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  • mod_rewrite "Request exceeded the limit of 10 internal redirects due to probable configuration error."

    - by Shoaibi
    What i want: Force www [works] Restrict access to .inc.php [works] Force redirection of abc.php to /abc/ Removal of extension from url Add a trailing slash if needed old .htaccess : Options +FollowSymLinks <IfModule mod_rewrite.c> RewriteEngine On RewriteBase / ### Force www RewriteCond %{HTTP_HOST} ^example\.net$ RewriteRule ^(.*)$ http://www\.example\.net/$1 [L,R=301] ### Restrict access RewriteCond %{REQUEST_URI} ^/(.*)\.inc\.php$ [NC] RewriteRule .* - [F,L] #### Remove extension: RewriteRule ^(.*)/$ /$1.php [L,R=301] ######### Trailing slash: RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_URI} !(.*)/$ RewriteRule ^(.*)$ http://www.example.net/$1/ [R=301,L] </IfModule> New .htaccess: Options +FollowSymLinks <IfModule mod_rewrite.c> RewriteEngine On RewriteBase / ### Force www RewriteCond %{HTTP_HOST} ^example\.net$ RewriteRule ^(.*)$ http://www\.example\.net/$1 [L,R=301] ### Restrict access RewriteCond %{REQUEST_URI} ^/(.*)\.inc\.php$ [NC] RewriteRule .* - [F,L] #### Remove extension: RewriteCond %{REQUEST_FILENAME} \.php$ RewriteCond %{REQUEST_FILENAME} -f RewriteRule (.*)\.php$ /$1/ [L,R=301] #### Map pseudo-directory to PHP file RewriteCond %{REQUEST_FILENAME}\.php -f RewriteRule (.*) /$1.php [L] ######### Trailing slash: RewriteCond %{REQUEST_FILENAME} -d RewriteCond %{REQUEST_FILENAME} !/$ RewriteRule (.*) $1/ [L,R=301] </IfModule> errorlog: Request exceeded the limit of 10 internal redirects due to probable configuration error. Use 'LimitInternalRecursion' to increase the limit if necessary. Use 'LogLevel debug' to get a backtrace., referer: http://www.example.net/ Rewrite.log: http://pastebin.com/x5PKeJHB

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  • Is there a limit setting a php_admin_value in php-fpm?

    - by PeeHaa
    I am trying to set a large value in the configuration of a pool in php-fpm, but at some point it just doesn't start anymore. php_admin_value[disable_functions] = dl,exec,passthru,shell_exec,system,proc_open,popen,curl_exec,curl_multi_exec,parse_ini_file,show_source,pcntl_exec,include,include_once,require,require_once,posix_mkfifo,posix_getlogin,posix_ttyname,getenv,get_current_use,proc_get_status,get_cfg_va,disk_free_space,disk_total_space,diskfreespace,getcwd,getlastmo,getmygid,getmyinode,getmypid,getmyuid,ini_set,mail,proc_nice,proc_terminate,proc_close,pfsockopen,fsockopen,apache_child_terminate,posix_kill,posix_mkfifo,posix_setpgid,posix_setsid,posix_setuid,fopen,tmpfile,bzopen,gzopen,chgrp,chmod,chown,copy,file_put_contents,lchgrp,lchown,link,mkdi,move_uploaded_file,rename,rmdi,symlink,tempnam,touch,unlink,iptcembed,ftp_get,ftp_nb_get,file_exists,file_get_contents,file,fileatime,filectime,filegroup,fileinode,filemtime,fileowne,fileperms,filesize,filetype,glob,is_di,is_executable,is_file,is_link,is_readable,is_uploaded_file,is_writable,is_writeable,linkinfo,lstat,parse_ini_file,pathinfo,readfile,readlink,realpath,stat,gzfile,create_function When trying to restart php-fpm it fails with the following message: Stopping php-fpm: [ OK ] Starting php-fpm: [20-Oct-2013 22:31:52] ERROR: [/etc/php-fpm.d/codepad.conf:235] value is NULL for a ZEND_INI_PARSER_ENTRY [20-Oct-2013 22:31:52] ERROR: Unable to include /etc/php-fpm.d/codepad.conf from /etc/php-fpm.conf at line 235 [20-Oct-2013 22:31:52] ERROR: failed to load configuration file '/etc/php-fpm.conf' [20-Oct-2013 22:31:52] ERROR: FPM initialization failed [FAILED] When I remove the last disabled function (create_function) it start again. I also tried with other functions, but this gives the same error so it's not related to the create_function function. The string currently is just over 1KB in size so it looks like I have hit a limit here? Is my assumption correct? Is there a way to overcome this limit? I also tried to add another php_admin_value[disable_functions] underneath it (hoping it would be appended), but that didn't work (it just used the first one).

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  • SAP dévoile Business Object 4.0, la nouvelle version de sa solution BI intègre la mobilité, les réseaux sociaux et le « in-memory »

    SAP dévoile Business Object 4.0 La nouvelle version de sa solution BI intègre la mobilité, les réseaux sociaux et le « in-memory » SAP vient de dévoiler Business Object 4.0, la prochaine version de sa plate-forme de nouvelle génération de Business Intelligence et de Gestion d'Information d'Entreprise (EIM). [IMG]http://ftp-developpez.com/gordon-fowler/SAP/Slide-5-SAP-BusinessObjects-4.0-Event-Insight2.jpg[/IMG] Après SAP ByDesign 2.6, sa suite ERP en mode SaaS (qui arrive avec un tout nouveau SDK), Business Object 4.0 est la deuxième très grosse annonce de cette année 2011 que Nicolas Sekkaki, Direc...

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  • How do you limit root partition disk access to allow drive to go into stanby mode?

    - by Casey
    When there are no users on my system, I would like the hard disk to spindown to low-power state. I realize that this might not be 100% achievable for a straight 24 hours, but it seems reasonable that the system could remain idle for a few hours at a time when it is not in use. My system is headless and running a limited number of services. The primary services are: exim4, mythtv-backend, nfs, samba, cups, apt-cacher-ng Assume that drives are already enabled to go into standby mode. Also, its not acceptable to increase the write-back timeout, since my system is not on a UPS.

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  • tile_static, tile_barrier, and tiled matrix multiplication with C++ AMP

    - by Daniel Moth
    We ended the previous post with a mechanical transformation of the C++ AMP matrix multiplication example to the tiled model and in the process introduced tiled_index and tiled_grid. This is part 2. tile_static memory You all know that in regular CPU code, static variables have the same value regardless of which thread accesses the static variable. This is in contrast with non-static local variables, where each thread has its own copy. Back to C++ AMP, the same rules apply and each thread has its own value for local variables in your lambda, whereas all threads see the same global memory, which is the data they have access to via the array and array_view. In addition, on an accelerator like the GPU, there is a programmable cache, a third kind of memory type if you'd like to think of it that way (some call it shared memory, others call it scratchpad memory). Variables stored in that memory share the same value for every thread in the same tile. So, when you use the tiled model, you can have variables where each thread in the same tile sees the same value for that variable, that threads from other tiles do not. The new storage class for local variables introduced for this purpose is called tile_static. You can only use tile_static in restrict(direct3d) functions, and only when explicitly using the tiled model. What this looks like in code should be no surprise, but here is a snippet to confirm your mental image, using a good old regular C array // each tile of threads has its own copy of locA, // shared among the threads of the tile tile_static float locA[16][16]; Note that tile_static variables are scoped and have the lifetime of the tile, and they cannot have constructors or destructors. tile_barrier In amp.h one of the types introduced is tile_barrier. You cannot construct this object yourself (although if you had one, you could use a copy constructor to create another one). So how do you get one of these? You get it, from a tiled_index object. Beyond the 4 properties returning index objects, tiled_index has another property, barrier, that returns a tile_barrier object. The tile_barrier class exposes a single member, the method wait. 15: // Given a tiled_index object named t_idx 16: t_idx.barrier.wait(); 17: // more code …in the code above, all threads in the tile will reach line 16 before a single one progresses to line 17. Note that all threads must be able to reach the barrier, i.e. if you had branchy code in such a way which meant that there is a chance that not all threads could reach line 16, then the code above would be illegal. Tiled Matrix Multiplication Example – part 2 So now that we added to our understanding the concepts of tile_static and tile_barrier, let me obfuscate rewrite the matrix multiplication code so that it takes advantage of tiling. Before you start reading this, I suggest you get a cup of your favorite non-alcoholic beverage to enjoy while you try to fully understand the code. 01: void MatrixMultiplyTiled(vector<float>& vC, const vector<float>& vA, const vector<float>& vB, int M, int N, int W) 02: { 03: static const int TS = 16; 04: array_view<const float,2> a(M, W, vA); 05: array_view<const float,2> b(W, N, vB); 06: array_view<writeonly<float>,2> c(M,N,vC); 07: parallel_for_each(c.grid.tile< TS, TS >(), 08: [=] (tiled_index< TS, TS> t_idx) restrict(direct3d) 09: { 10: int row = t_idx.local[0]; int col = t_idx.local[1]; 11: float sum = 0.0f; 12: for (int i = 0; i < W; i += TS) { 13: tile_static float locA[TS][TS], locB[TS][TS]; 14: locA[row][col] = a(t_idx.global[0], col + i); 15: locB[row][col] = b(row + i, t_idx.global[1]); 16: t_idx.barrier.wait(); 17: for (int k = 0; k < TS; k++) 18: sum += locA[row][k] * locB[k][col]; 19: t_idx.barrier.wait(); 20: } 21: c[t_idx.global] = sum; 22: }); 23: } Notice that all the code up to line 9 is the same as per the changes we made in part 1 of tiling introduction. If you squint, the body of the lambda itself preserves the original algorithm on lines 10, 11, and 17, 18, and 21. The difference being that those lines use new indexing and the tile_static arrays; the tile_static arrays are declared and initialized on the brand new lines 13-15. On those lines we copy from the global memory represented by the array_view objects (a and b), to the tile_static vanilla arrays (locA and locB) – we are copying enough to fit a tile. Because in the code that follows on line 18 we expect the data for this tile to be in the tile_static storage, we need to synchronize the threads within each tile with a barrier, which we do on line 16 (to avoid accessing uninitialized memory on line 18). We also need to synchronize the threads within a tile on line 19, again to avoid the race between lines 14, 15 (retrieving the next set of data for each tile and overwriting the previous set) and line 18 (not being done processing the previous set of data). Luckily, as part of the awesome C++ AMP debugger in Visual Studio there is an option that helps you find such races, but that is a story for another blog post another time. May I suggest reading the next section, and then coming back to re-read and walk through this code with pen and paper to really grok what is going on, if you haven't already? Cool. Why would I introduce this tiling complexity into my code? Funny you should ask that, I was just about to tell you. There is only one reason we tiled our extent, had to deal with finding a good tile size, ensure the number of threads we schedule are correctly divisible with the tile size, had to use a tiled_index instead of a normal index, and had to understand tile_barrier and to figure out where we need to use it, and double the size of our lambda in terms of lines of code: the reason is to be able to use tile_static memory. Why do we want to use tile_static memory? Because accessing tile_static memory is around 10 times faster than accessing the global memory on an accelerator like the GPU, e.g. in the code above, if you can get 150GB/second accessing data from the array_view a, you can get 1500GB/second accessing the tile_static array locA. And since by definition you are dealing with really large data sets, the savings really pay off. We have seen tiled implementations being twice as fast as their non-tiled counterparts. Now, some algorithms will not have performance benefits from tiling (and in fact may deteriorate), e.g. algorithms that require you to go only once to global memory will not benefit from tiling, since with tiling you already have to fetch the data once from global memory! Other algorithms may benefit, but you may decide that you are happy with your code being 150 times faster than the serial-version you had, and you do not need to invest to make it 250 times faster. Also algorithms with more than 3 dimensions, which C++ AMP supports in the non-tiled model, cannot be tiled. Also note that in future releases, we may invest in making the non-tiled model, which already uses tiling under the covers, go the extra step and use tile_static memory on your behalf, but it is obviously way to early to commit to anything like that, and we certainly don't do any of that today. Comments about this post by Daniel Moth welcome at the original blog.

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  • C# Performance Pitfall – Interop Scenarios Change the Rules

    - by Reed
    C# and .NET, overall, really do have fantastic performance in my opinion.  That being said, the performance characteristics dramatically differ from native programming, and take some relearning if you’re used to doing performance optimization in most other languages, especially C, C++, and similar.  However, there are times when revisiting tricks learned in native code play a critical role in performance optimization in C#. I recently ran across a nasty scenario that illustrated to me how dangerous following any fixed rules for optimization can be… The rules in C# when optimizing code are very different than C or C++.  Often, they’re exactly backwards.  For example, in C and C++, lifting a variable out of loops in order to avoid memory allocations often can have huge advantages.  If some function within a call graph is allocating memory dynamically, and that gets called in a loop, it can dramatically slow down a routine. This can be a tricky bottleneck to track down, even with a profiler.  Looking at the memory allocation graph is usually the key for spotting this routine, as it’s often “hidden” deep in call graph.  For example, while optimizing some of my scientific routines, I ran into a situation where I had a loop similar to: for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i]); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This loop was at a fairly high level in the call graph, and often could take many hours to complete, depending on the input data.  As such, any performance optimization we could achieve would be greatly appreciated by our users. After a fair bit of profiling, I noticed that a couple of function calls down the call graph (inside of ProcessElement), there was some code that effectively was doing: // Allocate some data required DataStructure* data = new DataStructure(num); // Call into a subroutine that passed around and manipulated this data highly CallSubroutine(data); // Read and use some values from here double values = data->Foo; // Cleanup delete data; // ... return bar; Normally, if “DataStructure” was a simple data type, I could just allocate it on the stack.  However, it’s constructor, internally, allocated it’s own memory using new, so this wouldn’t eliminate the problem.  In this case, however, I could change the call signatures to allow the pointer to the data structure to be passed into ProcessElement and through the call graph, allowing the inner routine to reuse the same “data” memory instead of allocating.  At the highest level, my code effectively changed to something like: DataStructure* data = new DataStructure(numberToProcess); for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i], data); } delete data; Granted, this dramatically reduced the maintainability of the code, so it wasn’t something I wanted to do unless there was a significant benefit.  In this case, after profiling the new version, I found that it increased the overall performance dramatically – my main test case went from 35 minutes runtime down to 21 minutes.  This was such a significant improvement, I felt it was worth the reduction in maintainability. In C and C++, it’s generally a good idea (for performance) to: Reduce the number of memory allocations as much as possible, Use fewer, larger memory allocations instead of many smaller ones, and Allocate as high up the call stack as possible, and reuse memory I’ve seen many people try to make similar optimizations in C# code.  For good or bad, this is typically not a good idea.  The garbage collector in .NET completely changes the rules here. In C#, reallocating memory in a loop is not always a bad idea.  In this scenario, for example, I may have been much better off leaving the original code alone.  The reason for this is the garbage collector.  The GC in .NET is incredibly effective, and leaving the allocation deep inside the call stack has some huge advantages.  First and foremost, it tends to make the code more maintainable – passing around object references tends to couple the methods together more than necessary, and overall increase the complexity of the code.  This is something that should be avoided unless there is a significant reason.  Second, (unlike C and C++) memory allocation of a single object in C# is normally cheap and fast.  Finally, and most critically, there is a large advantage to having short lived objects.  If you lift a variable out of the loop and reuse the memory, its much more likely that object will get promoted to Gen1 (or worse, Gen2).  This can cause expensive compaction operations to be required, and also lead to (at least temporary) memory fragmentation as well as more costly collections later. As such, I’ve found that it’s often (though not always) faster to leave memory allocations where you’d naturally place them – deep inside of the call graph, inside of the loops.  This causes the objects to stay very short lived, which in turn increases the efficiency of the garbage collector, and can dramatically improve the overall performance of the routine as a whole. In C#, I tend to: Keep variable declarations in the tightest scope possible Declare and allocate objects at usage While this tends to cause some of the same goals (reducing unnecessary allocations, etc), the goal here is a bit different – it’s about keeping the objects rooted for as little time as possible in order to (attempt) to keep them completely in Gen0, or worst case, Gen1.  It also has the huge advantage of keeping the code very maintainable – objects are used and “released” as soon as possible, which keeps the code very clean.  It does, however, often have the side effect of causing more allocations to occur, but keeping the objects rooted for a much shorter time. Now – nowhere here am I suggesting that these rules are hard, fast rules that are always true.  That being said, my time spent optimizing over the years encourages me to naturally write code that follows the above guidelines, then profile and adjust as necessary.  In my current project, however, I ran across one of those nasty little pitfalls that’s something to keep in mind – interop changes the rules. In this case, I was dealing with an API that, internally, used some COM objects.  In this case, these COM objects were leading to native allocations (most likely C++) occurring in a loop deep in my call graph.  Even though I was writing nice, clean managed code, the normal managed code rules for performance no longer apply.  After profiling to find the bottleneck in my code, I realized that my inner loop, a innocuous looking block of C# code, was effectively causing a set of native memory allocations in every iteration.  This required going back to a “native programming” mindset for optimization.  Lifting these variables and reusing them took a 1:10 routine down to 0:20 – again, a very worthwhile improvement. Overall, the lessons here are: Always profile if you suspect a performance problem – don’t assume any rule is correct, or any code is efficient just because it looks like it should be Remember to check memory allocations when profiling, not just CPU cycles Interop scenarios often cause managed code to act very differently than “normal” managed code. Native code can be hidden very cleverly inside of managed wrappers

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  • What's the difference between "Flash Drive" and "Flash Memory"?

    - by Clive D
    I have a problem with a Blu ray disk I bought. I talked to a Sony technician who advised me to plug a "USB Flash Memory Stick" into the Blu-ray player. Is this something specific? Is there a difference between the following two? "USB Flash Drive" "USB Flash Memory" When I go to Curry's or other sites that sell USB Sticks, they only talk about "USB Flash Drives". I've been in computing for many years and know the basics, but "memory" and "drive" are different things to me.

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  • How do I limit the size of my syslog?

    - by Wayne Werner
    I've got my mom's computer running Ubuntu 12.04 LTS. It's been working just fine but all of the sudden syslog has been filling up. And by filling up I mean I just deleted a /var/log/syslog that was 400GB in size. Yes - Gigabytes. While I'm sure there was some useful information in there, I'm not sure that 400GB is any kind of information to sift through. And what's really amazing about it is that it happened within a period of 8 hours - I had ran df around noon, and between then and now her drive filled up 30% (from just under 70% to 100%). What could be causing this and how could I fix it?`

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  • How can I set a time limit for a game?

    - by Haoda Fu
    I am learning the multi-threading and timer in C# now. But it seems I can't find a good solution. For example, I would like to see how many addition problems that I can solve within 1 min. I would like my program to have A digital clock to count for 60 seconds in the top of my Console. Print a math problem in the middle of my console wait for my input. When 60 seconds is done, stop the math problem challenges immediately (most of time, it is still waiting for my input, but we will stop it immediately). Count how many correct problems that I have solved. Two challenges of the program now. a) how can we make sure the print time and math problem do not mess up. b) how can we stop the math challenges part immediately after time is up

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  • Fatal error: Out of memory (allocated ...) (tried to allocate ... bytes) not due to memory_limit setting

    - by Lorenz Meyer
    Since a few days, I get the following error on my server: Fatal error: Out of memory (allocated 262144) (tried to allocate 393216 bytes) Usually this error is due to a memory consumption that is exceeding the configured memory_limit, but in my case there is no relation. The memory_limit is set to 128MB, and in this case, we not even reach 1MB. Also the server does not have a big load, in fact it is an intranet server, and there are just a few people conected to it. System: Windows Server 2003, 1Go RAM, only 600 MB used. Apache 2.2.4 PHP 5.2.3 This error is appearing randomly. The memory limit reached also is randomly between a few kB to a few MB. Sometimes restarting Apache is required to get rid of the error, sometimes it disapears itself. Restarting Apache or the entire server helps temporarily. Where could this problem come from ? How could I narrow down the error source ?

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  • TechEd 2014 Day 3

    - by John Paul Cook
    There is some confusion about durability of data stored in SQL Server in-memory tables, so some review of the concepts is appropriate. The in-memory option is enabled at the database level. Enabling it at the database level only gives you the option to specify the in-memory feature on a table by table basis. No existing tables or new tables will by default become in-memory tables when you enable the feature at the database level. If you choose to make a table an in-memory table, by default it is...(read more)

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  • How do I take some RAM and use it towards Dedicated video memory for my Nvidia graphics card?

    - by Noah Rainey
    I have a Nividia GeForce 6150SE nForce 430 graphics card (so it's quite old), it only gets 64MB of dedicated memory by default. I went into the bios and see if I can increase it, but it wouldn't let me. However, from the Nividia control panel I see I have up to 1071MB of total available graphics memory. I'm not sure what that means and I'm not sure how I can harness this memory and use some RAM for my graphics card. Can someone explain if this is possible and if so, how?

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  • How can I limit CD drive speed while on the live CD to avoid drive noise?

    - by iugamarian
    I sometimes disconect my harddisks for the weeks while only using the internet and I use the Ubuntu Live CD. But every time it needs something while in live desktop it accelerates and makes a lot of noise, also the acceleration takes too long. I want lower drive speed than acceleration lags, because acceleration lags stop me completly exactly when I need something. How can I lower the CD drive speed, say to maximum 16x, without restarting? I can't restart because I only use the CD drive, no harddisks, no flash disks, no network disks. Edit: No USB drives. Setcd does not work for the live session.

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  • TechEd 2014 Day 3

    - by John Paul Cook
    There is some confusion about durability of data stored in SQL Server in-memory tables, so some review of the concepts is appropriate. The in-memory option is enabled at the database level. Enabling it at the database level only gives you the option to specify the in-memory feature on a table by table basis. No existing tables or new tables will by default become in-memory tables when you enable the feature at the database level. If you choose to make a table an in-memory table, by default it is...(read more)

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  • How to limit concurrent file access on a Samba share?

    - by JPbuntu
    I have a Ubuntu 12.04 file server running Samba. There are 6 windows machines that access the server, as well as two people that will occasionally access files remotely. The problem that I am having is that the CAD/CAM software we are using doesn't seem to request file locks, meaning if two people open a file at the same time, the first person to close the file will get their changes overwritten if the second person saves the file. I tried changing the smb.conf to strict locking = yes but this doesn't seem to have any effect. File locking with excel seems to work fine, so I know that Samba is using the file locks...if they were put on the file in the first place. Is there a way (either in Samba or Ubuntu) to only allow one user to have a file open at a time? If not does anyone have any suggestions for managing a problem like this?

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  • How long does it take in practice to warm up large in-memory databases?

    - by Sim
    Companies such as Peak Hosting are offering 64 core machines with 512Gb RAM for $2K/month. This is a very interesting choice for in-memory databases such as Memcached/Redis as well as databases whose performance degrades rapidly when the data & indexes don't fit in RAM, such as MongoDB. My main concern with monster machines such as these is the time it takes to warm up an in-memory database. In my experience, theoretical metrics, e.g., that SATA can load 100Mb/sec, fall short of what happens in practice. Even at that rate, 100Mb/sec means that loading up 512Gb RAM machine from SATA disks can take over 1 1/2 hours (!). I am looking for real-world reports of warm-up times for machines with very large memory. Please, share details of the software on the machine, data size, storage configuration, e.g., SATA or SSD, network, hosting/cloud provider, if relevant, etc.

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  • Why does using 2 memory sticks cause my computer to crash?

    - by hi
    My computer randomly crashes when playing games, but if I remove one memory stick (it does not matter which one I remove), it does not crash anymore. Memory tests do not find errors, I just put in a new power supply (650W), I only have 1 graphics card, so why is this happening? BTW, they are the same memory, same vendor same specs, everything I bought it together (2x2GB) My motherboard is a Asus P5Q Pro, so it supports both dual channel and more than 4gb. Switching slots does nothing, as long as I don't use more than 1 I'm fine.

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  • Why OS X use swap when there is lots of "inactive memory"?

    - by Balchev
    I am using OS X from few months (Lion and now Mountain Lion). I have 8 GB on my mini and almost daily now it get close to that. On Windows 7 machine with 8 GB I never had that kind of problem. Anyway, I read over the net, that the inactive memory is app cache of the programs that are recently closed and can be used for faster reopening.And this inactive memory can be released to a new app if needed. It is not released. Instead OS X starts swapping. So my question is why OS X use swap when there is lots of "inactive memory"? Here a screen that shows what I mean: I really hope there is a away to make OS X to use those 2.69 GB before start swapping.I really do.

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  • I asked this yesterday, after the input given I'm still having trouble implementing..

    - by Josh
    I'm not sure how to fix this or what I did wrong, but whenever I enter in a value it just closes out the run prompt. So, seems I do have a problem somewhere in my coding. Whenever I run the program and input a variable, it always returns the same answer.."The content at location 76 is 0." On that note, someone told me that "I don't know, but I suspect that Program A incorrectly has a fixed address being branched to on instructions 10 and 11." - mctylr but I'm not sure how to fix that.. I'm trying to figure out how to incorporate this idea from R Samuel Klatchko.. I'm still not sure what I'm missing but I can't get it to work.. const int OP_LOAD = 3; const int OP_STORE = 4; const int OP_ADD = 5; ... const int OP_LOCATION_MULTIPLIER = 100; mem[0] = OP_LOAD * OP_LOCATION_MULTIPLIER + ...; mem[1] = OP_ADD * OP_LOCATION_MULTIPLIER + ...; operand = memory[ j ] % OP_LOCATION_MULTIPLIER; operation = memory[ j ] / OP_LOCATION_MULTIPLIER; I'm new to programming, I'm not the best, so I'm going for simplicity. Also this is an SML program. Anyway, this IS a homework assignment and I'm wanting a good grade on this. So I was looking for input and making sure this program will do what I'm hoping they are looking for. Anyway, here are the instructions: Write SML (Simpletron Machine language) programs to accomplish each of the following task: A) Use a sentinel-controlled loop to read positive number s and compute and print their sum. Terminate input when a neg number is entered. B) Use a counter-controlled loop to read seven numbers, some positive and some negative, and compute + print the avg. C) Read a series of numbers, and determine and print the largest number. The first number read indicates how many numbers should be processed. Without further a due, here is my program. All together. int main() { const int READ = 10; const int WRITE = 11; const int LOAD = 20; const int STORE = 21; const int ADD = 30; const int SUBTRACT = 31; const int DIVIDE = 32; const int MULTIPLY = 33; const int BRANCH = 40; const int BRANCHNEG = 41; const int BRANCHZERO = 41; const int HALT = 43; int mem[100] = {0}; //Making it 100, since simpletron contains a 100 word mem. int operation; //taking the rest of these variables straight out of the book seeing as how they were italisized. int operand; int accum = 0; // the special register is starting at 0 int j; // This is for part a, it will take in positive variables in a sent-controlled loop and compute + print their sum. Variables from example in text. memory [0] = 1010; memory [01] = 2009; memory [02] = 3008; memory [03] = 2109; memory [04] = 1109; memory [05] = 4300; memory [06] = 1009; j = 0; //Makes the variable j start at 0. while ( true ) { operand = memory[ j ]%100; // Finds the op codes from the limit on the memory (100) operation = memory[ j ]/100; //using a switch loop to set up the loops for the cases switch ( operation ){ case 10: //reads a variable into a word from loc. Enter in -1 to exit cout <<"\n Input a positive variable: "; cin >> memory[ operand ]; break; case 11: // takes a word from location cout << "\n\nThe content at location " << operand << "is " << memory[operand]; break; case 20:// loads accum = memory[ operand ]; break; case 21: //stores memory[ operand ] = accum; break; case 30: //adds accum += mem[operand]; break; case 31: // subtracts accum-= memory[ operand ]; break; case 32: //divides accum /=(memory[ operand ]); break; case 33: // multiplies accum*= memory [ operand ]; break; case 40: // Branches to location j = -1; break; case 41: //branches if acc. is < 0 if (accum < 0) j = 5; break; case 42: //branches if acc = 0 if (accum == 0) j = 5; break; case 43: // Program ends exit(0); break; } j++; } return 0; }

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  • How to limit speed with BMW JSDK on 116i?

    - by lexicore
    I'm experimenting with the BMW Java SDK on the new BMW 116i Innovation Package. Basic things like turning the lights on and off, starting and stopping the motor work fine. What I'm trying to do now is that to write a carlet which would limit the speed to the maximum configured in the driver profile. Driver identity will be detected as usual via RFID reader. My problem is that though I can read the speed from the tachometer, I can't really limit the speed. Here's what I've got working so far: public class SpeenControllingCarlet extends GenericCarlet { public void start(final VehicleModel model) throws CarletException { RfidReader rfidReader = (RfidReader) model .getDevice(Devices.DRIVER_RFID_READER); Rfid rfid = rfidReader.getRfid(); DriverProfile driverProfile = model.getDriverProfileRegistry() .getDriverProfile(rfid.toString()); if (driverProfile == null) { return; } final Double maxAllowedSpeed = Double.valueOf(driverProfile .getCustomAttribute("maxAllowedSpeed", "190")); Tachometer tachometer = (Tachometer) mode.getDevice(Devices.TACHOMETER); tachometer.addSpeedListener(new SpeedListener() { public void onSpeedChanged(SpeedChangedEvent speedChangedEvent) { if (speedChangedEvent.getCurrentSpeed() > maxAllowedSpeed) { Horn horn = (Horn) mode.getDevice(Devices.HORN); horn.beep(440, 2000); } } }); } } This will just beep for two seconds if the driver goes faster than the driver profile allows. My question is - is there a possibility to actually limit the speed (not just silly beeping)?

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