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  • Oracle Solaris 11 ZFS Lab for Openworld 2012

    - by user12626122
    Preface This is the content from the Oracle Openworld 2012 ZFS lab. It was well attended - the feedback was that it was a little short - thats probably because in writing it I bacame very time-concious after the ASM/ACFS on Solaris extravaganza I ran last year which was almost too long for mortal man to finish in the 1 hour session. Enjoy. Table of Contents Exercise Z.1: ZFS Pools Exercise Z.2: ZFS File Systems Exercise Z.3: ZFS Compression Exercise Z.4: ZFS Deduplication Exercise Z.5: ZFS Encryption Exercise Z.6: Solaris 11 Shadow Migration Introduction This set of exercises is designed to briefly demonstrate new features in Solaris 11 ZFS file system: Deduplication, Encryption and Shadow Migration. Also included is the creation of zpools and zfs file systems - the basic building blocks of the technology, and also Compression which is the compliment of Deduplication. The exercises are just introductions - you are referred to the ZFS Adminstration Manual for further information. From Solaris 11 onward the online manual pages consist of zpool(1M) and zfs(1M) with further feature-specific information in zfs_allow(1M), zfs_encrypt(1M) and zfs_share(1M). The lab is easily carried out in a VirtualBox running Solaris 11 with 6 virtual 3 Gb disks to play with. Exercise Z.1: ZFS Pools Task: You have several disks to use for your new file system. Create a new zpool and a file system within it. Lab: You will check the status of existing zpools, create your own pool and expand it. Your Solaris 11 installation already has a root ZFS pool. It contains the root file system. Check this: root@solaris:~# zpool list NAME SIZE ALLOC FREE CAP DEDUP HEALTH ALTROOT rpool 15.9G 6.62G 9.25G 41% 1.00x ONLINE - root@solaris:~# zpool status pool: rpool state: ONLINE scan: none requested config: NAME STATE READ WRITE CKSUM rpool ONLINE 0 0 0 c3t0d0s0 ONLINE 0 0 0 errors: No known data errors Note the disk device the root pool is on - c3t0d0s0 Now you will create your own ZFS pool. First you will check what disks are available: root@solaris:~# echo | format Searching for disks...done AVAILABLE DISK SELECTIONS: 0. c3t0d0 <ATA-VBOX HARDDISK-1.0 cyl 2085 alt 2 hd 255 sec 63> /pci@0,0/pci8086,2829@d/disk@0,0 1. c3t2d0 <ATA-VBOX HARDDISK-1.0 cyl 1534 alt 2 hd 128 sec 32> /pci@0,0/pci8086,2829@d/disk@2,0 2. c3t3d0 <ATA-VBOX HARDDISK-1.0 cyl 1534 alt 2 hd 128 sec 32> /pci@0,0/pci8086,2829@d/disk@3,0 3. c3t4d0 <ATA-VBOX HARDDISK-1.0 cyl 1534 alt 2 hd 128 sec 32> /pci@0,0/pci8086,2829@d/disk@4,0 4. c3t5d0 <ATA-VBOX HARDDISK-1.0 cyl 1534 alt 2 hd 128 sec 32> /pci@0,0/pci8086,2829@d/disk@5,0 5. c3t6d0 <ATA-VBOX HARDDISK-1.0 cyl 1534 alt 2 hd 128 sec 32> /pci@0,0/pci8086,2829@d/disk@6,0 6. c3t7d0 <ATA-VBOX HARDDISK-1.0 cyl 1534 alt 2 hd 128 sec 32> /pci@0,0/pci8086,2829@d/disk@7,0 Specify disk (enter its number): Specify disk (enter its number): The root disk is numbered 0. The others are free for use. Try creating a simple pool and observe the error message: root@solaris:~# zpool create mypool c3t2d0 c3t3d0 'mypool' successfully created, but with no redundancy; failure of one device will cause loss of the pool So destroy that pool and create a mirrored pool instead: root@solaris:~# zpool destroy mypool root@solaris:~# zpool create mypool mirror c3t2d0 c3t3d0 root@solaris:~# zpool status mypool pool: mypool state: ONLINE scan: none requested config: NAME STATE READ WRITE CKSUM mypool ONLINE 0 0 0 mirror-0 ONLINE 0 0 0 c3t2d0 ONLINE 0 0 0 c3t3d0 ONLINE 0 0 0 errors: No known data errors Back to topExercise Z.2: ZFS File Systems Task: You have to create file systems for later exercises. You can see that when a pool is created, a file system of the same name is created: root@solaris:~# zfs list NAME USED AVAIL REFER MOUNTPOINT mypool 86.5K 2.94G 31K /mypool Create your filesystems and mountpoints as follows: root@solaris:~# zfs create -o mountpoint=/data1 mypool/mydata1 The -o option sets the mount point and automatically creates the necessary directory. root@solaris:~# zfs list mypool/mydata1 NAME USED AVAIL REFER MOUNTPOINT mypool/mydata1 31K 2.94G 31K /data1 Back to top Exercise Z.3: ZFS Compression Task:Try out different forms of compression available in ZFS Lab:Create 2nd filesystem with compression, fill both file systems with the same data, observe results You can see from the zfs(1) manual page that there are several types of compression available to you, set with the property=value syntax: compression=on | off | lzjb | gzip | gzip-N | zle Controls the compression algorithm used for this dataset. The lzjb compression algorithm is optimized for performance while providing decent data compression. Setting compression to on uses the lzjb compression algorithm. The gzip compression algorithm uses the same compression as the gzip(1) command. You can specify the gzip level by using the value gzip-N where N is an integer from 1 (fastest) to 9 (best compression ratio). Currently, gzip is equivalent to gzip-6 (which is also the default for gzip(1)). Create a second filesystem with compression turned on. Note how you set and get your values separately: root@solaris:~# zfs create -o mountpoint=/data2 mypool/mydata2 root@solaris:~# zfs set compression=gzip-9 mypool/mydata2 root@solaris:~# zfs get compression mypool/mydata1 NAME PROPERTY VALUE SOURCE mypool/mydata1 compression off default root@solaris:~# zfs get compression mypool/mydata2 NAME PROPERTY VALUE SOURCE mypool/mydata2 compression gzip-9 local Now you can copy the contents of /usr/lib into both your normal and compressing filesystem and observe the results. Don't forget the dot or period (".") in the find(1) command below: root@solaris:~# cd /usr/lib root@solaris:/usr/lib# find . -print | cpio -pdv /data1 root@solaris:/usr/lib# find . -print | cpio -pdv /data2 The copy into the compressing file system takes longer - as it has to perform the compression but the results show the effect: root@solaris:/usr/lib# zfs list NAME USED AVAIL REFER MOUNTPOINT mypool 1.35G 1.59G 31K /mypool mypool/mydata1 1.01G 1.59G 1.01G /data1 mypool/mydata2 341M 1.59G 341M /data2 Note that the available space in the pool is shared amongst the file systems. This behavior can be modified using quotas and reservations which are not covered in this lab but are covered extensively in the ZFS Administrators Guide. Back to top Exercise Z.4: ZFS Deduplication The deduplication property is used to remove redundant data from a ZFS file system. With the property enabled duplicate data blocks are removed synchronously. The result is that only unique data is stored and common componenents are shared. Task:See how to implement deduplication and its effects Lab: You will create a ZFS file system with deduplication turned on and see if it reduces the amount of physical storage needed when we again fill it with a copy of /usr/lib. root@solaris:/usr/lib# zfs destroy mypool/mydata2 root@solaris:/usr/lib# zfs set dedup=on mypool/mydata1 root@solaris:/usr/lib# rm -rf /data1/* root@solaris:/usr/lib# mkdir /data1/2nd-copy root@solaris:/usr/lib# zfs list NAME USED AVAIL REFER MOUNTPOINT mypool 1.02M 2.94G 31K /mypool mypool/mydata1 43K 2.94G 43K /data1 root@solaris:/usr/lib# find . -print | cpio -pd /data1 2142768 blocks root@solaris:/usr/lib# zfs list NAME USED AVAIL REFER MOUNTPOINT mypool 1.02G 1.99G 31K /mypool mypool/mydata1 1.01G 1.99G 1.01G /data1 root@solaris:/usr/lib# find . -print | cpio -pd /data1/2nd-copy 2142768 blocks root@solaris:/usr/lib#zfs list NAME USED AVAIL REFER MOUNTPOINT mypool 1.99G 1.96G 31K /mypool mypool/mydata1 1.98G 1.96G 1.98G /data1 You could go on creating copies for quite a while...but you get the idea. Note that deduplication and compression can be combined: the compression acts on metadata. Deduplication works across file systems in a pool and there is a zpool-wide property dedupratio: root@solaris:/usr/lib# zpool get dedupratio mypool NAME PROPERTY VALUE SOURCE mypool dedupratio 4.30x - Deduplication can also be checked using "zpool list": root@solaris:/usr/lib# zpool list NAME SIZE ALLOC FREE CAP DEDUP HEALTH ALTROOT mypool 2.98G 1001M 2.01G 32% 4.30x ONLINE - rpool 15.9G 6.66G 9.21G 41% 1.00x ONLINE - Before moving on to the next topic, destroy that dataset and free up some space: root@solaris:~# zfs destroy mypool/mydata1 Back to top Exercise Z.5: ZFS Encryption Task: Encrypt sensitive data. Lab: Explore basic ZFS encryption. This lab only covers the basics of ZFS Encryption. In particular it does not cover various aspects of key management. Please see the ZFS Adminastrion Manual and the zfs_encrypt(1M) manual page for more detail on this functionality. Back to top root@solaris:~# zfs create -o encryption=on mypool/data2 Enter passphrase for 'mypool/data2': ******** Enter again: ******** root@solaris:~# Creation of a descendent dataset shows that encryption is inherited from the parent: root@solaris:~# zfs create mypool/data2/data3 root@solaris:~# zfs get -r encryption,keysource,keystatus,checksum mypool/data2 NAME PROPERTY VALUE SOURCE mypool/data2 encryption on local mypool/data2 keysource passphrase,prompt local mypool/data2 keystatus available - mypool/data2 checksum sha256-mac local mypool/data2/data3 encryption on inherited from mypool/data2 mypool/data2/data3 keysource passphrase,prompt inherited from mypool/data2 mypool/data2/data3 keystatus available - mypool/data2/data3 checksum sha256-mac inherited from mypool/data2 You will find the online manual page zfs_encrypt(1M) contains examples. In particular, if time permits during this lab session you may wish to explore the changing of a key using "zfs key -c mypool/data2". Exercise Z.6: Shadow Migration Shadow Migration allows you to migrate data from an old file system to a new file system while simultaneously allowing access and modification to the new file system during the process. You can use Shadow Migration to migrate a local or remote UFS or ZFS file system to a local file system. Task: You wish to migrate data from one file system (UFS, ZFS, VxFS) to ZFS while mainaining access to it. Lab: Create the infrastructure for shadow migration and transfer one file system into another. First create the file system you want to migrate root@solaris:~# zpool create oldstuff c3t4d0 root@solaris:~# zfs create oldstuff/forgotten Then populate it with some files: root@solaris:~# cd /var/adm root@solaris:/var/adm# find . -print | cpio -pdv /oldstuff/forgotten You need the shadow-migration package installed: root@solaris:~# pkg install shadow-migration Packages to install: 1 Create boot environment: No Create backup boot environment: No Services to change: 1 DOWNLOAD PKGS FILES XFER (MB) Completed 1/1 14/14 0.2/0.2 PHASE ACTIONS Install Phase 39/39 PHASE ITEMS Package State Update Phase 1/1 Image State Update Phase 2/2 You then enable the shadowd service: root@solaris:~# svcadm enable shadowd root@solaris:~# svcs shadowd STATE STIME FMRI online 7:16:09 svc:/system/filesystem/shadowd:default Set the filesystem to be migrated to read-only root@solaris:~# zfs set readonly=on oldstuff/forgotten Create a new zfs file system with the shadow property set to the file system to be migrated: root@solaris:~# zfs create -o shadow=file:///oldstuff/forgotten mypool/remembered Use the shadowstat(1M) command to see the progress of the migration: root@solaris:~# shadowstat EST BYTES BYTES ELAPSED DATASET XFRD LEFT ERRORS TIME mypool/remembered 92.5M - - 00:00:59 mypool/remembered 99.1M 302M - 00:01:09 mypool/remembered 109M 260M - 00:01:19 mypool/remembered 133M 304M - 00:01:29 mypool/remembered 149M 339M - 00:01:39 mypool/remembered 156M 86.4M - 00:01:49 mypool/remembered 156M 8E 29 (completed) Note that if you had created /mypool/remembered as encrypted, this would be the preferred method of encrypting existing data. Similarly for compressing or deduplicating existing data. The procedure for migrating a file system over NFS is similar - see the ZFS Administration manual. That concludes this lab session.

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  • Collision Detection and Resolution in Three.js

    - by androidmaster
    So at the moment am making a simple game using three.js and three.firstpersonControls.js but with the current Three.js r66, they apparently removed checkWallCollision and then in the r67 firstpersonControls removed support for that collision. SO my question is how would i go about checking collision in 3D using three.js and then resolution to that collision. (Pushing player out of the block) Note I used a 2D array to generate the world so it's only cubes that I have to check collision with.... if this is a bad question or am lacking something please tell me before you -rep me, am just not sure how to do this and google doesn't want to help

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  • How can we view 3d objects from top down view in TD game

    - by Syed
    I am making a tower defense game. I am working in x and y axis only. I have made a grid, snapped towers and made a pathfinding algo to run enemy. Initially I have worked with cubes and spheres in place of towers and enemies. Now I am going to place real towers (3D). Note that I haven't used z axis up till now. The user will analyze the game from top down view. I want the user to see towers placement with a little bit of 3d view but I have made my all code in 2d thing. Is there any solution to my problem that somewhat tower placement would view a 3D touch or you can say 2.5D ?? (like fieldrunners) or should I have to involve z axis and ignoring y axis ?

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  • Something other than Vertex Welding with Texture Atlas?

    - by Tim Winter
    What options (in C# with XNA) would there be for texture usage in a procedural generated 3D world made of cubes to increase performance? Yes, it's like Minecraft. I've been doing a texture atlas and rendering faces individually (4 vertices per face), but I've also read in a couple places about using texture wrapping with two 1D atlases to merge adjacent faces with the same texture. If two or more adjacent faces share the same image, it'd be quite easy to wrap in this way reducing vertices by a large amount. My problem with this is having too many textures, swapping too often, and many image related things like non-power of 2 images. Is there a middle ground option between the 1D texture atlas trick and rendering 4 vertices per cube face? This is a picture of what I have currently (in wireframe). 4 vertices per face seems extremely inefficient to me.

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  • Why are SW engineering interviews disproportionately difficult?

    - by stackoverflowuser2010
    First, some background on me. I have a PhD in CS and have had jobs both as a software engineer and as an R&D research scientist, both at Very Large Corporations You Know Very Well. I recently changed jobs and interviewed for both types of jobs (as I have done in the past). My observation: SW engineer job interviews are way, way disproportionately more difficult than CS researcher job interviews, but the researcher job is higher paying, more competitive, more rewarding, more interesting, and has a higher upside. Here's a typical interview loop for researcher: Phone interview to see if my research is in alignment with the lab's researcher In-person, give presentation on my recent research for one hour (which represents maybe 9 month's worth of work), answer questions In-person one-on-one interviews with about 5 researchers, where they ask me very reasonable questions on my work/publications/patents, including: technical questions, where my work fits into related work, and how I can extend my work to new areas Here's a typical interview loop for SW engineer: Phone interview where I'm asked algorithm questions and maybe do some coding. Pretty standard. In-person interviews at the whiteboard where they drill the F*** out of you on esoteric C++ minutia (e.g. how does a polymorphic virtual function call work), algorithms (make all-pairs-shortest-path algorithm work for 1B vertices), system design (design a database load balancer), etc. This goes on for six or seven interviews. Ridiculous. Why would anyone be willing to put up with this? What is the point of asking about C++ trivia or writing code to prove yourself? Why not make the SE interview more like the researcher interview where you give a talk about what you've done? How are technical job interviews for other fields, like physics, chemistry, civil engineering, mechanical engineering?

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  • Oracle ADF Mobile and Developing On-device Mobile Applications

    - by Joe Huang
    Hi, everyone: It has been almost a year since we posted to this blog, and I am happy to report that we are steadily marching toward releasing a new generation of ADF Mobile.  This blog site has been quiet as we are heads down to develop this new generation of ADF Mobile.  As we are nearing releasing this next generation product, there are substantial number of Oracle internal application teams and external customers/partners actively developing using the beta version of this framework.  We are actively taking feedbacks from these teams and ensuring the product is ready for general availability. If you are intersted for more details around this new generation of ADF Mobile, we are hosting a session and a hands on lab this week at the ODTUG KScope 12 conference.  The lab is booked completely full weeks in advance, but perhaps you can still get into the session (Wed at 9:45 AM).   Look for updates from this blog site as well as the Oracle OTN ADF Mobile landing page during the weeks leading to Oracle OpenWorld 2012.   Thanks, Joe Huang

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  • How to make custom shaped holes in terrain

    - by Guy Ben-Moshe
    So I'm trying to create a game where you fit certain shaped objects into the hole that fits them (similar to the young children's game with different shaped blocks) in Unity 3D. I've encountered a problem, how do I make the holes in the terrain? Or what type of object should I use for making holes in? So far I've tried to make a 3d model in unity by using other cubes and planes, it just doesn't feel right. I guess I need to create a model in another software and import to unity, I don't know any other software I can use. Tips would help.

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  • Stereo images rectification and disparity: which algorithms?

    - by alessandro.francesconi
    I'm trying to figure out what are currently the two most efficent algorithms that permit, starting from a L/R pair of stereo images created using a traditional camera (so affected by some epipolar lines misalignment), to produce a pair of adjusted images plus their depth information by looking at their disparity. Actually I've found lots of papers about these two methods, like: "Computing Rectifying Homographies for Stereo Vision" (Zhang - seems one of the best for rectification only) "Three-step image recti?cation" (Monasse) "Rectification and Disparity" (slideshow by Navab) "A fast area-based stereo matching algorithm" (Di Stefano - seems a bit inaccurate) "Computing Visual Correspondence with Occlusions via Graph Cuts" (Kolmogorov - this one produces a very good disparity map, with also occlusion informations, but is it efficient?) "Dense Disparity Map Estimation Respecting Image Discontinuities" (Alvarez - toooo long for a first review) Anyone could please give me some advices for orienting into this wide topic? What kind of algorithm/method should I treat first, considering that I'll work on a very simple input: a pair of left and right images and nothing else, no more information (some papers are based on additional, pre-taken, calibration infos)? Speaking about working implementations, the only interesting results I've seen so far belongs to this piece of software, but only for automatic rectification, not disparity: http://stereo.jpn.org/eng/stphmkr/index.html I tried the "auto-adjustment" feature and seems really effective. Too bad there is no source code...

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  • Distribute Sort Sample Service

    - by kaleidoscope
    How it works? Using the front-end of the service, a user can specify a size in MB for the input data set to sort. Algorithm CreateAndSplit The CreateAndSplit task generates the input data and stores them as 10 blobs in the utility storage. The URLs to these blobs are packaged as Separate work items and written to the queue. · Separate The Separate task reads the blobs with the random numbers created in the CreateAndSplit task and places the random numbers into buckets. The interval of the numbers that go into one bucket is chosen so that the expected amount of numbers (assuming a uniform distribution of the numbers in the original data set) is around 100 kB. Each bucket is represented as a blob container in utility storage. Whenever there are 10 blobs in one bucket (i.e., the placement in this bucket is complete because we had 10 original splits), the separate task will generate a new Sort task and write the task into the queue. · Sort The Sort task merges all blobs in a single bucket and sorts them using a standard sort algorithm. The result is stored as a blob in utility storage. · Concat The concat task merges the results of all Sort tasks into a single blob. This blob can be downloaded as a text file using this Web page. As the resulting file is presented in text format, the size of the file is likely to be larger than the specified input file. Anish

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  • Which algorithms/data structures should I "recognize" and know by name?

    - by Earlz
    I'd like to consider myself a fairly experienced programmer. I've been programming for over 5 years now. My weak point though is terminology. I'm self-taught, so while I know how to program, I don't know some of the more formal aspects of computer science. So, what are practical algorithms/data structures that I could recognize and know by name? Note, I'm not asking for a book recommendation about implementing algorithms. I don't care about implementing them, I just want to be able to recognize when an algorithm/data structure would be a good solution to a problem. I'm asking more for a list of algorithms/data structures that I should "recognize". For instance, I know the solution to a problem like this: You manage a set of lockers labeled 0-999. People come to you to rent the locker and then come back to return the locker key. How would you build a piece of software to manage knowing which lockers are free and which are in used? The solution, would be a queue or stack. What I'm looking for are things like "in what situation should a B-Tree be used -- What search algorithm should be used here" etc. And maybe a quick introduction of how the more complex(but commonly used) data structures/algorithms work. I tried looking at Wikipedia's list of data structures and algorithms but I think that's a bit overkill. So I'm looking more for what are the essential things I should recognize?

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  • How do graphics programmers deal with rendering vertices that don't change the image?

    - by canisrufus
    So, the title is a little awkward. I'll give some background, and then ask my question. Background: I work as a web GIS application developer, but in my spare time I've been playing with map rendering and improving data interchange formats. I work only in 2D space. One interesting issue I've encountered is that when you're rendering a polygon at a small scale (zoomed way out), many of the vertices are redundant. An extreme case would be that you have a polygon with 500,000 vertices that only takes up a single pixel. If you're sending this data to the browser, it would make sense to omit ~499,999 of those vertices. One way we achieve that is by rendering an image on a server and and sending it as a PNG: voila, it's a point. Sometimes, though, we want data sent to the browser where it can be rendered with SVG (or canvas, or webgl) so that it can be interactive. The problem: It turns out that, using modern geographic data sets, it's very easy to overload SVG's rendering abilities. In an effort to cope with those limitations, I'm trying to figure out how to visually losslessly reduce a data set for a given scale and map extent (and, if necessary, for a known map pixel width and height). I got a great reduction in data size just using the Douglas-Peucker algorithm, and I believe I was able to get it to keep the polygons true to within one pixel. Unfortunately, Douglas-Peucker doesn't preserve topology, so it changed how borders between polygons got rendered. I couldn't readily find other algorithms to try out and adapt to the purpose, but I don't have much CS/algorithm background and might not recognize them if I saw them.

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  • Functional programming and stateful algorithms

    - by bigstones
    I'm learning functional programming with Haskell. In the meantime I'm studying Automata theory and as the two seem to fit well together I'm writing a small library to play with automata. Here's the problem that made me ask the question. While studying a way to evaluate a state's reachability I got the idea that a simple recursive algorithm would be quite inefficient, because some paths might share some states and I might end up evaluating them more than once. For example, here, evaluating reachability of g from a, I'd have to exclude f both while checking the path through d and c: So my idea is that an algorithm working in parallel on many paths and updating a shared record of excluded states might be great, but that's too much for me. I've seen that in some simple recursion cases one can pass state as an argument, and that's what I have to do here, because I pass forward the list of states I've gone through to avoid loops. But is there a way to pass that list also backwards, like returning it in a tuple together with the boolean result of my canReach function? (although this feels a bit forced) Besides the validity of my example case, what other techniques are available to solve this kind of problems? I feel like these must be common enough that there have to be solutions like what happens with fold* or map. So far, reading learnyouahaskell.com I didn't find any, but consider I haven't touched monads yet. (if interested, I posted my code on codereview)

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  • Why is Quicksort called "Quicksort"?

    - by Darrel Hoffman
    The point of this question is not to debate the merits of this over any other sorting algorithm - certainly there are many other questions that do this. This question is about the name. Why is Quicksort called "Quicksort"? Sure, it's "quick", most of the time, but not always. The possibility of degenerating to O(N^2) is well known. There are various modifications to Quicksort that mitigate this problem, but the ones which bring the worst case down to a guaranteed O(n log n) aren't generally called Quicksort anymore. (e.g. Introsort). I just wonder why of all the well-known sorting algorithms, this is the only one deserving of the name "quick", which describes not how the algorithm works, but how fast it (usually) is. Mergesort is called that because it merges the data. Heapsort is called that because it uses a heap. Introsort gets its name from "Introspective", since it monitors its own performance to decide when to switch from Quicksort to Heapsort. Similarly for all the slower ones - Bubblesort, Insertion sort, Selection sort, etc. They're all named for how they work. The only other exception I can think of is "Bogosort", which is really just a joke that nobody ever actually uses in practice. Why isn't Quicksort called something more descriptive, like "Partition sort" or "Pivot sort", which describe what it actually does? It's not even a case of "got here first". Mergesort was developed 15 years before Quicksort. (1945 and 1960 respectively according to Wikipedia) I guess this is really more of a history question than a programming one. I'm just curious how it got the name - was it just good marketing?

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  • What is a simple deformer in which vertices deform linearly with control points?

    - by sebf
    In my project I want to deform a complex mesh, using a simpler 'proxy' mesh. In effect, each vertex of the proxy/collision mesh will be a control point/bone, which should deform the vertices of the main mesh attached to it depending on weight, but where the weight is not dependant on the absolute distance from the control point but rather distance relative to the other affecting control points. The point of this is to preserve complex three dimensional features of the main mesh while using physics implementations which expect something far simpler, low resolution, single surface, etc. Therefore, the vertices must deform linearly with their respective weighted control points (i.e. no falloff fields or all the mesh features will end up collapsed) - as if each vertex was linked to a point on the plane created by the attached control points and deformed with it. I have tried implementing the weight computation algorithm in this paper (page 4) but it is not working as expected and I am wondering if it is really the best way to do what I want. What is the simplest way to 'skin'* an arbitrary mesh, to another arbitrary mesh? *By skin I mean I need an algorithm to determine the best control points for a vertex, and their weights.

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  • How to improve Algorithmic Programming Solving skill? [closed]

    - by gaurav
    Possible Duplicate: How can I improve my problem-solving ability? How do you improve your problem solving skills? Should I learn design patterns or algorithms to improve my logical thinking skills? What to do when you're faced with a problem that you can't solve quickly? Are there non-programming related activities akin to solving programming problems? I am a computer engineering graduate. I have studied programming since three years. I am good in coding and programming. I have been trying to compete in algorithmic competitions on sites such as topcoder,spoj since one and a half year, but I am still unable to solve problems other than too easy problems. I have learned from people that it takes practice to solve such problems. I try to solve those problems but sometimes I am unable to understand and even if I do understand I am unable to think of a good algorithm for solving it. Even if I solve I get Wrong answer and I am unable to figure out what is the problem with my code as it works on samples given on the sites but fails on test cases which they do not provide. I really want to solve those problems and become good in algorithms. I have read books for learning algorithms like Introduction to algorithms by CLRS,practicing programming questions. I have gone through some questions but they don't answer this question. I have seen the questions which are said duplicates but those questions focus on overall programming, but I am asking for algorithm related programming, basically for competing in programming which involve solving a problem statement then online judge will automatically evaluate it, such type of programming is quite different from the type of programming these questions discuss.

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  • How can I find the shortest path between two subgraphs of a larger graph?

    - by Pops
    I'm working with a weighted, undirected multigraph (loops not permitted; most node connections have multiplicity 1; a few node connections have multiplicity 2). I need to find the shortest path between two subgraphs of this graph that do not overlap with each other. There are no other restrictions on which nodes should be used as start/end points. Edges can be selectively removed from the graph at certain times (as explained in my previous question) so it's possible that for two given subgraphs, there might not be any way to connect them. I'm pretty sure I've heard of an algorithm for this before, but I can't remember what it's called, and my Google searches for strings like "shortest path between subgraphs" haven't helped. Can someone suggest a more efficient way to do this than comparing shortest paths between all nodes in one subgraph with all nodes in the other subgraph? Or at least tell me the name of the algorithm so I can look it up myself? For example, if I have the graph below, the nodes circled in red might be one subgraph and the nodes circled in blue might be another. The edges would all have positive integer weights, although they're not shown in the image. I'd want to find whatever path has the shortest total cost as long as it starts at a red node and ends at a blue node. I believe this means the specific node positions and edge weights cannot be ignored. (This is just an example graph I grabbed off Wikimedia and drew on, not my actual problem.)

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  • Sorting versus hashing

    - by Paul Siegel
    My problem is as follows. I have an array of n strings with m < n of them distinct. I want to create a one-to-one function which assigns each of the m distinct strings to the numbers 0 ... m-1. For example, if my strings are: Bob, Amy, Bob, Charlie, Amy then the function: Bob -> 0, Amy -> 1, Charlie -> 2 would meet my needs. I have thought of three possible approaches: Sort the list of strings, remove duplicates, and construct the function using a search algorithm. Create a hash table and check each string to see if it is already in the table before inserting it. Sort the list of strings, remove duplicates, and put the resulting list into a hash table. My code will be written in Java, and I will likely use standard Java algorithms: merge sort for sorting, binary search for searching, and whatever the standard Java hash table algorithm is. Question: Assume that after creating the function I will have to evaluate it on each of the n original strings. Which of the three approaches is fastest? Is there a better way? Part of the problem is that I don't really know what's going on "under the hood" in standard hashing algorithms. Any help would be appreciated.

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  • Greiner-Hormann clipping problem

    - by Belgin
    I have a set of planar polygons in 3D space defined by their vertices in counterclockwise order. Let's define the 'positive face' as being the face of the 3D polygon such as when observed, the vertices appear in counterclockwise order, and the 'negative face', the face which when observed, the vertices appear in clockwise order. I'm doing perspective projection of the set of polygons onto a projection polygon defined by the points in this order: (0, h, 0), (0, 0, 0), (w, 0, 0), and (w, h, 0), where w and h are strictly positive integers. The positive face of this projection polygon is oriented towards positive Z, and the camera point is somewhere at (0, 0, d), where d is a strictly negative number. In order to 'clip' the projected polygons into the projection polygon, I'm applying the Greiner-Hormann (PDF) clipping algorithm, which requires that the clipper and the to-be-clipped polygons be in the same order (i.e. clockwise or counterclockwise). My question is the following: How can I determine whether the projected face of the 3D polygon is the negative or the positive one? Meaning, how do I find out if I have to work with the vertices in normal or inverted order for the algorithm to work? I noticed that only if the 3D polygon is facing the projection polygon with its negative face, both of them are in the same order (counterclockwise), otherwise, a modification needs to be done. Here is a picture (PNG) that illustrates this. Note that the planes described by the polygon from the set and the projection polygon may not always be parallel.

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  • How can I rank teams based off of head to head wins/losses

    - by TMP
    I'm trying to write an algorithm (specifically in Ruby) that will rank teams based on their record against each other. If a team A and team B have won the same amount of games against each other, then it goes down to point differentials. Here's an example: A beat B two times B beats C one time A beats D three times C bests D two times D beats C one time B beats A one time Which sort of reduces to A[B] = 2 B[C] = 1 A[D] = 3 C[D] = 2 D[C] = 1 B[A] = 1 Which sort of reduces to A[B] = 1 B[C] = 1 A[D] = 3 C[D] = 1 D[C] = -1 B[A] = -1 Which is about how far I've got I think the results of this specific algorithm would be: A, B, C, D But I'm stuck on how to transition from my nested hash-like structure to the results. My psuedo-code is as follows (I can post my ruby code too if someone wants): For each game(g): hash[g.winner][g.loser] += 1 That leaves hash as the first reduction above hash2 = clone of hash For each key(winner), value(losers hash) in hash: For each key(loser), value(losses against winner): hash2[loser][winner] -= losses Which leaves hash2 as the second reduction Feel free to as me question or edit this to be more clear, I'm not sure of how to put it in a very eloquent way. Thanks!

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  • Graduated transition from Green - Yellow - Red

    - by GoldBishop
    I have am having algorithm mental block in designing a way to transition from Green to Red, as smoothly as possible with a, potentially, unknown length of time to transition. For testing purposes, i will be using 300 as my model timespan but the methodology algorithm design needs to be flexible enough to account for larger or even smaller timespans. Figured using RGB would probably be the best to transition with, but open to other color creation types, assuming its native to .Net (VB/C#). Currently i have: t = 300 x = t/2 z = 0 low = Green (0, 255, 0) mid = Yellow (255, 255, 0) high = Red (255, 0, 0) Lastly, sort of an optional piece, is to account for the possibility of the low, mid, and high color's to be flexible as well. I assume that there would need to be a check to make sure that someone isnt putting in low = (255,0,0), mid=(254,0,0), and high=(253,0,0). Outside of this anomaly, which i will handle myself based on the best approach to evaluate a color. Question: What would be the best approach to do the transition from low to mid and then from mid to high? What would be some potential pitfalls of implementing this type of design, if any?

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  • Sort algorithms that work on large amount of data

    - by Giorgio
    I am looking for sorting algorithms that can work on a large amount of data, i.e. that can work even when the whole data set cannot be held in main memory at once. The only candidate that I have found up to now is merge sort: you can implement the algorithm in such a way that it scans your data set at each merge without holding all the data in main memory at once. The variation of merge sort I have in mind is described in this article in section Use with tape drives. I think this is a good solution (with complexity O(n x log(n)) but I am curious to know if there are other (possibly faster) sorting algorithms that can work on large data sets that do not fit in main memory. EDIT Here are some more details, as required by the answers: The data needs to be sorted periodically, e.g. once in a month. I do not need to insert a few records and have the data sorted incrementally. My example text file is about 1 GB UTF-8 text, but I wanted to solve the problem in general, even if the file were, say, 20 GB. It is not in a database and, due to other constraints, it cannot be. The data is dumped by others as a text file, I have my own code to read this text file. The format of the data is a text file: new line characters are record separators. One possible improvement I had in mind was to split the file into files that are small enough to be sorted in memory, and finally merge all these files using the algorithm I have described above.

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  • Distance between two 3D objects' faces

    - by Arthur Gibraltar
    I'm really newbie on programming and I'm making some tests. I couldn't find nowhere on Internet how could I calculate the distance between two 3D objects' faces. Is there anyway? Detailing, as an example, I have two 3D cubes. Each one has a vector3 position designating it's center on the 3D space and an orientation matrix. And each cube has a size (float width, float height and float length). I could get a simple distance between them by calling Vector3.Distance(), but it doesn't consider its sizes, just the position. Then the distance would be between its centers. Is there any way to calculate the distance between the faces? Thanks for any reply.

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  • Matrix Multiplication with C++ AMP

    - by Daniel Moth
    As part of our API tour of C++ AMP, we looked recently at parallel_for_each. I ended that post by saying we would revisit parallel_for_each after introducing array and array_view. Now is the time, so this is part 2 of parallel_for_each, and also a post that brings together everything we've seen until now. The code for serial and accelerated Consider a naïve (or brute force) serial implementation of matrix multiplication  0: void MatrixMultiplySerial(std::vector<float>& vC, const std::vector<float>& vA, const std::vector<float>& vB, int M, int N, int W) 1: { 2: for (int row = 0; row < M; row++) 3: { 4: for (int col = 0; col < N; col++) 5: { 6: float sum = 0.0f; 7: for(int i = 0; i < W; i++) 8: sum += vA[row * W + i] * vB[i * N + col]; 9: vC[row * N + col] = sum; 10: } 11: } 12: } We notice that each loop iteration is independent from each other and so can be parallelized. If in addition we have really large amounts of data, then this is a good candidate to offload to an accelerator. First, I'll just show you an example of what that code may look like with C++ AMP, and then we'll analyze it. It is assumed that you included at the top of your file #include <amp.h> 13: void MatrixMultiplySimple(std::vector<float>& vC, const std::vector<float>& vA, const std::vector<float>& vB, int M, int N, int W) 14: { 15: concurrency::array_view<const float,2> a(M, W, vA); 16: concurrency::array_view<const float,2> b(W, N, vB); 17: concurrency::array_view<concurrency::writeonly<float>,2> c(M, N, vC); 18: concurrency::parallel_for_each(c.grid, 19: [=](concurrency::index<2> idx) restrict(direct3d) { 20: int row = idx[0]; int col = idx[1]; 21: float sum = 0.0f; 22: for(int i = 0; i < W; i++) 23: sum += a(row, i) * b(i, col); 24: c[idx] = sum; 25: }); 26: } First a visual comparison, just for fun: The beginning and end is the same, i.e. lines 0,1,12 are identical to lines 13,14,26. The double nested loop (lines 2,3,4,5 and 10,11) has been transformed into a parallel_for_each call (18,19,20 and 25). The core algorithm (lines 6,7,8,9) is essentially the same (lines 21,22,23,24). We have extra lines in the C++ AMP version (15,16,17). Now let's dig in deeper. Using array_view and extent When we decided to convert this function to run on an accelerator, we knew we couldn't use the std::vector objects in the restrict(direct3d) function. So we had a choice of copying the data to the the concurrency::array<T,N> object, or wrapping the vector container (and hence its data) with a concurrency::array_view<T,N> object from amp.h – here we used the latter (lines 15,16,17). Now we can access the same data through the array_view objects (a and b) instead of the vector objects (vA and vB), and the added benefit is that we can capture the array_view objects in the lambda (lines 19-25) that we pass to the parallel_for_each call (line 18) and the data will get copied on demand for us to the accelerator. Note that line 15 (and ditto for 16 and 17) could have been written as two lines instead of one: extent<2> e(M, W); array_view<const float, 2> a(e, vA); In other words, we could have explicitly created the extent object instead of letting the array_view create it for us under the covers through the constructor overload we chose. The benefit of the extent object in this instance is that we can express that the data is indeed two dimensional, i.e a matrix. When we were using a vector object we could not do that, and instead we had to track via additional unrelated variables the dimensions of the matrix (i.e. with the integers M and W) – aren't you loving C++ AMP already? Note that the const before the float when creating a and b, will result in the underling data only being copied to the accelerator and not be copied back – a nice optimization. A similar thing is happening on line 17 when creating array_view c, where we have indicated that we do not need to copy the data to the accelerator, only copy it back. The kernel dispatch On line 18 we make the call to the C++ AMP entry point (parallel_for_each) to invoke our parallel loop or, as some may say, dispatch our kernel. The first argument we need to pass describes how many threads we want for this computation. For this algorithm we decided that we want exactly the same number of threads as the number of elements in the output matrix, i.e. in array_view c which will eventually update the vector vC. So each thread will compute exactly one result. Since the elements in c are organized in a 2-dimensional manner we can organize our threads in a two-dimensional manner too. We don't have to think too much about how to create the first argument (a grid) since the array_view object helpfully exposes that as a property. Note that instead of c.grid we could have written grid<2>(c.extent) or grid<2>(extent<2>(M, N)) – the result is the same in that we have specified M*N threads to execute our lambda. The second argument is a restrict(direct3d) lambda that accepts an index object. Since we elected to use a two-dimensional extent as the first argument of parallel_for_each, the index will also be two-dimensional and as covered in the previous posts it represents the thread ID, which in our case maps perfectly to the index of each element in the resulting array_view. The kernel itself The lambda body (lines 20-24), or as some may say, the kernel, is the code that will actually execute on the accelerator. It will be called by M*N threads and we can use those threads to index into the two input array_views (a,b) and write results into the output array_view ( c ). The four lines (21-24) are essentially identical to the four lines of the serial algorithm (6-9). The only difference is how we index into a,b,c versus how we index into vA,vB,vC. The code we wrote with C++ AMP is much nicer in its indexing, because the dimensionality is a first class concept, so you don't have to do funny arithmetic calculating the index of where the next row starts, which you have to do when working with vectors directly (since they store all the data in a flat manner). I skipped over describing line 20. Note that we didn't really need to read the two components of the index into temporary local variables. This mostly reflects my personal choice, in some algorithms to break down the index into local variables with names that make sense for the algorithm, i.e. in this case row and col. In other cases it may i,j,k or x,y,z, or M,N or whatever. Also note that we could have written line 24 as: c(idx[0], idx[1])=sum  or  c(row, col)=sum instead of the simpler c[idx]=sum Targeting a specific accelerator Imagine that we had more than one hardware accelerator on a system and we wanted to pick a specific one to execute this parallel loop on. So there would be some code like this anywhere before line 18: vector<accelerator> accs = MyFunctionThatChoosesSuitableAccelerators(); accelerator acc = accs[0]; …and then we would modify line 18 so we would be calling another overload of parallel_for_each that accepts an accelerator_view as the first argument, so it would become: concurrency::parallel_for_each(acc.default_view, c.grid, ...and the rest of your code remains the same… how simple is that? Comments about this post by Daniel Moth welcome at the original blog.

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  • How to Detect Sprites in a SpriteSheet?

    - by IAE
    I'm currently writing a Sprite Sheet Unpacker such as Alferds Spritesheet Unpacker. Now, before this is sent to gamedev, this isn't necessarily about games. I would like to know how to detect a sprite within a spriitesheet, or more abstactly, a shape inside of an image. Given this sprite sheet: I want to detect and extract all individual sprites. I've followed the algorithm detailed in Alferd's Blog Post which goes like: Determine predominant color and dub it the BackgroundColor Iterate over each pixel and check ColorAtXY == BackgroundColor If false, we've found a sprite. Keep going right until we find a BackgroundColor again, backtrack one, go down and repeat until a BackgroundColor is reached. Create a box from location to ending location. Repeat this until all sprites are boxed up. Combined overlapping boxes (or within a very short distance) The resulting non-overlapping boxes should contain the sprite. This implementation is fine, especially for small sprite sheets. However, I find the performance too poor for larger sprite sheets and I would like to know what algorithms or techniques can be leveraged to increase the finding of sprites. A second implementation I considered, but have not tested yet, is to find the first pixel, then use a backtracking algorithm to find every connected pixel. This should find a contiguous sprite (breaks down if the sprite is something like an explosion where particles are no longer part of the main sprite). The cool thing is that I can immediately remove a detected sprite from the sprite sheet. Any other suggestions?

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  • What are examples of games with "minimalist" models/art assets

    - by Ken
    When teaching game development, my student's obsess about building realistic or complex art/models/animation. And spending wayyy to much time trying to get accurate collision detection between two 3D models [despite my best efforts] However I would like them to spend more time thinking about developing the game mechanics, interaction and game play. I'm looking for some games where the visuals are simple but have good game play. Things I am thinking about are Cubes' vs Spheres or Impossible Game. What are more examples of visually simple (preferably 3D) games to help inspire my students?

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