Search Results

Search found 8692 results on 348 pages for 'per magnusson'.

Page 35/348 | < Previous Page | 31 32 33 34 35 36 37 38 39 40 41 42  | Next Page >

  • OpenGL ES 2.0: Using VBOs?

    - by Bunkai.Satori
    OpenGL VBOs (vertex buffer objects) have been developed to improve performance of OpenGL (OpenGL ES 2.0 in my case). The logic is that with the help of VBOs, the data does not need to be copied from client memory to graphics card on per frame basis. However, as I see it, the game scene changes continuously: position of objects change, their scaling and rotating change, they get animated, they explode, they get spawn or disappear. In such highly dynamic environment, such as computer game scene is, what is the point of using VBOs, if the VBOs would need to be constructed on per-frame basis anyway? Can you please help me to understand how to practically take beneif of VBOs in computer games? Can there be more vertex based VBOs (say one per one object) or there must be always exactly only one VBO present for each draw cycle?

    Read the article

  • Geometry instancing in OpenGL ES 2.0

    - by seahorse
    I am planning to do geometry instancing in OpenGL ES 2.0 Basically I plan to render the same geometry(a chair) maybe 1000 times in my scene. What is the best way to do this in OpenGL ES 2.0? I am considering passing model view mat4 as an attribute. Since attributes are per vertex data do I need to pass this same mat4, three times for each vertex of the same triangle(since modelview remains constant across vertices of the triangle). That would amount to a lot of extra data sent to the GPU( 2 extra vertices*16 floats*(Number of triangles) amount of extra data). Or should I be sending the mat4 only once per triangle?But how is that possible using attributes since attributes are defined as "per vertex" data? What is the best and efficient way to do instancing in OpenGL ES 2.0?

    Read the article

  • 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.

    Read the article

  • PTLQueue : a scalable bounded-capacity MPMC queue

    - by Dave
    Title: Fast concurrent MPMC queue -- I've used the following concurrent queue algorithm enough that it warrants a blog entry. I'll sketch out the design of a fast and scalable multiple-producer multiple-consumer (MPSC) concurrent queue called PTLQueue. The queue has bounded capacity and is implemented via a circular array. Bounded capacity can be a useful property if there's a mismatch between producer rates and consumer rates where an unbounded queue might otherwise result in excessive memory consumption by virtue of the container nodes that -- in some queue implementations -- are used to hold values. A bounded-capacity queue can provide flow control between components. Beware, however, that bounded collections can also result in resource deadlock if abused. The put() and take() operators are partial and wait for the collection to become non-full or non-empty, respectively. Put() and take() do not allocate memory, and are not vulnerable to the ABA pathologies. The PTLQueue algorithm can be implemented equally well in C/C++ and Java. Partial operators are often more convenient than total methods. In many use cases if the preconditions aren't met, there's nothing else useful the thread can do, so it may as well wait via a partial method. An exception is in the case of work-stealing queues where a thief might scan a set of queues from which it could potentially steal. Total methods return ASAP with a success-failure indication. (It's tempting to describe a queue or API as blocking or non-blocking instead of partial or total, but non-blocking is already an overloaded concurrency term. Perhaps waiting/non-waiting or patient/impatient might be better terms). It's also trivial to construct partial operators by busy-waiting via total operators, but such constructs may be less efficient than an operator explicitly and intentionally designed to wait. A PTLQueue instance contains an array of slots, where each slot has volatile Turn and MailBox fields. The array has power-of-two length allowing mod/div operations to be replaced by masking. We assume sensible padding and alignment to reduce the impact of false sharing. (On x86 I recommend 128-byte alignment and padding because of the adjacent-sector prefetch facility). Each queue also has PutCursor and TakeCursor cursor variables, each of which should be sequestered as the sole occupant of a cache line or sector. You can opt to use 64-bit integers if concerned about wrap-around aliasing in the cursor variables. Put(null) is considered illegal, but the caller or implementation can easily check for and convert null to a distinguished non-null proxy value if null happens to be a value you'd like to pass. Take() will accordingly convert the proxy value back to null. An advantage of PTLQueue is that you can use atomic fetch-and-increment for the partial methods. We initialize each slot at index I with (Turn=I, MailBox=null). Both cursors are initially 0. All shared variables are considered "volatile" and atomics such as CAS and AtomicFetchAndIncrement are presumed to have bidirectional fence semantics. Finally T is the templated type. I've sketched out a total tryTake() method below that allows the caller to poll the queue. tryPut() has an analogous construction. Zebra stripping : alternating row colors for nice-looking code listings. See also google code "prettify" : https://code.google.com/p/google-code-prettify/ Prettify is a javascript module that yields the HTML/CSS/JS equivalent of pretty-print. -- pre:nth-child(odd) { background-color:#ff0000; } pre:nth-child(even) { background-color:#0000ff; } border-left: 11px solid #ccc; margin: 1.7em 0 1.7em 0.3em; background-color:#BFB; font-size:12px; line-height:65%; " // PTLQueue : Put(v) : // producer : partial method - waits as necessary assert v != null assert Mask = 1 && (Mask & (Mask+1)) == 0 // Document invariants // doorway step // Obtain a sequence number -- ticket // As a practical concern the ticket value is temporally unique // The ticket also identifies and selects a slot auto tkt = AtomicFetchIncrement (&PutCursor, 1) slot * s = &Slots[tkt & Mask] // waiting phase : // wait for slot's generation to match the tkt value assigned to this put() invocation. // The "generation" is implicitly encoded as the upper bits in the cursor // above those used to specify the index : tkt div (Mask+1) // The generation serves as an epoch number to identify a cohort of threads // accessing disjoint slots while s-Turn != tkt : Pause assert s-MailBox == null s-MailBox = v // deposit and pass message Take() : // consumer : partial method - waits as necessary auto tkt = AtomicFetchIncrement (&TakeCursor,1) slot * s = &Slots[tkt & Mask] // 2-stage waiting : // First wait for turn for our generation // Acquire exclusive "take" access to slot's MailBox field // Then wait for the slot to become occupied while s-Turn != tkt : Pause // Concurrency in this section of code is now reduced to just 1 producer thread // vs 1 consumer thread. // For a given queue and slot, there will be most one Take() operation running // in this section. // Consumer waits for producer to arrive and make slot non-empty // Extract message; clear mailbox; advance Turn indicator // We have an obvious happens-before relation : // Put(m) happens-before corresponding Take() that returns that same "m" for T v = s-MailBox if v != null : s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 // unlock slot to admit next producer and consumer return v Pause tryTake() : // total method - returns ASAP with failure indication for auto tkt = TakeCursor slot * s = &Slots[tkt & Mask] if s-Turn != tkt : return null T v = s-MailBox // presumptive return value if v == null : return null // ratify tkt and v values and commit by advancing cursor if CAS (&TakeCursor, tkt, tkt+1) != tkt : continue s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 return v The basic idea derives from the Partitioned Ticket Lock "PTL" (US20120240126-A1) and the MultiLane Concurrent Bag (US8689237). The latter is essentially a circular ring-buffer where the elements themselves are queues or concurrent collections. You can think of the PTLQueue as a partitioned ticket lock "PTL" augmented to pass values from lock to unlock via the slots. Alternatively, you could conceptualize of PTLQueue as a degenerate MultiLane bag where each slot or "lane" consists of a simple single-word MailBox instead of a general queue. Each lane in PTLQueue also has a private Turn field which acts like the Turn (Grant) variables found in PTL. Turn enforces strict FIFO ordering and restricts concurrency on the slot mailbox field to at most one simultaneous put() and take() operation. PTL uses a single "ticket" variable and per-slot Turn (grant) fields while MultiLane has distinct PutCursor and TakeCursor cursors and abstract per-slot sub-queues. Both PTL and MultiLane advance their cursor and ticket variables with atomic fetch-and-increment. PTLQueue borrows from both PTL and MultiLane and has distinct put and take cursors and per-slot Turn fields. Instead of a per-slot queues, PTLQueue uses a simple single-word MailBox field. PutCursor and TakeCursor act like a pair of ticket locks, conferring "put" and "take" access to a given slot. PutCursor, for instance, assigns an incoming put() request to a slot and serves as a PTL "Ticket" to acquire "put" permission to that slot's MailBox field. To better explain the operation of PTLQueue we deconstruct the operation of put() and take() as follows. Put() first increments PutCursor obtaining a new unique ticket. That ticket value also identifies a slot. Put() next waits for that slot's Turn field to match that ticket value. This is tantamount to using a PTL to acquire "put" permission on the slot's MailBox field. Finally, having obtained exclusive "put" permission on the slot, put() stores the message value into the slot's MailBox. Take() similarly advances TakeCursor, identifying a slot, and then acquires and secures "take" permission on a slot by waiting for Turn. Take() then waits for the slot's MailBox to become non-empty, extracts the message, and clears MailBox. Finally, take() advances the slot's Turn field, which releases both "put" and "take" access to the slot's MailBox. Note the asymmetry : put() acquires "put" access to the slot, but take() releases that lock. At any given time, for a given slot in a PTLQueue, at most one thread has "put" access and at most one thread has "take" access. This restricts concurrency from general MPMC to 1-vs-1. We have 2 ticket locks -- one for put() and one for take() -- each with its own "ticket" variable in the form of the corresponding cursor, but they share a single "Grant" egress variable in the form of the slot's Turn variable. Advancing the PutCursor, for instance, serves two purposes. First, we obtain a unique ticket which identifies a slot. Second, incrementing the cursor is the doorway protocol step to acquire the per-slot mutual exclusion "put" lock. The cursors and operations to increment those cursors serve double-duty : slot-selection and ticket assignment for locking the slot's MailBox field. At any given time a slot MailBox field can be in one of the following states: empty with no pending operations -- neutral state; empty with one or more waiting take() operations pending -- deficit; occupied with no pending operations; occupied with one or more waiting put() operations -- surplus; empty with a pending put() or pending put() and take() operations -- transitional; or occupied with a pending take() or pending put() and take() operations -- transitional. The partial put() and take() operators can be implemented with an atomic fetch-and-increment operation, which may confer a performance advantage over a CAS-based loop. In addition we have independent PutCursor and TakeCursor cursors. Critically, a put() operation modifies PutCursor but does not access the TakeCursor and a take() operation modifies the TakeCursor cursor but does not access the PutCursor. This acts to reduce coherence traffic relative to some other queue designs. It's worth noting that slow threads or obstruction in one slot (or "lane") does not impede or obstruct operations in other slots -- this gives us some degree of obstruction isolation. PTLQueue is not lock-free, however. The implementation above is expressed with polite busy-waiting (Pause) but it's trivial to implement per-slot parking and unparking to deschedule waiting threads. It's also easy to convert the queue to a more general deque by replacing the PutCursor and TakeCursor cursors with Left/Front and Right/Back cursors that can move either direction. Specifically, to push and pop from the "left" side of the deque we would decrement and increment the Left cursor, respectively, and to push and pop from the "right" side of the deque we would increment and decrement the Right cursor, respectively. We used a variation of PTLQueue for message passing in our recent OPODIS 2013 paper. ul { list-style:none; padding-left:0; padding:0; margin:0; margin-left:0; } ul#myTagID { padding: 0px; margin: 0px; list-style:none; margin-left:0;} -- -- There's quite a bit of related literature in this area. I'll call out a few relevant references: Wilson's NYU Courant Institute UltraComputer dissertation from 1988 is classic and the canonical starting point : Operating System Data Structures for Shared-Memory MIMD Machines with Fetch-and-Add. Regarding provenance and priority, I think PTLQueue or queues effectively equivalent to PTLQueue have been independently rediscovered a number of times. See CB-Queue and BNPBV, below, for instance. But Wilson's dissertation anticipates the basic idea and seems to predate all the others. Gottlieb et al : Basic Techniques for the Efficient Coordination of Very Large Numbers of Cooperating Sequential Processors Orozco et al : CB-Queue in Toward high-throughput algorithms on many-core architectures which appeared in TACO 2012. Meneghin et al : BNPVB family in Performance evaluation of inter-thread communication mechanisms on multicore/multithreaded architecture Dmitry Vyukov : bounded MPMC queue (highly recommended) Alex Otenko : US8607249 (highly related). John Mellor-Crummey : Concurrent queues: Practical fetch-and-phi algorithms. Technical Report 229, Department of Computer Science, University of Rochester Thomasson : FIFO Distributed Bakery Algorithm (very similar to PTLQueue). Scott and Scherer : Dual Data Structures I'll propose an optimization left as an exercise for the reader. Say we wanted to reduce memory usage by eliminating inter-slot padding. Such padding is usually "dark" memory and otherwise unused and wasted. But eliminating the padding leaves us at risk of increased false sharing. Furthermore lets say it was usually the case that the PutCursor and TakeCursor were numerically close to each other. (That's true in some use cases). We might still reduce false sharing by incrementing the cursors by some value other than 1 that is not trivially small and is coprime with the number of slots. Alternatively, we might increment the cursor by one and mask as usual, resulting in a logical index. We then use that logical index value to index into a permutation table, yielding an effective index for use in the slot array. The permutation table would be constructed so that nearby logical indices would map to more distant effective indices. (Open question: what should that permutation look like? Possibly some perversion of a Gray code or De Bruijn sequence might be suitable). As an aside, say we need to busy-wait for some condition as follows : "while C == 0 : Pause". Lets say that C is usually non-zero, so we typically don't wait. But when C happens to be 0 we'll have to spin for some period, possibly brief. We can arrange for the code to be more machine-friendly with respect to the branch predictors by transforming the loop into : "if C == 0 : for { Pause; if C != 0 : break; }". Critically, we want to restructure the loop so there's one branch that controls entry and another that controls loop exit. A concern is that your compiler or JIT might be clever enough to transform this back to "while C == 0 : Pause". You can sometimes avoid this by inserting a call to a some type of very cheap "opaque" method that the compiler can't elide or reorder. On Solaris, for instance, you could use :"if C == 0 : { gethrtime(); for { Pause; if C != 0 : break; }}". It's worth noting the obvious duality between locks and queues. If you have strict FIFO lock implementation with local spinning and succession by direct handoff such as MCS or CLH,then you can usually transform that lock into a queue. Hidden commentary and annotations - invisible : * And of course there's a well-known duality between queues and locks, but I'll leave that topic for another blog post. * Compare and contrast : PTLQ vs PTL and MultiLane * Equivalent : Turn; seq; sequence; pos; position; ticket * Put = Lock; Deposit Take = identify and reserve slot; wait; extract & clear; unlock * conceptualize : Distinct PutLock and TakeLock implemented as ticket lock or PTL Distinct arrival cursors but share per-slot "Turn" variable provides exclusive role-based access to slot's mailbox field put() acquires exclusive access to a slot for purposes of "deposit" assigns slot round-robin and then acquires deposit access rights/perms to that slot take() acquires exclusive access to slot for purposes of "withdrawal" assigns slot round-robin and then acquires withdrawal access rights/perms to that slot At any given time, only one thread can have withdrawal access to a slot at any given time, only one thread can have deposit access to a slot Permissible for T1 to have deposit access and T2 to simultaneously have withdrawal access * round-robin for the purposes of; role-based; access mode; access role mailslot; mailbox; allocate/assign/identify slot rights; permission; license; access permission; * PTL/Ticket hybrid Asymmetric usage ; owner oblivious lock-unlock pairing K-exclusion add Grant cursor pass message m from lock to unlock via Slots[] array Cursor performs 2 functions : + PTL ticket + Assigns request to slot in round-robin fashion Deconstruct protocol : explication put() : allocate slot in round-robin fashion acquire PTL for "put" access store message into slot associated with PTL index take() : Acquire PTL for "take" access // doorway step seq = fetchAdd (&Grant, 1) s = &Slots[seq & Mask] // waiting phase while s-Turn != seq : pause Extract : wait for s-mailbox to be full v = s-mailbox s-mailbox = null Release PTL for both "put" and "take" access s-Turn = seq + Mask + 1 * Slot round-robin assignment and lock "doorway" protocol leverage the same cursor and FetchAdd operation on that cursor FetchAdd (&Cursor,1) + round-robin slot assignment and dispersal + PTL/ticket lock "doorway" step waiting phase is via "Turn" field in slot * PTLQueue uses 2 cursors -- put and take. Acquire "put" access to slot via PTL-like lock Acquire "take" access to slot via PTL-like lock 2 locks : put and take -- at most one thread can access slot's mailbox Both locks use same "turn" field Like multilane : 2 cursors : put and take slot is simple 1-capacity mailbox instead of queue Borrow per-slot turn/grant from PTL Provides strict FIFO Lock slot : put-vs-put take-vs-take at most one put accesses slot at any one time at most one put accesses take at any one time reduction to 1-vs-1 instead of N-vs-M concurrency Per slot locks for put/take Release put/take by advancing turn * is instrumental in ... * P-V Semaphore vs lock vs K-exclusion * See also : FastQueues-excerpt.java dice-etc/queue-mpmc-bounded-blocking-circular-xadd/ * PTLQueue is the same as PTLQB - identical * Expedient return; ASAP; prompt; immediately * Lamport's Bakery algorithm : doorway step then waiting phase Threads arriving at doorway obtain a unique ticket number Threads enter in ticket order * In the terminology of Reed and Kanodia a ticket lock corresponds to the busy-wait implementation of a semaphore using an eventcount and a sequencer It can also be thought of as an optimization of Lamport's bakery lock was designed for fault-tolerance rather than performance Instead of spinning on the release counter, processors using a bakery lock repeatedly examine the tickets of their peers --

    Read the article

  • Is there a "golden ratio" in coding?

    - by badallen
    My coworkers and I often come up with silly ideas such as adding entries to Urban Dictionary that are inappropriate but completely make sense if you are a developer. Or making rap songs that are about delegates, reflections or closures in JS... Anyhow, here is what I brought up this afternoon which was immediately dismissed to be a stupid idea. So I want to see if I can get redemptions here. My idea is coming up with a Golden Ratio (or in the neighborhood of) between the number of classes per project versus the number of methods/functions per class versus the number of lines per method/function. I know this is silly and borderline, if not completely, useless, but just think of all the legacy methods or classes you have encountered that are absolutely horrid - like methods with 10000 lines or classes with 10000 methods. So Golden Ratio, anyone? :)

    Read the article

  • Q&amp;A: What is the UK pricing for the Windows Azure CDN?

    - by Eric Nelson
    The pricing for Windows Azure Content Delivery Network (CDN) was announced last week. The prices are: £0.091 per GB transferred from North America & Europe locations £0.1213 per GB transferred from other locations £0.0061 per 10,000 transactions CDN rates are effective for all billing periods that begin subsequent to June 30, 2010. All usage for billing periods beginning prior to July 1, 2010 will not be charged. To help you determine which pricing plan best suits your needs, please review the comparison table, which includes the CDN information. Steven Nagy has also done an interesting follow up post on CDN. Related Links: Q&A- How can I calculate the TCO and ROI when considering the Windows Azure Platform? Q&A- When do I get charged for compute hours on Windows Azure? Q&A- What are the UK prices for the Windows Azure Platform

    Read the article

  • Ti sei perso l'Oracle EPM Live Webcast sul Project Planning? Ora puoi rivederlo

    - by antonella.buonagurio
    Se non hai potuto seguire l'ultimo webcast EPM dedicato al Project Planning puoi rivederlo a questo link. Il webcast, che fa parte di una serie di live webseminar  dedicati ai professionisti dell'area amministrazione finanza e controllo, è focalizzato sul processo di budgeting, forecasting e controllo di gestione per commessa e delle attività a progetto in ambito economico-finanziario. Durante il webseminar viene presentata  l'integrazione funzionale di Oracle Hyperion EPM System con le altre soluzioni Oracle per il project planning & management. Non perdere l'ultimo appuntamento prima delle vacanze! 13 luglio Oracle EPM Live webcast:  Predictive Planning clicca qui per saperne di più!

    Read the article

  • Introdução ao NHibernate on TechDays 2010

    - by Ricardo Peres
    I’ve been working on the agenda for my presentation titled Introdução ao NHibernate that I’ll be giving on TechDays 2010, and I would like to request your assistance. If you have any subject that you’d like me to talk about, you can suggest it to me. For now, I’m thinking of the following issues: Domain Driven Design with NHibernate Inheritance Mapping Strategies (Table Per Class Hierarchy, Table Per Type, Table Per Concrete Type, Mixed) Mappings (hbm.xml, NHibernate Attributes, Fluent NHibernate, ConfORM) Supported querying types (ID, HQL, LINQ, Criteria API, QueryOver, SQL) Entity Relationships Custom Types Caching Interceptors and Listeners Advanced Usage (Duck Typing, EntityMode Map, …) Other projects (NHibernate Validator, NHibernate Search, NHibernate Shards, …) ASP.NET Integration ASP.NET Dynamic Data Integration WCF Data Services Integration Comments?

    Read the article

  • Oracle Applications Day 2012. Experience the Global Innovation of Management Applications

    - by antonella.buonagurio
    1024x768 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} 1024x768 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} 10 ottobre 2012 – Milano, East End Studios | 17 ottobre 2012 - Roma, Officine Farneto Partecipa all’appuntamento dedicato alla comunità di Clienti e Partner per fare networking e condividere le esperienze sulle soluzioni più innovative per affrontare le sfide attuali e future. Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} A Milano (10/10/2012) interverranno, tra gli altri:  Enrico Ancona, Amministratore Delegato - Imperia & Monferrina e Business Reply  Massimiliano Gerli, CIO - Amplifon e Michele Paolin, Senior Manager - Deloitte eXtended Business Services A Roma (17/10/2012) interverranno, tra gli altri: Giulio Carone, CFO - Enel Green Power e Claudio Arcudi, Senior Executive - Accenture Gianluca D’Aniello, CIO - Sky e Giorgio Pitruzzello, Manager - Deloitte Consulting Spartaco Parente, EPD Change & Label Control - Abbott e Business Reply Sono inoltre previsti i contributi delle aziende Abbott, Aeroporto di Napoli, Amplifon, Dema Aerospace, Enel Green Power, Fiera Milano, Imperia & Monferrina, La Rinascente, Safilo, Sky, Spal,Technogym, Tiscali e Tivù che parleranno di: Innovation for Human Resources Performance Management Excellence Empower Applications with Technology (Milano) Applications for Public Sector (Roma) Next Generation Global Operations Customer Experience Revolution Oltre dieci Instant Workshop ti permetteranno di conoscere e condividere l’esperienza dei Partner e delle aziende che utilizzano le soluzioni Oracle.In più, oltre dieci Instant Workshop per conoscere e condividere l’esperienza dei Partner e delle aziende che utilizzano con successo le soluzioni Oracle. Iscriviti sul sito Partecipa al concorso fotografico Oracle I.M.A.G.E. e vinci il tuo iPad! Scatta le immagini che per te descrivono i cinque concept dell’evento (Innovation, Management, Applications, Global, Experience) e inviale per e-mail. Per iscriverti al contest visita la pagina Concorso sul sito Non perdere l’evento più “social cool” dell’anno!

    Read the article

  • detecting when you are going to reach your hit limit for Google Analytics free account

    - by crmpicco
    I am a user of a free Google Analytics account and i'm slightly concerned that I may be approaching the 10,000,000 hit (Pageviews, Events etc) per month. Google state in their documentation: These limits apply to the Web Property / Property / Tracking ID. 10 million hits per month per property If you go over this limit, the Google Analytics team might contact you and ask you upgrade to Premium or implement client sampling to reduce the amount of data being sent to Google Analytics. However, I note that there is nothing to say that you can review or check up on your current usage for the month. I have administrator access to the Google Analytics account, but I see no feature that lets me check up on my monthly usage. I don't know if Google offer this, either by means of the admin interface or via their support channels - but it would certainly be a useful feature. Is there anyway for a free GA user to obtain this information?

    Read the article

  • App Fabric Service Bus and Access Control Pricing

    - by kaleidoscope
    The Service Bus costs $3.99 per Connection-month on a consumption basis for individually provisioned connections. Data transfers charges would also apply. Or, if you are able to forecast your needs ahead of time, you can purchase “Packs” of Connections. For example: $9.95 for a pack of 5 Connections, $49.75 for a pack of 25, $199.00 for a pack of 100, or $995 for a pack of 500, plus data transfer charges. Connection Packs represent an effective rate of $1.99 per Connection-month. Access Control will be priced at $1.99 per 100,000 Transactions, which includes token requests and management operations, plus associated data transfer. Typically, Service Bus developers depend on Access Control to secure their Connections. More Information: http://azurefeeds.com/post/865/Announcing_Windows_Azure_platform_commercial_offer_availability_and_updated_AppFabric_pricing.aspx   Amit, S

    Read the article

  • I manager della logistica a confronto

    - by Paolo Leveghi
    Il 4 di Aprile scorso una quindicina di manager della logistica appartenenti a diversi settori industriali (Retail, Consumer Goods, Natural Resources, etc) si sono ritrovati per un workshop di lavoro oganizzato da Oracle con la collaborazione di Assologistica. Il tema era libero: di cosa avreste bisogno per migliorare la logistica delle vostre aziende?  La discussione è stata viva e durata per più di tre ore. Gli spunti della serata, assieme a quelli che verranno fuori dall'analogo incontro che si svolgerà il 18 Aprile prossimo, saranno parte di una presentazione che verrà preparata da Assologistica e distribuita al suo network.

    Read the article

  • Innovare e creare valore si può ancora fare?

    - by Silvia Valgoi
    In un momento in cui parole come social networking, Web 2.0, e-commerce, mobilità e multicanalità, cloud computing sono sulla bocca di tutti abbiamo deciso di fermare questo turbinio di bla, bla, bla e prenderci del tempo per condividerne con voi significati ed opportunità. Questi sono gli obiettivi del Sales & Marketing Summit che si terrà il prossimo 28 marzo 2012: Conoscere in anteprima Oracle Fusion CRM, la soluzione di nuova generazione per migliorare e incrementare l'efficacia dei processi di Vendita e Marketing. Scoprire come costruire i processi più innovativi di Customer Experience. Incontrare i nostri esperti e sperimentare le nuove soluzioni di Oracle grazie alle Sessioni Interattive dedicate a Fusion CRM e alla Customer Experience. Confrontarti e condividere idee per innovare   Ti aspettiamo!

    Read the article

  • IX eCommerce Forum: Oracle ed Euronics presentano il loro caso di successo

    - by Claudia Caramelli-Oracle
    Promosso da Netcomm, l'evento ha raggiunto la nona edizione. La tematica principale permette di indagare le dinamiche di tutta la filiera del commercio elettronico, offrendo spunti utili grazie al coinvolgimento di ospiti illustri e relatori. L'e-Commerce Forum è il luogo ideale per scoprire le opportunità del mercato italiano.Oracle, insieme a Reply, ha organizzato un workshop lunch rivolto a tutti coloro che sono interessati a sentire storie di successo circa come la piattaforma eCommerce di Oracle è stata implementata con successo. Il testimonial in questa occasione è stato Euronics. Abbiamo avuto in sala quasi 40 persone che hanno trascorso la loro pausa pranzo con noi! La tematica del resto è attuale e in continua evoluzione/espansione: l'interesse è alto e Oracle offre i mezzi più all'avanguardia per costruire la propria storia di successo proiettando le altre realtà sempre più avanti nel commercio elettronico.Per maggiori informazioni scrivi a Silvia Valgoi

    Read the article

  • Fastest bit-blit in C# ?

    - by AttackingHobo
    I know there is Unity, and XNA that both use C#, but I am don't know what else I could use. The reason I say C# is that the syntax and style is similar to AS3, which I am familiar with, and I want to choose the correct framework to start learning with. What should I use to be able to do the most possible bit-blit(direct pixel copy) objects per frame. EDIT: I should not need to add this, but I am looking for the most possible amount of objects per frame because I am making a few Bullet-Hell SHMUPS. I need thousands and thousands of bullets, particles, and hundreds of enemies on the screen at once. I am looking for a solution to do as many bit-blit operations per frame, I am not looking for a general purpose engine. EDIT2: I want bit-blitting because I do not want to exclude people who have lower end video cards but a fast processor from playing my games.

    Read the article

  • SOA, Java EE and data organization

    - by jolasveinn
    At the company I work for, we're currently splitting up our monolith solution into a number of small services (SOA). Many of the services are small, so we'd like to deploy a number of these services on the same application server, JBoss 7.1 in this case. As per the SOA philosophy, the independence of each service and the teams working on them is very important. What would be the best way to organize the data? Use one schema per service Would you use one datasource per schema in the application server? Or use one datasource, prefixing all DB object names with the schema name in some transparent manner? Use a shared schema, but evading any naming collisions by requiring each service to use a distinct prefix for all DB objects Other options? Am I maybe thinking this completely wrong here? :)

    Read the article

  • How to design a leaderboard?

    - by PeterK
    This sounds like an easy thing but when i considering the following Many players Some have played many games and some just started Different type of statistics ...on what information should the actual ranking be based on. I am planning to display the board in a UITableView so there is limited space available per player. However, I am not bound to the UITableView if there is a better solution. This is a quiz game and the information i am currently capturing per player is: #games played totally #games played per game type (current version have only one game type) #questions answered #correct answers Maybe i should include additional information. I have been thinking about having a leaderboard property page where the player can decide on what basis the leaderboard should display information but would like to avoid the complexity in that. However, if that is needed i will do it. Anyone that can give me some advice on how to design the presentation of this would be highly appreciated?

    Read the article

  • What constitutes proper use of threads in programming?

    - by Smith
    I am tired of hearing people recommend that you should use only one thread per process, while many programs use up to 100 per process! take for example some common programs vb.net ide uses about 25 thread when not debugging System uses about 100 chrome uses about 19 Avira uses more than about 50 Any time I post a thread related question, I am reminded almost every time that I should not use more that one thread per process, and all the programs I mention above are ruining on my system with a single processor. What constitutes proper use of threads in programming? Please make general comment, but I'd prefer .NET framework thanks EDIT changed processor to process

    Read the article

  • Google Maps API: Premier License or excess map loads?

    - by j0nes
    I am currently looking for a way on how to deal with the Google Maps API usage limits. I am planning a redesign of our page that will probably get around 2 million map loads per month. This will surely break the usage limit of 750000 map loads per month available in the free version. If we pay for excess map loads, this means we would have to pay 5000$ per month. The other option would be to use a Premier license, however there is very few information available on the usage limits for this and the price. I have filled the request form to get a custom offer from Google, but I did not get any response yet. Can anyone of the Premier license holders tell me which option will be cheaper for my usage pattern, paying for Premier license or paying for excess map loads?

    Read the article

  • Extremely Hybrid Game requirements

    - by tugrul büyükisik
    What system specifications would a game need if it was: Total players per planet: ~20000 Total players per team:~1M Total players per map(small volume of space or small surface over a planet): ~2000 Total players: ~10M(world has more players than this amount i think) Two of the players are commanders of opposite quadrants(from HUD of a strategy game). Lots of players use space-crafts as a captain(like 3d fps and rts). Many many players control consoles in those space-crafts as under command of captains.(fps ) Some players are still in stone-age trying to reinvent wheel in some planet. Players design and construct any vehicles they have. With good physics engine Has puzzles inside. Everyone get experience by doing stuff(RPG). Commerce, income or totally different resource-based group(like starcraft) Player classes(primitive: cunning and strong, wrapped: healthy, wealthy) Arcade top-down style firing with ships when people get bored very low chance of miraculous things.(mediclorians, wormholes, bugs) Different game-modes: persistent(living world), resetted periodically(a new chance for noobs), instant(pre-built space + hack&slash) I suspect this would need 128GB ram and 2048 cores.

    Read the article

  • Oracle TimesTen In-Memory Database Performance on SPARC T4-2

    - by Brian
    The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T4 processor platforms running Oracle Solaris 11 providing unsurpassed scalability, performance, upgradability, protection of investment and return on investment. The following demonstrate the value of combining Oracle TimesTen In-Memory Database with SPARC T4 servers and Oracle Solaris 11: On a Mobile Call Processing test, the 2-socket SPARC T4-2 server outperforms: Oracle's SPARC Enterprise M4000 server (4 x 2.66 GHz SPARC64 VII+) by 34%. Oracle's SPARC T3-4 (4 x 1.65 GHz SPARC T3) by 2.7x, or 5.4x per processor. Utilizing the TimesTen Performance Throughput Benchmark (TPTBM), the SPARC T4-2 server protects investments with: 2.1x the overall performance of a 4-socket SPARC Enterprise M4000 server in read-only mode and 1.5x the performance in update-only testing. This is 4.2x more performance per processor than the SPARC64 VII+ 2.66 GHz based system. 10x more performance per processor than the SPARC T2+ 1.4 GHz server. 1.6x better performance per processor than the SPARC T3 1.65 GHz based server. In replication testing, the two socket SPARC T4-2 server is over 3x faster than the performance of a four socket SPARC Enterprise T5440 server in both asynchronous replication environment and the highly available 2-Safe replication. This testing emphasizes parallel replication between systems. Performance Landscape Mobile Call Processing Test Performance System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 218,400 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 162,900 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 80,400 TimesTen Performance Throughput Benchmark (TPTBM) Read-Only System Processor Sockets/Cores/Threads Tps SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 7.9M SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 6.5M M4000 SPARC64 VII+, 2.66 GHz 4 16 32 3.1M T5440 SPARC T2+, 1.4 GHz 4 32 256 3.1M TimesTen Performance Throughput Benchmark (TPTBM) Update-Only System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 547,800 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 363,800 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 240,500 TimesTen Replication Tests System Processor Sockets/Cores/Threads Asynchronous 2-Safe SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 38,024 13,701 SPARC T5440 SPARC T2+, 1.4 GHz 4 32 256 11,621 4,615 Configuration Summary Hardware Configurations: SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 4 x 300 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head SPARC T3-4 server 4 x SPARC T3 processors, 1.6 GHz 512 GB memory 1 x 8 Gbs FC Qlogic HBA 8 x 146 GB internal disks 1 x Sun Fire X4275 server configured as COMSTAR head SPARC Enterprise M4000 server 4 x SPARC64 VII+ processors, 2.66 GHz 128 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 2 x 146 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head Software Configuration: Oracle Solaris 11 11/11 Oracle TimesTen 11.2.2.4 Benchmark Descriptions TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The workload can test read-only, update-only, delete and insert operations as required. Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources. Parallel Replication tests using both asynchronous and 2-Safe replication methods. For asynchronous replication, transactions are processed in batches to maximize the throughput capabilities of the replication server and network. In 2-Safe replication, also known as no data-loss or high availability, transactions are replicated between servers immediately emphasizing low latency. For both environments, performance is measured in the number of parallel replication servers and the maximum transactions-per-second for all concurrent processes. See Also SPARC T4-2 Server oracle.com OTN Oracle TimesTen In-Memory Database oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

    Read the article

  • Developing an Implementation Plan with Iterations by Russ Pitts

    - by user535886
    Developing an Implementation Plan with Iterations by Russ Pitts  Ok, so you have come to grips with understanding that applying the iterative concept, as defined by OUM is simply breaking up the project effort you have estimated for each phase into one or more six week calendar duration blocks of work. Idea being the business user(s) or key recipient(s) of work product(s) being developed never go longer than six weeks without having some sort of review or prototyping of the work results for an iteration…”think-a-little”, “do-a-little”, and “show-a-little” in a six week or less timeframe…ideally the business user(s) or key recipients(s) are involved throughout. You also understand the OUM concept that you only plan for that which you have knowledge of. The concept further defined, a project plan initially is developed at a high-level, and becomes more detailed as project knowledge grows. Agreeing to this concept means you also have to admit to the fallacy that one can plan with precision beyond six weeks into a project…Anything beyond six weeks is a best guess in most cases when dealing with software implementation projects. Project planning, as defined by OUM begins with the Implementation Plan view, which is a very high-level perspective of the effort estimated for each of the five OUM phases, as well as the number of iterations within each phase. You might wonder how can you predict the number of iterations for each phase at this early point in the project. Remember project planning is not an exact science, and initially is high-level and abstract in nature, and then becomes more detailed and precise as the project proceeds. So where do you start in defining iterations for each phase for a project? The following are three easy steps to initially define the number of iterations for each phase: Step 1 => Start with identifying the known factors… …Prior to starting a project you should know: · The agreed upon time-period for an iteration (e.g 6 weeks, or 4 weeks, or…) within a phase (recommend keeping iteration time-period consistent within a phase, if not for the entire project) · The number of resources available for the project · The number of total number of man-day (effort) you have estimated for each of the five OUM phases of the project · The number of work days for a week Step 2 => Calculate the man-days of effort required for an iteration within a phase… Lets assume for the sake of this example there are 10 project resources, and you have estimated 2,536 man-days of work effort which will need to occur for the elaboration phase of the project. Let’s also assume a week for this project is defined as 5 business days, and that each iteration in the elaboration phase will last a calendar duration of 6 weeks. A simple calculation is performed to calculate the daily burn rate for a single iteration, which produces a result of… ((Number of resources * days per week) * duration of iteration) = Number of days required per iteration ((10 resources * 5 days/week) * 6 weeks) = 300 man days of effort required per iteration Step 3 => Calculate the number of iterations that can occur within a phase Next calculate the number of iterations that can occur for the amount of man-days of effort estimated for the phase being considered… (number of man-days of effort estimated / number of man-days required per iteration) = # of iterations for phase (2,536 man-days of estimated effort for phase / 300 man days of effort required per iteration) = 8.45 iterations, which should be rounded to a whole number such as 9 iterations* *Note - It is important to note this is an approximate calculation, not an exact science. This particular example is a simple one, which assumes all resources are utilized throughout the phase, including tech resources, etc. (rounding down or up to a whole number based on project factor considerations). It is also best in many cases to round up to higher number, as this provides some calendar scheduling contingency.

    Read the article

  • Detect Unicode Usage in SQL Column

    One optimization you can make to a SQL table that is overly large is to change from nvarchar (or nchar) to varchar (or char).  Doing so will cut the size used by the data in half, from 2 bytes per character (+ 2 bytes of overhead for varchar) to only 1 byte per character.  However, you will lose the ability to store Unicode characters, such as those used by many non-English alphabets.  If the tables are storing user-input, and your application is or might one day be used internationally, its likely that using Unicode for your characters is a good thing.  However, if instead the data is being generated by your application itself or your development team (such as lookup data), and you can be certain that Unicode character sets are not required, then switching such columns to varchar/char can be an easy improvement to make. Avoid Premature Optimization If you are working with a lookup table that has a small number of rows, and is only ever referenced in the application by its numeric ID column, then you wont see any benefit to using varchar vs. nvarchar.  More generally, for small tables, you wont see any significant benefit.  Thus, if you have a general policy in place to use nvarchar/nchar because it offers more flexibility, do not take this post as a recommendation to go against this policy anywhere you can.  You really only want to act on measurable evidence that suggests that using Unicode is resulting in a problem, and that you wont lose anything by switching to varchar/char. Obviously the main reason to make this change is to reduce the amount of space required by each row.  This in turn affects how many rows SQL Server can page through at a time, and can also impact index size and how much disk I/O is required to respond to queries, etc.  If for example you have a table with 100 million records in it and this table has a column of type nchar(5), this column will use 5 * 2 = 10 bytes per row, and with 100M rows that works out to 10 bytes * 100 million = 1000 MBytes or 1GB.  If it turns out that this column only ever stores ASCII characters, then changing it to char(5) would reduce this to 5*1 = 5 bytes per row, and only 500MB.  Of course, if it turns out that it only ever stores the values true and false then you could go further and replace it with a bit data type which uses only 1 byte per row (100MB  total). Detecting Whether Unicode Is In Use So by now you think that you have a problem and that it might be alleviated by switching some columns from nvarchar/nchar to varchar/char but youre not sure whether youre currently using Unicode in these columns.  By definition, you should only be thinking about this for a column that has a lot of rows in it, since the benefits just arent there for a small table, so you cant just eyeball it and look for any non-ASCII characters.  Instead, you need a query.  Its actually very simple: SELECT DISTINCT(CategoryName)FROM CategoriesWHERE CategoryName <> CONVERT(varchar, CategoryName) Summary Gregg Stark for the tip. Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

    Read the article

  • ORE graphics using Remote Desktop Protocol

    - by Sherry LaMonica
    Oracle R Enterprise graphics are returned as raster, or bitmap graphics. Raster images consist of tiny squares of color information referred to as pixels that form points of color to create a complete image. Plots that contain raster images render quickly in R and create small, high-quality exported image files in a wide variety of formats. However, it is a known issue that the rendering of raster images can be problematic when creating graphics using a Remote Desktop connection. Raster images do not display in the windows device using Remote Desktop under the default settings. This happens because Remote Desktop restricts the number of colors when connecting to a Windows machine to 16 bits per pixel, and interpolating raster graphics requires many colors, at least 32 bits per pixel.. For example, this simple embedded R image plot will be returned in a raster-based format using a standalone Windows machine:  R> library(ORE) R> ore.connect(user="rquser", sid="orcl", host="localhost", password="rquser", all=TRUE)  R> ore.doEval(function() image(volcano, col=terrain.colors(30))) Here, we first load the ORE packages and connect to the database instance using database login credentials. The ore.doEval function executes the R code within the database embedded R engine and returns the image back to the client R session. Over a Remote Desktop connection under the default settings, this graph will appear blank due to the restricted number of colors. Users who encounter this issue have two options to display ORE graphics over Remote Desktop: either raise Remote Desktop's Color Depth or direct the plot output to an alternate device. Option #1: Raise Remote Desktop Color Depth setting In a Remote Desktop session, all environment variables, including display variables determining Color Depth, are determined by the RCP-Tcp connection settings. For example, users can reduce the Color Depth when connecting over a slow connection. The different settings are 15 bits, 16 bits, 24 bits, or 32 bits per pixel. To raise the Remote Desktop color depth: On the Windows server, launch Remote Desktop Session Host Configuration from the Accessories menu.Under Connections, right click on RDP-Tcp and select Properties.On the Client Settings tab either uncheck LimitMaximum Color Depth or set it to 32 bits per pixel. Click Apply, then OK, log out of the remote session and reconnect.After reconnecting, the Color Depth on the Display tab will be set to 32 bits per pixel.  Raster graphics will now display as expected. For ORE users, the increased color depth results in slightly reduced performance during plot creation, but the graph will be created instead of displaying an empty plot. Option #2: Direct plot output to alternate device Plotting to a non-windows device is a good option if it's not possible to increase Remote Desktop Color Depth, or if performance is degraded when creating the graph. Several device drivers are available for off-screen graphics in R, such as postscript, pdf, and png. On-screen devices include windows, X11 and Cairo. Here we output to the Cairo device to render an on-screen raster graphic.  The grid.raster function in the grid package is analogous to other grid graphical primitives - it draws a raster image within the current plot's grid.  R> options(device = "CairoWin") # use Cairo device for plotting during the session R> library(Cairo) # load Cairo, grid and png libraries  R> library(grid) R> library(png)  R> res <- ore.doEval(function()image(volcano,col=terrain.colors(30))) # create embedded R plot  R> img <- ore.pull(res, graphics = TRUE)$img[[1]] # extract image  R> grid.raster(as.raster(readPNG(img)), interpolate = FALSE) # generate raster graph R> dev.off() # turn off first device   By default, the interpolate argument to grid.raster is TRUE, which means that what is actually drawn by R is a linear interpolation of the pixels in the original image. Setting interpolate to FALSE uses a sample from the pixels in the original image.A list of graphics devices available in R can be found in the Devices help file from the grDevices package: R> help(Devices)

    Read the article

< Previous Page | 31 32 33 34 35 36 37 38 39 40 41 42  | Next Page >