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  • A Good Final High School AP Computer Science Programming Project?

    - by user297663
    Hey guys this question might seem very specific but I am in need of some ideas for a project to do for my last month or so in my AP Computer Science class. I've been looking at some college final ideas and a lot of them just seem plain boring. At first I thought about writing a IRC client in JAVA but I wouldn't really be learning anything "new" that would help me in the future. Then I thought about doing IPhone/touch apps (I don't have an adroid phone and I can easily get my hands on an itouch) but I would need ideas to make apps for that. I want to do something that is going to feel trivial and need some explanation but will also help me in the long run learning new concepts in computer science. If you guys could help out I would greatly appreciate it. I really only have a month to do this project so try to keep the project inside of that range. Also, I don't mind learning new languages. Thanks :)

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  • Does normalization really hurt performance in high traffic sites?

    - by Luke101
    I am designing a database and I would like to normalize the database. I one query I will joining about 30-40 tables. Will this hurt the website performance if it ever becomes extremely popular? This will be the main query and it will be getting called 50% of the time. The other queries I will be joining about 2 tables. I have a choice right now to normalize or not to normalize but if the normalization becomes a problem in the future i may have to rewrite 40% of the software and it may take me a long time. Does normalization really hurt in this case? Should I denormalize now while I have the time?

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  • Is there a performance difference between Windows 7 on SSD installed from scratch versus it using a recent ghost/clone drive image from a harddisk?

    - by therobyouknow
    I'm planning to upgrade a notebook PC to a Solid-State Flash Drive (SSD) soon. I want to use the notebook before that and am considering installing Windows 7 on the hard disk (spinning variety, 5400rpm) before I get the SSD. To save time I am wondering if I can ghost/clone the installation of Windows 7 from the hard drive and put on the SSD. Would the performance of this clone from the harddisk onto the SSD be different from starting again and reinstalling Windows 7 from scratch on the SSD? (Windows 7 32bit professional)

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  • Dual boot, win7 & ubuntu. Gparted, resize not move. Performance?

    - by data_jepp
    I installed dual boot on a computer that already had win7 installed. The question here is about gparted ability to move partitions. I made place for ubuntu in the computers "Data" partition, by resizing it. But I canceled the "move" action. Was that incredibly stupid, or is this care? Maybe performance is affected. Can this effect the hd's lifespan? The computer is UL30A.

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  • How close can I get C# to the performance of C++ for small intensive tasks?

    - by SLC
    I was thinking about the speed difference of C++ to C# being mostly about C# compiling to byte-code that is taken in by the JIT compiler (is that correct?) and all the checks C# does. I notice that it is possible to turn a lot of these functions off, both in the compile options, and possibly through using the unsafe keyword as unsafe code is not verifiable by the common language runtime. Therefore if you were to write a simple console application in both languages, that flipped an imaginary coin an infinite number of times and displayed the results to the screen every 10,000 or so iterations, how much speed difference would there be? I chose this because it's a very simple program. I'd like to test this but I don't know C++ or have the tools to compile it. This is my C# version though: static void Main(string[] args) { unsafe { Random rnd = new Random(); int heads = 0, tails = 0; while (true) { if (rnd.NextDouble() > 0.5) heads++; else tails++; if ((heads + tails) % 1000000 == 0) Console.WriteLine("Heads: {0} Tails: {1}", heads, tails); } } } Is the difference enough to warrant deliberately compiling sections of code "unsafe" or into DLLs that do not have some of the compile options like overflow checking enabled? Or does it go the other way, where it would be beneficial to compile sections in C++? I'm sure interop speed comes into play too then. To avoid subjectivity, I reiterate the specific parts of this question as: Does C# have a performance boost from using unsafe code? Do the compile options such as disabling overflow checking boost performance, and do they affect unsafe code? Would the program above be faster in C++ or negligably different? Is it worth compiling long intensive number-crunching tasks in a language such as C++ or using /unsafe for a bonus? Less subjectively, could I complete an intensive operation faster by doing this?

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  • How to increase the performance of a loop which runs for every 'n' minutes.

    - by GustlyWind
    Hi Giving small background to my requirement and what i had accomplished so far: There are 18 Scheduler tasks run at regular intervals (least being 30 mins) takes input of nearly 5000 eligible employees run into a static method for iteration and generates a mail content for that employee and mails. An average task takes about 9 min multiplied by 18 will be roughly 162 mins meanwhile there would be next tasks which will be in queue (I assume). So my plan is something like the below loop try { // Handle Arraylist of alerts eligible employees Iterator employee = empIDs.iterator(); while (employee.hasNext()) { ScheduledImplementation.getInstance().sendAlertInfoToEmpForGivenAlertType((Long)employee.next(), configType,schedType); } } catch (Exception vEx) { _log.error("Exception Caught During sending " + configType + " messages:" + configType, vEx); } Since I know how many employees would come to my method I will divide the while loop into two and perform simultaneous operations on two or three employees at a time. Is this possible. Or is there any other ways I can improve the performance. Some of the things I had implemented so far 1.Wherever possible made methods static and variables too Didn't bother to catch exceptions and send back because these are background tasks. (And I assume this improves performance) Get the DB values in one query instead of multiple hits. If am successful in optimizing the while loop I think i can save couple of mins. Thanks

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  • Is having a lot of DOM elements bad for performance?

    - by rFactor
    Hi, I am making a button that looks like this: <!-- Container --> <div> <!-- Top --> <div> <div></div> <div></div> <div></div> </div> <!-- Middle --> <div> <div></div> <div></div> <div></div> </div> <!-- Bottom --> <div> <div></div> <div></div> <div></div> </div> </div> It has many elements, because I want it to be skinnable without limiting the skinners abilities. However, I am concerned about performance. Does having a lot of DOM elements refrect bad performance? Obviously there will always be an impact, but how great is that?

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  • Performance of a get unique elements/group by operation on an IEnumerable<T>.

    - by tolism7
    I was wondering how could I improve the performance of the following code: public class MyObject { public int Year { get; set; } } //In my case I have 30000 IEnumerable<MyObject> data = MethodThatReturnsManyMyObjects(); var groupedByYear = data.GroupBy(x => x.Year); //Here is the where it takes around 5 seconds foreach (var group in groupedByYear) //do something here. The idea is to get a set of objects with unique year values. In my scenario there are only 6 years included in the 30000 items in the list so the foreach loop will be executed 6 times only. So we have many items needing to be grouped in a few groups. Using the .Distinct() with an explicit IEqualityComparer would be an alternative but somehow I feel that it wont make any difference. I can understand if 30000 items is too much and that i should be happy with the 5 seconds I get, but I was wondering if the above can be imporved performance wise. Thanks.

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  • Rewriting jQuery to plain old javascript - are the performance gains worth it?

    - by Swader
    Since jQuery is an incredibly easy and banal library, I've developed a rather complex project fairly quickly with it. The entire interface is jQuery based, and memory is cleaned regularly to maintain optimum performance. Everything works very well in Firefox, and exceptionally so in Chrome (other browsers are of no concern for me as this is not a commercial or publicly available product). What I'm wondering now is - since pure plain old javascript is really not a complicated language to master, would it be performance enhancing to rewrite the whole thing in plain old JS, and if so, how much of a boost would you expect to get from it? If the answers prove positive enough, I'll go ahead and do it, run a benchmark and report back with the precise findings. Cheers Edit: Thanks guys, valuable insight. The purpose was not to "re-invent the wheel" - it was just for experience and personal improvement. Just because something exists, doesn't mean you shouldn't explore it into greater detail, know how it works or try to recreate it. This is the same reason I seldom use frameworks, I would much rather use my own code and iron it out and gain massive experience doing it, than start off by using someone else's code, regardless of how ironed out it is. Anyway, won't be doing it, thanks for saving me the effort :)

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  • MySQL - What is wrong with this query or my database? Terrible performance.

    - by Moss
    SELECT * from `employees` a LEFT JOIN (SELECT phone1 p1, count(*) c, FROM `employees` GROUP BY phone1) b ON a.phone1 = b.p1; I'm not sure if it is this query in particular that has the problem. I have been getting terrible performance in general with this database. The table in question has 120,000 rows. I have tried this particular query remotely and locally with the MyISAM and InnoDB engines, with different types of joins, and with and without an index on phone1. I can get this to complete in about 4 minutes on a 10,000 row table successfully but performance drops exponentially with larger tables. Remotely it will lose connection to the server and locally it brings my system to its knees and seems to go on forever. This query is only a smaller step I was trying to do when a larger query couldn't complete. Maybe I should explain the whole scenario. I have one big flat ugly table that lists a bunch of people and their contact info and the info of the companies they work for. I'm trying to normalize the database and intelligently determine which phone numbers apply to individual people and which apply to an office location. My reasoning is that if a phone number occurs multiple times and the number of occurrence equals the number of times that the street address it is attached to occurs then it must be an office number. So the first step is to count each phone number grouping by phone number. Normally if you just use COUNT()...GROUP BY it will only list the first record it finds in that group so I figured I have to join the full table to the count table where the phone number matches. This does work but as I said I can't successfully complete it on any table much larger than 10,000 rows. This seems pathetic and this doesn't seem like a crazy query to do. Is there a better way to achieve what I want or do I have to break my large table into 12 pieces or is there something wrong with the table or db?

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  • HD video editing system with Truecrypt

    - by Rob
    I'm looking to do hi-def video editing and transcoding on an unencrypted standard partition, with Truecrypt on the system partition for sensitive data. I'm aiming to keep certain data private but still have performance where needed. Goals: Maximum, unimpacted, performance possible for hi-def video editing, encryption of video not required Encrypt system partition, using Truecrypt, for web/email privacy, etc. in the event of loss In other words I want to selectively encrypt the hard drive - i.e. make the system partition encrypted but not impact the original maximum performance that would be available to me for hi-def/HD video editing. The thinking is to use an unencrypted partition for the video and set up video applications to point at that. Assuming that they would use that partition only for their workspace and not the encrypted system partition, then I should expect to not get any performance hit. Would I be correct? I guess it might depend on the application, if that app is hard-wired to use the system partition always for temporary storage during editing and transcoding, or if it has to be installed on the C: system partition always. So some real data on how various apps behave in the respect would be useful, e.g. Adobe, Cyberlink, Nero etc. etc. I have a Intel i7 Quad-core (8 threads) 1.6Ghz (up to 2.8Ghz turbo-boost) 4Gb, 7200rpm SATA, nvidia HP laptop. I've read the excellent posting about the general performance impact of truecrypt but the benchmarks weren't specific enough for my needs where I'm dealing with HD-video and using a non-encrypted partition to maintain max performance.

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  • Why is my rsync so slow?

    - by iblue
    My Laptop and my workstation are both connected to a Gigabit Switch. Both are running Linux. But when I copy files with rsync, it performs badly. I get about 22 MB/s. Shouldn't I theoretically get about 125 MB/s? What is the limiting factor here? EDIT: I conducted some experiments. Write performance on the laptop The laptop has a xfs filesystem with full disk encryption. It uses aes-cbc-essiv:sha256 cipher mode with 256 bits key length. Disk write performance is 58.8 MB/s. iblue@nerdpol:~$ LANG=C dd if=/dev/zero of=test.img bs=1M count=1024 1073741824 Bytes (1.1 GB) copied, 18.2735 s, 58.8 MB/s Read performance on the workstation The files I copied are on a software RAID-5 over 5 HDDs. On top of the raid is a lvm. The volume itself is encrypted with the same cipher. The workstation has a FX-8150 cpu that has a native AES-NI instruction set which speeds up encryption. Disk read performance is 256 MB/s (cache was cold). iblue@raven:/mnt/bytemachine/imgs$ dd if=backup-1333796266.tar.bz2 of=/dev/null bs=1M 10213172008 bytes (10 GB) copied, 39.8882 s, 256 MB/s Network performance I ran iperf between the two clients. Network performance is 939 Mbit/s iblue@raven $ iperf -c 94.135.XXX ------------------------------------------------------------ Client connecting to 94.135.XXX, TCP port 5001 TCP window size: 23.2 KByte (default) ------------------------------------------------------------ [ 3] local 94.135.XXX port 59385 connected with 94.135.YYY port 5001 [ ID] Interval Transfer Bandwidth [ 3] 0.0-10.0 sec 1.09 GBytes 939 Mbits/sec

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  • Very high CPU and low RAM usage - is it possible to place some of swap some of the CPU usage to the RAM (with CloudLinux LVE Manager installed)?

    - by Chriswede
    I had to install CloudLinux so that I could somewhat controle the CPU ussage and more importantly the Concurrent-Connections the Websites use. But as you can see the Server load is way to high and thats why some sites take up to 10 sec. to load! Server load 22.46 (8 CPUs) (!) Memory Used 36.32% (2,959,188 of 8,146,632) (ok) Swap Used 0.01% (132 of 2,104,504) (ok) Server: 8 x Intel(R) Xeon(R) CPU E31230 @ 3.20GHz Memory: 8143680k/9437184k available (2621k kernel code, 234872k reserved, 1403k data, 244k init) Linux Yesterday: Total of 214,514 Page-views (Awstat) Now my question: Can I shift some of the CPU usage to the RAM? Or what else could I do to make the sites run faster (websites are dynamic - so SQL heavy) Thanks top - 06:10:14 up 29 days, 20:37, 1 user, load average: 11.16, 13.19, 12.81 Tasks: 526 total, 1 running, 524 sleeping, 0 stopped, 1 zombie Cpu(s): 42.9%us, 21.4%sy, 0.0%ni, 33.7%id, 1.9%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 8146632k total, 7427632k used, 719000k free, 131020k buffers Swap: 2104504k total, 132k used, 2104372k free, 4506644k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 318421 mysql 15 0 1315m 754m 4964 S 474.9 9.5 95300:17 mysqld 6928 root 10 -5 0 0 0 S 2.0 0.0 90:42.85 kondemand/3 476047 headus 17 0 172m 19m 10m S 1.7 0.2 0:00.05 php 476055 headus 18 0 172m 18m 9.9m S 1.7 0.2 0:00.05 php 476056 headus 15 0 172m 19m 10m S 1.7 0.2 0:00.05 php 476061 headus 18 0 172m 19m 10m S 1.7 0.2 0:00.05 php 6930 root 10 -5 0 0 0 S 1.3 0.0 161:48.12 kondemand/5 6931 root 10 -5 0 0 0 S 1.3 0.0 193:11.74 kondemand/6 476049 headus 17 0 172m 19m 10m S 1.3 0.2 0:00.04 php 476050 headus 15 0 172m 18m 9.9m S 1.3 0.2 0:00.04 php 476057 headus 17 0 172m 18m 9.9m S 1.3 0.2 0:00.04 php 6926 root 10 -5 0 0 0 S 1.0 0.0 90:13.88 kondemand/1 6932 root 10 -5 0 0 0 S 1.0 0.0 247:47.50 kondemand/7 476064 worldof 18 0 172m 19m 10m S 1.0 0.2 0:00.03 php 6927 root 10 -5 0 0 0 S 0.7 0.0 93:52.80 kondemand/2 6929 root 10 -5 0 0 0 S 0.3 0.0 161:54.38 kondemand/4 8459 root 15 0 103m 5576 1268 S 0.3 0.1 54:45.39 lvest

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  • OAM OVD integration - Error Encounterd while performance test "LDAP response read timed out, timeout used:2000ms"

    - by siddhartha_sinha
    While working on OAM OVD integration for one of my client, I have been involved in the performance test of the products wherein I encountered OAM authentication failures while talking to OVD during heavy load. OAM logs revealed the following: oracle.security.am.common.policy.common.response.ResponseException: oracle.security.am.engines.common.identity.provider.exceptions.IdentityProviderException: OAMSSA-20012: Exception in getting user attributes for user : dummy_user1, idstore MyIdentityStore with exception javax.naming.NamingException: LDAP response read timed out, timeout used:2000ms.; remaining name 'ou=people,dc=oracle,dc=com' at oracle.security.am.common.policy.common.response.IdentityValueProvider.getUserAttribute(IdentityValueProvider.java:271) ... During the authentication and authorization process, OAM complains that the LDAP repository is taking too long to return user attributes.The default value is 2 seconds as can be seen from the exception, "2000ms". While troubleshooting the issue, it was found that we can increase the ldap read timeout in oam-config.xml.  For reference, the attribute to add in the oam-config.xml file is: <Setting Name="LdapReadTimeout" Type="xsd:string">2000</Setting> However it is not recommended to increase the time out unless it is absolutely necessary and ensure that back-end directory servers are working fine. Rather I took the path of tuning OVD in the following manner: 1) Navigate to ORACLE_INSTANCE/config/OPMN/opmn folder and edit opmn.xml. Search for <data id="java-options" ………> and edit the contents of the file with the highlighted items: <category id="start-options"><data id="java-bin" value="$ORACLE_HOME/jdk/bin/java"/><data id="java-options" value="-server -Xms1024m -Xmx1024m -Dvde.soTimeoutBackend=0 -Didm.oracle.home=$ORACLE_HOME -Dcommon.components.home=$ORACLE_HOME/../oracle_common -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:/opt/bea/Middleware/asinst_1/diagnostics/logs/OVD/ovd1/ovdGClog.log -XX:+UseConcMarkSweepGC -Doracle.security.jps.config=$ORACLE_INSTANCE/config/JPS/jps-config-jse.xml"/><data id="java-classpath" value="$ORACLE_HOME/ovd/jlib/vde.jar$:$ORACLE_HOME/jdbc/lib/ojdbc6.jar"/></category></module-data><stop timeout="120"/><ping interval="60"/></process-type> When the system is busy, a ping from the Oracle Process Manager and Notification Server (OPMN) to Oracle Virtual Directory may fail. As a result, OPMN will restart Oracle Virtual Directory after 20 seconds (the default ping interval). To avoid this, consider increasing the ping interval to 60 seconds or more. 2) Navigate to ORACLE_INSTANCE/config/OVD/ovd1 folder.Open listeners.os_xml file and perform the following changes: · Search for <ldap id=”Ldap Endpoint”…….> and point the cursor to that line. · Change threads count to 200. · Change anonymous bind to Deny. · Change workQueueCapacity to 8096. Add a new parameter <useNIO> and set its value to false viz: <useNIO>false</useNio> Snippet: <ldap version="8" id="LDAP Endpoint"> ....... .......  <socketOptions><backlog>128</backlog>         <reuseAddress>false</reuseAddress>         <keepAlive>false</keepAlive>         <tcpNoDelay>true</tcpNoDelay>         <readTimeout>0</readTimeout>      </socketOptions> <useNIO>false</useNIO></ldap> Restart OVD server. For more information on OVD tuneup refer to http://docs.oracle.com/cd/E25054_01/core.1111/e10108/ovd.htm. Please Note: There were few patches released from OAM side for performance tune-up as well. Will provide the updates shortly !!!

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  • GLSL Shader Texture Performance

    - by Austin
    I currently have a project that renders OpenGL video using a vertex and fragment shader. The shaders work fine as-is, but in trying to add in texturing, I am running into performance issues and can't figure out why. Before adding texturing, my program ran just fine and loaded my CPU between 0%-4%. When adding texturing (specifically textures AND color -- noted by comment below), my CPU is 100% loaded. The only code I have added is the relevant texturing code to the shader, and the "glBindTexture()" calls to the rendering code. Here are my shaders and relevant rending code. Vertex Shader: #version 150 uniform mat4 mvMatrix; uniform mat4 mvpMatrix; uniform mat3 normalMatrix; uniform vec4 lightPosition; uniform float diffuseValue; layout(location = 0) in vec3 vertex; layout(location = 1) in vec3 color; layout(location = 2) in vec3 normal; layout(location = 3) in vec2 texCoord; smooth out VertData { vec3 color; vec3 normal; vec3 toLight; float diffuseValue; vec2 texCoord; } VertOut; void main(void) { gl_Position = mvpMatrix * vec4(vertex, 1.0); VertOut.normal = normalize(normalMatrix * normal); VertOut.toLight = normalize(vec3(mvMatrix * lightPosition - gl_Position)); VertOut.color = color; VertOut.diffuseValue = diffuseValue; VertOut.texCoord = texCoord; } Fragment Shader: #version 150 smooth in VertData { vec3 color; vec3 normal; vec3 toLight; float diffuseValue; vec2 texCoord; } VertIn; uniform sampler2D tex; layout(location = 0) out vec3 colorOut; void main(void) { float diffuseComp = max( dot(normalize(VertIn.normal), normalize(VertIn.toLight)) ), 0.0); vec4 color = texture2D(tex, VertIn.texCoord); colorOut = color.rgb * diffuseComp * VertIn.diffuseValue + color.rgb * (1 - VertIn.diffuseValue); // FOLLOWING LINE CAUSES PERFORMANCE ISSUES colorOut *= VertIn.color; } Relevant Rendering Code: // 3 textures have been successfully pre-loaded, and can be used // texture[0] is a 1x1 white texture to effectively turn off texturing glUseProgram(program); // Draw squares glBindTexture(GL_TEXTURE_2D, texture[1]); // Set attributes, uniforms, etc glDrawArrays(GL_QUADS, 0, 6*4); // Draw triangles glBindTexture(GL_TEXTURE_2D, texture[0]); // Set attributes, uniforms, etc glDrawArrays(GL_TRIANGLES, 0, 3*4); // Draw reference planes glBindTexture(GL_TEXTURE_2D, texture[0]); // Set attributes, uniforms, etc glDrawArrays(GL_LINES, 0, 4*81*2); // Draw terrain glBindTexture(GL_TEXTURE_2D, texture[2]); // Set attributes, uniforms, etc glDrawArrays(GL_TRIANGLES, 0, 501*501*6); // Release glBindTexture(GL_TEXTURE_2D, 0); glUseProgram(0); Any help is greatly appreciated!

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  • Which version management design methodology to be used in a Dependent System nodes?

    - by actiononmail
    This is my first question so please indicate if my question is too vague and not understandable. My question is more related to High Level Design. We have a system (specifically an ATCA Chassis) configured in a Star Topology, having Master Node (MN) and other sub-ordinate nodes(SN). All nodes are connected via Ethernet and shall run on Linux OS with other proprietary applications. I have to build a recovery Framework Design so that any software entity, whether its Linux, Ramdisk or application can be rollback to previous good versions if something bad happens. Thus I think of maintaining a State Version Matrix over MN, where each State(1,2....n) represents Good Kernel, Ramdisk and application versions for each SN. It may happen that one SN version can dependent on other SN's version. Please see following diagram:- So I am in dilemma whether to use Package Management Methodology used by Debian Distributions (Like Ubuntu) or GIT repository methodology; in order to do a Rollback to previous good versions on either one SN or on all the dependent SNs. The method should also be easier for upgrading SNs along with MNs. Some of the features which I am trying to achieve:- 1) Upgrade of even single software entity is achievable without hindering others. 2) Dependency checks must be done before applying rollback or upgrade on each of the SN 3) User Prompt should be given in case dependency fails.If User still go for rollback, all the SNs should get notification to rollback there own releases (if required). 4) The binaries should be distributed on SNs accordingly so that recovery process is faster; rather fetching every time from MN. 5) Release Patches from developer for bug fixes, feature enhancement can be applied on running system. 6) Each version can be easily tracked and distinguishable. Thanks

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  • Using Hidden Markov Model for designing AI mp3 player

    - by Casper Slynge
    Hey guys. Im working on an assignment, where I want to design an AI for a mp3 player. The AI must be trained and designed with the use of a HMM method. The mp3 player shall have the functionality of adapting to its user, by analyzing incoming biological sensor data, and from this data the mp3 player will choose a genre for the next song. Given in the assignment is 14 samples of data: One sample consist of Heart Rate, Respiration, Skin Conductivity, Activity and finally the output genre. Below is the 14 samples of data, just for you to get an impression of what im talking about. Sample HR RSP SC Activity Genre S1 Medium Low High Low Rock S2 High Low Medium High Rock S3 High High Medium Low Classic S4 High Medium Low Medium Classic S5 Medium Medium Low Low Classic S6 Medium Low High High Rock S7 Medium High Medium Low Classic S8 High Medium High Low Rock S9 High High Low Low Classic S10 Medium Medium Medium Low Classic S11 Medium Medium High High Rock S12 Low Medium Medium High Classic S13 Medium High Low Low Classic S14 High Low Medium High Rock My time of work regarding HMM is quite low, so my question to you is if I got the right angle on the assignment. I have three different states for each sensor: Low, Medium, High. Two observations/output symbols: Rock, Classic In my own opinion I see my start probabilities as the weightened factors for either a Low, Medium or High state in the Heart Rate. So the ideal solution for the AI is that it will learn these 14 sets of samples. And when a users sensor input is received, the AI will compare the combination of states for all four sensors, with the already memorized samples. If there exist a matching combination, the AI will choose the genre, and if not it will choose a genre according to the weightened transition probabilities, while simultaniously updating the transition probabilities with the new data. Is this a right approach to take, or am I missing something ? Is there another way to determine the output probability (read about Maximum likelihood estimation by EM, but dont understand the concept)? Best regards, Casper

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  • one two-directed tcp socket OR two one-directed? (linux, high volume, low latency)

    - by osgx
    Hello I need to send (interchange) a high volume of data periodically with the lowest possible latency between 2 machines. The network is rather fast (e.g. 1Gbit or even 2G+). Os is linux. Is it be faster with using 1 tcp socket (for send and recv) or with using 2 uni-directed tcp sockets? The test for this task is very like NetPIPE network benchmark - measure latency and bandwidth for sizes from 2^1 up to 2^13 bytes, each size sent and received 3 times at least (in teal task the number of sends is greater. both processes will be sending and receiving, like ping-pong maybe). The benefit of 2 uni-directed connections come from linux: http://lxr.linux.no/linux+v2.6.18/net/ipv4/tcp_input.c#L3847 3847/* 3848 * TCP receive function for the ESTABLISHED state. 3849 * 3850 * It is split into a fast path and a slow path. The fast path is 3851 * disabled when: ... 3859 * - Data is sent in both directions. Fast path only supports pure senders 3860 * or pure receivers (this means either the sequence number or the ack 3861 * value must stay constant) ... 3863 * 3864 * When these conditions are not satisfied it drops into a standard 3865 * receive procedure patterned after RFC793 to handle all cases. 3866 * The first three cases are guaranteed by proper pred_flags setting, 3867 * the rest is checked inline. Fast processing is turned on in 3868 * tcp_data_queue when everything is OK. All other conditions for disabling fast path is false. And only not-unidirected socket stops kernel from fastpath in receive

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  • one two-directed tcp socket of two one-directed? (linux, high volume, low latency)

    - by osgx
    Hello I need to send (interchange) a high volume of data periodically with the lowest possible latency between 2 machines. The network is rather fast (e.g. 1Gbit or even 2G+). Os is linux. Is it be faster with using 1 tcp socket (for send and recv) or with using 2 uni-directed tcp sockets? The test for this task is very like NetPIPE network benchmark - measure latency and bandwidth for sizes from 2^1 up to 2^13 bytes, each size sent and received 3 times at least (in teal task the number of sends is greater. both processes will be sending and receiving, like ping-pong maybe). The benefit of 2 uni-directed connections come from linux: http://lxr.linux.no/linux+v2.6.18/net/ipv4/tcp_input.c#L3847 3847/* 3848 * TCP receive function for the ESTABLISHED state. 3849 * 3850 * It is split into a fast path and a slow path. The fast path is 3851 * disabled when: ... 3859 * - Data is sent in both directions. Fast path only supports pure senders 3860 * or pure receivers (this means either the sequence number or the ack 3861 * value must stay constant) ... 3863 * 3864 * When these conditions are not satisfied it drops into a standard 3865 * receive procedure patterned after RFC793 to handle all cases. 3866 * The first three cases are guaranteed by proper pred_flags setting, 3867 * the rest is checked inline. Fast processing is turned on in 3868 * tcp_data_queue when everything is OK. All other conditions for disabling fast path is false. And only not-unidirected socket stops kernel from fastpath in receive

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  • Performance Comparison of Shell Scripts vs high level interpreted langs (C#/Java/etc.)

    - by dferraro
    Hi all, First - This is not meant to be a 'which is better, ignorant nonionic war thread'... But rather, I generally need help in making an architecture decision / argument to put forward to my boss. Skipping the details - I simply just would love to know and find the results of anyone who has done some performance comparisons of Shell vs [Insert General Purpose Programming Language (interpreted) here), such as C# or Java... Surprisingly, I have spent some time on Google on searching here to not find any of this data. Has anyone ever done these comparisons, in different use-cases; hitting a database like in a XYX # of loops doing different types of SQL (Oracle pref, but MSSQL would do) queries such as any of the CRUD ops - and also not hitting database and just regular 50k loop type comparison doing different types of calculations, and things of that nature? In particular - for right now, I need to a comparison of hitting an Oracle DB from a shell script vs, lets say C# (again, any GPPL thats interpreted would be fine, even the higher level ones like Python). But I also need to know about standard programming calculations / instructions/etc... Before you ask 'why not just write a quick test yourself? The answer is: I've been a Windows developer my whole life/career and have very limited knowledge of Shell scripting - not to mention *nix as a whole.... So asking the question on here from the more experienced guys would be grealty beneficial, not to mention time saving as we are in near perputual deadline crunch as it is ;). Thanks so much in advance,

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  • MySQL – Scalability on Amazon RDS: Scale out to multiple RDS instances

    - by Pinal Dave
    Today, I’d like to discuss getting better MySQL scalability on Amazon RDS. The question of the day: “What can you do when a MySQL database needs to scale write-intensive workloads beyond the capabilities of the largest available machine on Amazon RDS?” Let’s take a look. In a typical EC2/RDS set-up, users connect to app servers from their mobile devices and tablets, computers, browsers, etc.  Then app servers connect to an RDS instance (web/cloud services) and in some cases they might leverage some read-only replicas.   Figure 1. A typical RDS instance is a single-instance database, with read replicas.  This is not very good at handling high write-based throughput. As your application becomes more popular you can expect an increasing number of users, more transactions, and more accumulated data.  User interactions can become more challenging as the application adds more sophisticated capabilities. The result of all this positive activity: your MySQL database will inevitably begin to experience scalability pressures. What can you do? Broadly speaking, there are four options available to improve MySQL scalability on RDS. 1. Larger RDS Instances – If you’re not already using the maximum available RDS instance, you can always scale up – to larger hardware.  Bigger CPUs, more compute power, more memory et cetera. But the largest available RDS instance is still limited.  And they get expensive. “High-Memory Quadruple Extra Large DB Instance”: 68 GB of memory 26 ECUs (8 virtual cores with 3.25 ECUs each) 64-bit platform High I/O Capacity Provisioned IOPS Optimized: 1000Mbps 2. Provisioned IOPs – You can get provisioned IOPs and higher throughput on the I/O level. However, there is a hard limit with a maximum instance size and maximum number of provisioned IOPs you can buy from Amazon and you simply cannot scale beyond these hardware specifications. 3. Leverage Read Replicas – If your application permits, you can leverage read replicas to offload some reads from the master databases. But there are a limited number of replicas you can utilize and Amazon generally requires some modifications to your existing application. And read-replicas don’t help with write-intensive applications. 4. Multiple Database Instances – Amazon offers a fourth option: “You can implement partitioning,thereby spreading your data across multiple database Instances” (Link) However, Amazon does not offer any guidance or facilities to help you with this. “Multiple database instances” is not an RDS feature.  And Amazon doesn’t explain how to implement this idea. In fact, when asked, this is the response on an Amazon forum: Q: Is there any documents that describe the partition DB across multiple RDS? I need to use DB with more 1TB but exist a limitation during the create process, but I read in the any FAQ that you need to partition database, but I don’t find any documents that describe it. A: “DB partitioning/sharding is not an official feature of Amazon RDS or MySQL, but a technique to scale out database by using multiple database instances. The appropriate way to split data depends on the characteristics of the application or data set. Therefore, there is no concrete and specific guidance.” So now what? The answer is to scale out with ScaleBase. Amazon RDS with ScaleBase: What you get – MySQL Scalability! ScaleBase is specifically designed to scale out a single MySQL RDS instance into multiple MySQL instances. Critically, this is accomplished with no changes to your application code.  Your application continues to “see” one database.   ScaleBase does all the work of managing and enforcing an optimized data distribution policy to create multiple MySQL instances. With ScaleBase, data distribution, transactions, concurrency control, and two-phase commit are all 100% transparent and 100% ACID-compliant, so applications, services and tooling continue to interact with your distributed RDS as if it were a single MySQL instance. The result: now you can cost-effectively leverage multiple MySQL RDS instance to scale out write-intensive workloads to an unlimited number of users, transactions, and data. Amazon RDS with ScaleBase: What you keep – Everything! And how does this change your Amazon environment? 1. Keep your application, unchanged – There is no change your application development life-cycle at all.  You still use your existing development tools, frameworks and libraries.  Application quality assurance and testing cycles stay the same. And, critically, you stay with an ACID-compliant MySQL environment. 2. Keep your RDS value-added services – The value-added services that you rely on are all still available. Amazon will continue to handle database maintenance and updates for you. You can still leverage High Availability via Multi A-Z.  And, if it benefits youra application throughput, you can still use read replicas. 3. Keep your RDS administration – Finally the RDS monitoring and provisioning tools you rely on still work as they did before. With your one large MySQL instance, now split into multiple instances, you can actually use less expensive, smallersmaller available RDS hardware and continue to see better database performance. Conclusion Amazon RDS is a tremendous service, but it doesn’t offer solutions to scale beyond a single MySQL instance. Larger RDS instances get more expensive.  And when you max-out on the available hardware, you’re stuck.  Amazon recommends scaling out your single instance into multiple instances for transaction-intensive apps, but offers no services or guidance to help you. This is where ScaleBase comes in to save the day. It gives you a simple and effective way to create multiple MySQL RDS instances, while removing all the complexities typically caused by “DIY” sharding andwith no changes to your applications . With ScaleBase you continue to leverage the AWS/RDS ecosystem: commodity hardware and value added services like read replicas, multi A-Z, maintenance/updates and administration with monitoring tools and provisioning. SCALEBASE ON AMAZON If you’re curious to try ScaleBase on Amazon, it can be found here – Download NOW. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Nginx php-fpm high cpu usage

    - by Piotr Kaluza
    I have a problem with a high traffic wordpress, super high CPU load under nginx php-fpm, I am caching with apc, and memcached, spent 2-3 days tweaking configs and looking for answers it seems to me that php-fpm takes up all the cpu available no matter how many max_children i set if i set 5 then the load is 20% each, if i set 20 then the load adds up till 90% i tried static and dynamic server is 2x3.0Ghz 6GB Ram SSD in raid 10 on ubuntu 12.04 x64 utpime: 17:27:51 up 2:19, 1 user, load average: 29.79, 28.08, 26.29 what can be the issue?

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  • Improving RDP performance

    - by blade
    Hi, How can I improve RDP performance? I'm on an 8mb line, and I have disabled all the fancy features like visual styles. One page said if I set a low speed, that too will increase performance. Is there any proof in this? Also, there was an ad here about an application/technology which can increase RDP performance by x20. Has anyone used this? Thanks

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