactly does it mean when someone says that a software is designed for embeddable use? We currently have zeroed in on two Web servers: AppWeb Lighttpd (lighty) Feature wise, both the above Web servers seem to be on par. However, it is claimed that AppWeb is designed for embedded use while Lighttpd is not. To choose between the above two Web servers, what criteria should I be looking at?

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  • SQL 2008 Encryption Scan

    - by Mike K.
    We recently upgraded a database server from SQL 2005 to SQL 2008 64 bit. CPU utilization is oftentimes running at 100% on all four processors now (this never happended on the SQL 2005 server). When I run sp_lock I see a number of processes waiting on a resource called [ENCRYPTION_SCAN]. I am not using any SQL 2008 encryption features. Does anyone know why I would have tasks waiting on this resource? It appears that whenever I have four processes waiting on this resource, CPU hits 100% on all four processors.

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  • How do I format positional argument help using Python's optparse?

    - by cdleary
    As mentioned in the docs the optparse.OptionParser uses an IndentedHelpFormatter to output the formatted option help, for which which I found some API documentation. I want to display a similarly formatted help text for the required, positional arguments in the usage text. Is there an adapter or a simple usage pattern that can be used for similar positional argument formatting? Clarification Preferably only using the stdlib. Optparse does great except for this one formatting nuance, which I feel like we should be able to fix without importing whole other packages. :-)

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  • ffmpeg libavcodec.so missing while compile with cygwin

    - by nick
    I am building ffmpeg for android by following this tutorial now i got android folder inside the ffmpeg2.0.1 folder but there is no libavcodec-55.so file. instead of that i have lib/libavcodec.a how can i get libavcodec.so file? build_android.sh #!/bin/bash NDK=$HOME/Desktop/adt/android-ndk-r9 SYSROOT=$NDK/platforms/android-9/arch-arm/ TOOLCHAIN=$NDK/toolchains/arm-linux-androideabi-4.8/prebuilt/windows-x86_64 function build_one { ./configure \ --prefix=$PREFIX \ --enable-shared \ --disable-static \ --disable-doc \ --disable-ffmpeg \ --disable-ffplay \ --disable-ffprobe \ --disable-ffserver \ --disable-avdevice \ --disable-doc \ --disable-symver \ --cross-prefix=$TOOLCHAIN/bin/arm-linux-androideabi- \ --target-os=linux \ --arch=arm \ --enable-cross-compile \ --sysroot=$SYSROOT \ --extra-cflags="-Os -fpic $ADDI_CFLAGS" \ --extra-ldflags="$ADDI_LDFLAGS" \ $ADDITIONAL_CONFIGURE_FLAG make clean make make install } CPU=arm PREFIX=$(pwd)/android/$CPU ADDI_CFLAGS="-marm" build_one

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  • Java Heap Overflow, Forcing Garbage Collection

    - by Nicholas
    I've create a trie tree with an array of children. When deleting a word, I set the children null, which I would assume deletes the node(delete is a relative term). I know that null doesn't delete the child, just sets it to null, which when using a large amount of words it causes to overflow the heap. Running a top on linux, I can see my memory usage spike to 1gb pretty quickly, but if I force garbage collection after the delete (Runtime.gc()) the memory usage goes to 50mb and never above that. From what I'm told, java by default runs garbage collection before a heap overflow happens, but I can't see to make that happen.

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  • Continuously checking database from a Windows service

    - by JonF
    I am making a Windows service which needs to continuously check for database entries that can be added at any time to tell it to execute some code. It is looking to see if it's status is set to pending, and it's execute time entry is than the current time. Is the only way to do this to just run select statements over and over? It might need to execute the code every minute which means I need to run the select statement every minute looking for entries in the database. I'm trying to avoid unneccesary cpu time because I'm probably going to end up paying for cpu cycles on the hosting provider

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  • Are all the system's floating points operations the same?

    - by Jj
    We're making this web app in PHP and when working in the reports we have Excel files to compare our results to make sure our coding is doing the right operations. Now we're running into some differences due floating point arithmetics. We're doing the same divisions and multiplications and running into slightly different numbers, that add up to a notable difference. My question is if Excel is delegating it's floating point arithmetic to the CPU and PHP is also relying in the CPU for it's operations. Or does each application implements its own set of math algorithms?

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  • measuring performance - using real clicks vs "ab" command

    - by shanyu
    I have a web site in closed beta, developed in Django, runs with Mysql on Debian. In the last few days, the main page has been showing a slowdown. For every ten clicks, one or two receives extremely slow response (10 secs or more), others are as fast as they used to be. When I was searching for the problem, I ran into this issue that I couldn't grasp: top command shows that when I request the main page, mysql shoots up to 90% - 100% cpu usage. I get the page just as the cpu use gets back to normal. So, I thought, it is db. Then I called ab with parameters -n 1000 -c 5, I got decent performance, about 100 pages per second, just as it was before the slowdown. I would imagine a worse performance as 10-20% of requests take 10 secs to load. Is this conflict between ab and "real" clicks normal, or am I using ab in a wrong configuration?

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  • Alternative databases to use when putting IIS Logs into a database using LogParser

    - by Robin Day
    We have run some scripts that use LogParser to dump our IIS logs into a SQL Server database. We can then query this to get simple stats on hits, usage etc. It's also good when linking it to error log databases and performance counter database to compare usage with errors, etc. Having implemented this for just one system and for the last 2-3 weeks we already have a 5GB database with around 10 million records. This is making any queries to this database quite slow and will no doubt cause storage issues if we continue to log as we are. Can anyone suggest any alternative databases that we could use for this data that would be more efficient for such logs? I'd be particularly interested in any experience of Google's BigTable or Amazon's SimbleDB. Are either of these suitable for reporting queries? COUNTs, GROUP BYs, PIVOTs?

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  • how to set a status

    - by ejah85
    hello guys..here i've a problem where i want to set the status whether it is approved or reject.. the condition are if admin select the registration number and driver name, that means the status is approve otherwise, if admin fill up the reason, that means the request is reject.. here is the code to set status if ($reason =='null'){ $query2 = "UPDATE usage SET status ='APPROVED' WHERE '$bookingno'=bookingno"; $result2 = @mysql_query($query2); } elseif (($regno =='null')&&($d_name =='null')) { $query3 = "UPDATE usage SET status ='REJECT' WHERE '$bookingno'=bookingno"; $result3 = @mysql_query($query3); } when i save the data, the status field are not updates..

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  • segmented reduction with scattered segments

    - by Christian Rau
    I got to solve a pretty standard problem on the GPU, but I'm quite new to practical GPGPU, so I'm looking for ideas to approach this problem. I have many points in 3-space which are assigned to a very small number of groups (each point belongs to one group), specifically 15 in this case (doesn't ever change). Now I want to compute the mean and covariance matrix of all the groups. So on the CPU it's roughly the same as: for each point p { mean[p.group] += p.pos; covariance[p.group] += p.pos * p.pos; ++count[p.group]; } for each group g { mean[g] /= count[g]; covariance[g] = covariance[g]/count[g] - mean[g]*mean[g]; } Since the number of groups is extremely small, the last step can be done on the CPU (I need those values on the CPU, anyway). The first step is actually just a segmented reduction, but with the segments scattered around. So the first idea I came up with, was to first sort the points by their groups. I thought about a simple bucket sort using atomic_inc to compute bucket sizes and per-point relocation indices (got a better idea for sorting?, atomics may not be the best idea). After that they're sorted by groups and I could possibly come up with an adaption of the segmented scan algorithms presented here. But in this special case, I got a very large amount of data per point (9-10 floats, maybe even doubles if the need arises), so the standard algorithms using a shared memory element per thread and a thread per point might make problems regarding per-multiprocessor resources as shared memory or registers (Ok, much more on compute capability 1.x than 2.x, but still). Due to the very small and constant number of groups I thought there might be better approaches. Maybe there are already existing ideas suited for these specific properties of such a standard problem. Or maybe my general approach isn't that bad and you got ideas for improving the individual steps, like a good sorting algorithm suited for a very small number of keys or some segmented reduction algorithm minimizing shared memory/register usage. I'm looking for general approaches and don't want to use external libraries. FWIW I'm using OpenCL, but it shouldn't really matter as the general concepts of GPU computing don't really differ over the major frameworks.

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  • Neo4j 1.9.4 (REST Server,CYPHER) performance issue

    - by user2968943
    I have Neo4j 1.9.4 installed on 24 core 24Gb ram (centos) machine and for most queries CPU usage spikes goes to 200% with only few concurrent requests. Domain: some sort of social application where few types of nodes(profiles) with 3-30 text/array properties and 36 relationship types with at least 3 properties. Most of nodes currently has ~300-500 relationships. Current data set footprint(from console): LogicalLogSize=4294907 (32MB) ArrayStoreSize=1675520 (12MB) NodeStoreSize=1342170 (10MB) PropertyStoreSize=1739548 (13MB) RelationshipStoreSize=6395202 (48MB) StringStoreSize=1478400 (11MB) which is IMHO really small. most queries looks like this one(with more or less WITH .. MATCH .. statements and few queries with variable length relations but the often fast): START targetUser=node({id}), currentUser=node({current}) MATCH targetUser-[contact:InContactsRelation]->n, n-[:InLocationRelation]->l, n-[:InCategoryRelation]->c WITH currentUser, targetUser,n, l,c, contact.fav is not null as inFavorites MATCH n<-[followers?:InContactsRelation]-() WITH currentUser, targetUser,n, l,c,inFavorites, COUNT(followers) as numFollowers RETURN id(n) as id, n.name? as name, n.title? as title, n._class as _class, n.avatar? as avatar, n.avatar_type? as avatar_type, l.name as location__name, c.name as category__name, true as isInContacts, inFavorites as isInFavorites, numFollowers it runs in ~1s-3s(for first run) and ~1s-70ms (for consecutive and it depends on query) and there is about 5-10 queries runs for each impression. Another interesting behavior is when i try run query from console(neo4j) on my local machine many consecutive times(just press ctrl+enter for few seconds) it has almost constant execution time but when i do it on server it goes slower exponentially and i guess it somehow related with my problem. Problem: So my problem is that neo4j is very CPU greedy(for 24 core machine its may be not an issue but its obviously overkill for small project). First time i used AWS EC2 m1.large instance but over all performance was bad, during testing, CPU always was over 100%. Some relevant parts of configuration: neostore.nodestore.db.mapped_memory=1280M wrapper.java.maxmemory=8192 note: I already tried configuration where all memory related parameters where HIGH and it didn't worked(no change at all). Question: Where to digg? configuration? scheme? queries? what i'm doing wrong? if need more info(logs, configs) just ask ;)

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  • Cassandra performance slow down with counter column

    - by tubcvt
    I have a cluster (4 node ) and a node have 16 core and 24 gb ram: 192.168.23.114 datacenter1 rack1 Up Normal 44.48 GB 25.00% 192.168.23.115 datacenter1 rack1 Up Normal 44.51 GB 25.00% 192.168.23.116 datacenter1 rack1 Up Normal 44.51 GB 25.00% 192.168.23.117 datacenter1 rack1 Up Normal 44.51 GB 25.00% We use about 10 column family (counter column) to make some system statistic report. Problem on here is that When i set replication_factor of this keyspace from 1 to 2 (contain 10 counter column family ), all cpu of node increase from 10% ( when use replication factor=1) to --- 90%. :( :( who can help me work around that :( . why counter column consume too much cpu time :(. thanks all

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  • How to convert code to properly release memory

    - by BankStrong
    I've taken over a code base that has subtle flaws - audio player goes mute, unlogged crashes, odd behavior, etc. I found a way to provoke one instance of the problem and tracked it to this code snippet: NSURL *soundURL = [NSURL fileURLWithPath:[[NSBundle mainBundle] pathForResource:[[soundsToPlay objectAtIndex:count] description] ofType:@"mp3"]]; self.audioPlayer = nil; self.audioPlayer = [[AVAudioPlayer alloc] initWithContentsOfURL:soundURL error:nil]; self.audioPlayer.delegate = self; AudioSessionSetActive(YES); [audioPlayer play]; When I comment out the 2nd line (nil) and add a release to the end, this problem stops. [self.audioPlayer release]; Where do I go from here? Nils are used in a similar fashion throughout the code (and may cause similar problems) - is there a safe way to remove them? I'm new to memory management - how can I discern proper nil usage from bad nil usage?

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  • StockTrader RI > Controllers, Presenters, WTF?

    - by SandRock
    I am currently learning how to make advanced usage of WPF via the Prism (Composite WPF) project. I watch many videos and examples and the demo application StockTraderRI makes me ask this question: What is the exact role of each of the following part? SomethingService: Ok, this is something to manage data SomethingView: Ok, this is what's displayed SomethingPresentationModel: Ok, this contains data and commands for the view to bind to (equivalent to a ViewModel). SomethingPresenter: I don't really understand it's usage SomethingController: Don't understand too I saw that a Presenter and a Controller are not necessary but I would like to understand why they are here. Can someone tell me their role and when to use them?

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  • When compiling programs to run inside a VM, what should march and mtune be set to?

    - by Russ
    With VMs being slave to whatever the host machine is providing, what compiler flags should be provided to gcc? I would normally think that -march=native would be what you would use when compiling for a dedicated box, but the fine detail that -march=native is going to as indicated in this article makes me extremely wary of using it. So... what to set -march and -mtune to inside a VM? For a specific example... My specific case right now is compiling python (and more) in a linux guest inside a KVM-based "cloud" host that I have no real control over the host hardware (aside from 'simple' stuff like CPU GHz m CPU count, and available RAM). Currently, cpuinfo tells me I've got an "AMD Opteron(tm) Processor 6176" but I honestly don't know (yet) if that is reliable and whether the guest can get moved around to different architectures on me to meet the host's infrastructure shuffling needs (sounds hairy/unlikely). All I can really guarantee is my OS, which is a 64-bit linux kernel where uname -m yields x86_64.

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  • AWS free tier "sign up date" vs "credit card details submission date"

    - by Mayur Rokade
    I am worried about my account expiry date. I created an account on AWS in July 2013 and submitted my credit card details on 31st Oct 2013. I went in Billing Management Console/Bills section where when I click on Date, I can see months ranging from July 2013 to Nov 2013. From AWS FAQs I gathered When does the AWS free usage tier expire? The AWS free usage tier will expire 12 months from the date you sign up. So WHEN will my account expire, July 2014 (sign up date) or Oct 2014 (credit card details submission date) ?

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  • CUDA small kernel 2d convolution - how to do it

    - by paulAl
    I've been experimenting with CUDA kernels for days to perform a fast 2D convolution between a 500x500 image (but I could also vary the dimensions) and a very small 2D kernel (a laplacian 2d kernel, so it's a 3x3 kernel.. too small to take a huge advantage with all the cuda threads). I created a CPU classic implementation (two for loops, as easy as you would think) and then I started creating CUDA kernels. After a few disappointing attempts to perform a faster convolution I ended up with this code: http://www.evl.uic.edu/sjames/cs525/final.html (see the Shared Memory section), it basically lets a 16x16 threads block load all the convolution data he needs in the shared memory and then performs the convolution. Nothing, the CPU is still a lot faster. I didn't try the FFT approach because the CUDA SDK states that it is efficient with large kernel sizes. Whether or not you read everything I wrote, my question is: how can I perform a fast 2D convolution between a relatively large image and a very small kernel (3x3) with CUDA?

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  • Programatically determining maximum transfer rate

    - by dauphic
    I have a problem that requires me to calculate the maximum upload and download available, then limit my program's usage to a percentage of it. However, I can't think of a good way to find the maximums. At the moment, the only solution I can come up with is transfering a few megabytes between the client and server, then measuring how ling the transfer took. This solution is very undesirable, however, because with 100,000 clients it could potentially result in too much of an increase to our server's bandwidth usage (which is already too high). Does anyone have any solutions to this problem?

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  • FOSS HTML to PDF in Python, .Net or command line?

    - by jle
    I have google as much as I possible, checked stackoverflow several times, and yet I can not find a good html to pdf converter that can handle css. Is there a free and open source solution (even for commercial usage)? There are many solutions, with huge variety of price ranges, but I was looking for something open source and free. I have tried PISA for Python and it works fairly well, but is not free for commercial usage. Is there anything for .Net? I have not had success with iTextSharp.

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