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  • SEO Courses - Tips and Techniques to Enhance Visibility

    Search Engine Optimization (SEO) is the process of optimizing a web site to achieve a higher ranking when a search engine looks for web pages based on particular word or phrase. The SEO courses empower you with the wherewithal to successfully set up and run an optimization program.

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  • Azure, don't give me multiple VMs, give me one elastic VM

    - by FransBouma
    Yesterday, Microsoft revealed new major features for Windows Azure (see ScottGu's post). It all looks shiny and great, but after reading most of the material describing the new features, I still find the overall idea behind all of it flawed: why should I care on how much VMs my web app runs? Isn't that a problem to solve for the Windows Azure engineers / software? And what if I need the file system, why can't I simply get a virtual filesystem ? To illustrate my point, let's use a real example: a product website with a customer system/database and next to it a support site with accompanying database. Both are written in .NET, using ASP.NET and use a SQL Server database each. The product website offers files to download by customers, very simple. You have a couple of options to host these websites: Buy a server, place it in a rack at an ISP and run the sites on that server Use 'shared hosting' with an ISP, which means your sites' appdomains are running on the same machine, as well as the files stored, and the databases are hosted in the same server as the other shared databases. Hire a VM, install your OS of choice at an ISP, and host the sites on that VM, basically the same as the first option, except you don't have a physical server At some cloud-vendor, either host the sites 'shared' or in a VM. See above. With all of those options, scalability is a problem, even the cloud-based ones, though not due to the same reasons: The physical server solution has the obvious problem that if you need more power, you need to buy a bigger server or more servers which requires you to add replication and other overhead Shared hosting solutions are almost always capped on memory usage / traffic and database size: if your sites get too big, you have to move out of the shared hosting environment and start over with one of the other solutions The VM solution, be it a VM at an ISP or 'in the cloud' at e.g. Windows Azure or Amazon, in theory allows scaling out by simply instantiating more VMs, however that too introduces the same overhead problems as with the physical servers: suddenly more than 1 instance runs your sites. If a cloud vendor offers its services in the form of VMs, you won't gain much over having a VM at some ISP: the main problems you have to work around are still there: when you spin up more than one VM, your application must be completely stateless at any moment, including the DB sub system, because what's in memory in instance 1 might not be in memory in instance 2. This might sounds trivial but it's not. A lot of the websites out there started rather small: they were perfectly runnable on a single machine with normal memory and CPU power. After all, you don't need a big machine to run a website with even thousands of users a day. Moving these sites to a multi-VM environment will cause a problem: all the in-memory state they use, all the multi-page transitions they use while keeping state across the transition, they can't do that anymore like they did that on a single machine: state is something of the past, you have to store every byte of state in either a DB or in a viewstate or in a cookie somewhere so with the next request, all state information is available through the request, as nothing is kept in-memory. Our example uses a bunch of files in a file system. Using multiple VMs will require that these files move to a cloud storage system which is mounted in each VM so we don't have to store the files on each VM. This might require different file paths, but this change should be minor. What's perhaps less minor is the maintenance procedure in place on the new type of cloud storage used: instead of ftp-ing into a VM, you might have to update the files using different ways / tools. All in all this makes moving an existing website which was written for an environment that's based around a VM (namely .NET with its CLR) overly cumbersome and problematic: it forces you to refactor your website system to be able to be used 'in the cloud', which is caused by the limited way how e.g. Windows Azure offers its cloud services: in blocks of VMs. Offer a scalable, flexible VM which extends with my needs Instead, cloud vendors should offer simply one VM to me. On that VM I run the websites, store my DB and my files. As it's a virtual machine, how this machine is actually ran on physical hardware (e.g. partitioned), I don't care, as that's the problem for the cloud vendor to solve. If I need more resources, e.g. I have more traffic to my server, way more visitors per day, the VM stretches, like I bought a bigger box. This frees me from the problem which comes with multiple VMs: I don't have any refactoring to do at all: I can simply build my website as if it runs on my local hardware server, upload it to the VM offered by the cloud vendor, install it on the VM and I'm done. "But that might require changes to windows!" Yes, but Microsoft is Windows. Windows Azure is their service, they can make whatever change to what they offer to make it look like it's windows. Yet, they're stuck, like Amazon, in thinking in VMs, which forces developers to 'think ahead' and gamble whether they would need to migrate to a cloud with multiple VMs in the future or not. Which comes down to: gamble whether they should invest time in code / architecture which they might never need. (YAGNI anyone?) So the VM we're talking about, is that a low-level VM which runs a guest OS, or is that VM a different kind of VM? The flexible VM: .NET's CLR ? My example websites are ASP.NET based, which means they run inside a .NET appdomain, on the .NET CLR, which is a VM. The only physical OS resource the sites need is the file system, however this too is accessed through .NET. In short: all the websites see is what .NET allows the websites to see, the world as the websites know it is what .NET shows them and lets them access. How the .NET appdomain is run physically, that's the concern of .NET, not mine. This begs the question why Windows Azure doesn't offer virtual appdomains? Or better: .NET environments which look like one machine but could be physically multiple machines. In such an environment, no change has to be made to the websites to migrate them from a local machine or own server to the cloud to get proper scaling: the .NET VM will simply scale with the need: more memory needed, more CPU power needed, it stretches. What it offers to the application running inside the appdomain is simply increasing, but not fragmented: all resources are available to the application: this means that the problem of how to scale is back to where it should be: with the cloud vendor. "Yeah, great, but what about the databases?" The .NET application communicates with the database server through a .NET ADO.NET provider. Where the database is located is not a problem of the appdomain: the ADO.NET provider has to solve that. I.o.w.: we can host the databases in an environment which offers itself as a single resource and is accessible through one connection string without replication overhead on the outside, and use that environment inside the .NET VM as if it was a single DB. But what about memory replication and other problems? This environment isn't simple, at least not for the cloud vendor. But it is simple for the customer who wants to run his sites in that cloud: no work needed. No refactoring needed of existing code. Upload it, run it. Perhaps I'm dreaming and what I described above isn't possible. Yet, I think if cloud vendors don't move into that direction, what they're offering isn't interesting: it doesn't solve a problem at all, it simply offers a way to instantiate more VMs with the guest OS of choice at the cost of me needing to refactor my website code so it can run in the straight jacket form factor dictated by the cloud vendor. Let's not kid ourselves here: most of us developers will never build a website which needs a truck load of VMs to run it: almost all websites created by developers can run on just a few VMs at most. Yet, the most expensive change is right at the start: moving from one to two VMs. As soon as you have refactored your website code to run across multiple VMs, adding another one is just as easy as clicking a mouse button. But that first step, that's the problem here and as it's right there at the beginning of scaling the website, it's particularly strange that cloud vendors refuse to solve that problem and leave it to the developers to solve that. Which makes migrating 'to the cloud' particularly expensive.

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  • Ardour wont start Jack problem

    - by Drew S
    I downloaded Ardour yesterday, it worked, edited an audio file done. Come back today it wont start I get this: Ardour could not start JACK There are several possible reasons: 1) You requested audio parameters that are not supported.. 2) JACK is running as another user. Please consider the possibilities, and perhaps try different parameters. So I try and look at qjackctl to see what happening there. When I try to start JACK I get D-BUS: JACK server could not be started. then Could not connect to JACK server as client. - Overall operation failed. - Unable to connect to server. Please check the messages window for more info. and this is the message box in JACK. 15:22:12.927 Patchbay deactivated. 15:22:12.927 Statistics reset. 15:22:12.944 ALSA connection change. 15:22:12.951 D-BUS: Service is available (org.jackaudio.service aka jackdbus). Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started 15:22:12.959 ALSA connection graph change. 15:22:45.850 ALSA connection graph change. 15:22:46.021 ALSA connection change. 15:22:56.492 ALSA connection graph change. 15:22:56.624 ALSA connection change. 15:23:42.340 D-BUS: JACK server could not be started. Sorry Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started Wed Oct 23 15:23:42 2013: Starting jack server... Wed Oct 23 15:23:42 2013: JACK server starting in realtime mode with priority 10 Wed Oct 23 15:23:42 2013: ERROR: Cannot lock down 82274202 byte memory area (Cannot allocate memory) Wed Oct 23 15:23:42 2013: Acquired audio card Audio0 Wed Oct 23 15:23:42 2013: creating alsa driver ... hw:0|hw:0|1024|2|44100|0|0|nomon|swmeter|-|32bit Wed Oct 23 15:23:42 2013: ERROR: ATTENTION: The playback device "hw:0" is already in use. The following applications are using your soundcard(s) so you should check them and stop them as necessary before trying to start JACK again: pulseaudio (process ID 2553) Wed Oct 23 15:23:42 2013: ERROR: Cannot initialize driver Wed Oct 23 15:23:42 2013: ERROR: JackServer::Open failed with -1 Wed Oct 23 15:23:42 2013: ERROR: Failed to open server Wed Oct 23 15:23:43 2013: Saving settings to "/home/drew/.config/jack/conf.xml" ... 15:26:41.669 Could not connect to JACK server as client. - Overall operation failed. - Unable to connect to server. Please check the messages window for more info. Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started 15:26:49.006 D-BUS: JACK server could not be started. Sorry Wed Oct 23 15:26:48 2013: Starting jack server... Wed Oct 23 15:26:48 2013: JACK server starting in non-realtime mode Wed Oct 23 15:26:48 2013: ERROR: Cannot lock down 82274202 byte memory area (Cannot allocate memory) Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started Wed Oct 23 15:26:48 2013: ERROR: cannot register object path "/org/freedesktop/ReserveDevice1/Audio0": A handler is already registered for /org/freedesktop/ReserveDevice1/Audio0 Wed Oct 23 15:26:48 2013: ERROR: Failed to acquire device name : Audio0 error : A handler is already registered for /org/freedesktop/ReserveDevice1/Audio0 Wed Oct 23 15:26:48 2013: ERROR: Audio device hw:0 cannot be acquired... Wed Oct 23 15:26:48 2013: ERROR: Cannot initialize driver Wed Oct 23 15:26:48 2013: ERROR: JackServer::Open failed with -1 Wed Oct 23 15:26:48 2013: ERROR: Failed to open server Wed Oct 23 15:26:50 2013: Saving settings to "/home/drew/.config/jack/conf.xml" ... 15:26:52.441 Could not connect to JACK server as client. - Overall operation failed. - Unable to connect to server. Please check the messages window for more info. Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started 15:26:55.997 D-BUS: JACK server could not be started. Sorry Wed Oct 23 15:26:55 2013: Starting jack server... Wed Oct 23 15:26:55 2013: JACK server starting in non-realtime mode Wed Oct 23 15:26:55 2013: ERROR: Cannot lock down 82274202 byte memory area (Cannot allocate memory) Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started Wed Oct 23 15:26:55 2013: ERROR: cannot register object path "/org/freedesktop/ReserveDevice1/Audio0": A handler is already registered for /org/freedesktop/ReserveDevice1/Audio0 Wed Oct 23 15:26:55 2013: ERROR: Failed to acquire device name : Audio0 error : A handler is already registered for /org/freedesktop/ReserveDevice1/Audio0 Wed Oct 23 15:26:55 2013: ERROR: Audio device hw:0 cannot be acquired... Wed Oct 23 15:26:55 2013: ERROR: Cannot initialize driver Wed Oct 23 15:26:55 2013: ERROR: JackServer::Open failed with -1 Wed Oct 23 15:26:55 2013: ERROR: Failed to open server Wed Oct 23 15:26:57 2013: Saving settings to "/home/drew/.config/jack/conf.xml" ... 15:26:59.054 Could not connect to JACK server as client. - Overall operation failed. - Unable to connect to server. Please check the messages window for more info. Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started 15:29:24.624 ALSA connection graph change. 15:29:24.641 ALSA connection change. 15:33:11.760 D-BUS: JACK server could not be started. Sorry Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started Wed Oct 23 15:33:11 2013: Starting jack server... Wed Oct 23 15:33:11 2013: JACK server starting in non-realtime mode Wed Oct 23 15:33:11 2013: ERROR: Cannot lock down 82274202 byte memory area (Cannot allocate memory) Wed Oct 23 15:33:11 2013: ERROR: cannot register object path "/org/freedesktop/ReserveDevice1/Audio0": A handler is already registered for /org/freedesktop/ReserveDevice1/Audio0 Wed Oct 23 15:33:11 2013: ERROR: Failed to acquire device name : Audio0 error : A handler is already registered for /org/freedesktop/ReserveDevice1/Audio0 Wed Oct 23 15:33:11 2013: ERROR: Audio device hw:0 cannot be acquired... Wed Oct 23 15:33:11 2013: ERROR: Cannot initialize driver Wed Oct 23 15:33:11 2013: ERROR: JackServer::Open failed with -1 Wed Oct 23 15:33:11 2013: ERROR: Failed to open server Wed Oct 23 15:33:12 2013: Saving settings to "/home/drew/.config/jack/conf.xml" ... 15:34:09.439 Could not connect to JACK server as client. - Overall operation failed. - Unable to connect to server. Please check the messages window for more info. Cannot connect to server socket err = No such file or directory Cannot connect to server request channel jack server is not running or cannot be started

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  • Few Steps For Making Your Website SEO Friendly

    Currently going by the dynamics of the internet every web designer of class is expected to be acquainted with or have a basic working knowledge of search engine optimization tools. Web promotion as an optimization tool for enhancing increased traffic to a given site is one skill web designers just like online marketers require in their respective fields to conquer the market.

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  • SortedDictionary and SortedList

    - by Simon Cooper
    Apart from Dictionary<TKey, TValue>, there's two other dictionaries in the BCL - SortedDictionary<TKey, TValue> and SortedList<TKey, TValue>. On the face of it, these two classes do the same thing - provide an IDictionary<TKey, TValue> interface where the iterator returns the items sorted by the key. So what's the difference between them, and when should you use one rather than the other? (as in my previous post, I'll assume you have some basic algorithm & datastructure knowledge) SortedDictionary We'll first cover SortedDictionary. This is implemented as a special sort of binary tree called a red-black tree. Essentially, it's a binary tree that uses various constraints on how the nodes of the tree can be arranged to ensure the tree is always roughly balanced (for more gory algorithmical details, see the wikipedia link above). What I'm concerned about in this post is how the .NET SortedDictionary is actually implemented. In .NET 4, behind the scenes, the actual implementation of the tree is delegated to a SortedSet<KeyValuePair<TKey, TValue>>. One example tree might look like this: Each node in the above tree is stored as a separate SortedSet<T>.Node object (remember, in a SortedDictionary, T is instantiated to KeyValuePair<TKey, TValue>): class Node { public bool IsRed; public T Item; public SortedSet<T>.Node Left; public SortedSet<T>.Node Right; } The SortedSet only stores a reference to the root node; all the data in the tree is accessed by traversing the Left and Right node references until you reach the node you're looking for. Each individual node can be physically stored anywhere in memory; what's important is the relationship between the nodes. This is also why there is no constructor to SortedDictionary or SortedSet that takes an integer representing the capacity; there are no internal arrays that need to be created and resized. This may seen trivial, but it's an important distinction between SortedDictionary and SortedList that I'll cover later on. And that's pretty much it; it's a standard red-black tree. Plenty of webpages and datastructure books cover the algorithms behind the tree itself far better than I could. What's interesting is the comparions between SortedDictionary and SortedList, which I'll cover at the end. As a side point, SortedDictionary has existed in the BCL ever since .NET 2. That means that, all through .NET 2, 3, and 3.5, there has been a bona-fide sorted set class in the BCL (called TreeSet). However, it was internal, so it couldn't be used outside System.dll. Only in .NET 4 was this class exposed as SortedSet. SortedList Whereas SortedDictionary didn't use any backing arrays, SortedList does. It is implemented just as the name suggests; two arrays, one containing the keys, and one the values (I've just used random letters for the values): The items in the keys array are always guarenteed to be stored in sorted order, and the value corresponding to each key is stored in the same index as the key in the values array. In this example, the value for key item 5 is 'z', and for key item 8 is 'm'. Whenever an item is inserted or removed from the SortedList, a binary search is run on the keys array to find the correct index, then all the items in the arrays are shifted to accomodate the new or removed item. For example, if the key 3 was removed, a binary search would be run to find the array index the item was at, then everything above that index would be moved down by one: and then if the key/value pair {7, 'f'} was added, a binary search would be run on the keys to find the index to insert the new item, and everything above that index would be moved up to accomodate the new item: If another item was then added, both arrays would be resized (to a length of 10) before the new item was added to the arrays. As you can see, any insertions or removals in the middle of the list require a proportion of the array contents to be moved; an O(n) operation. However, if the insertion or removal is at the end of the array (ie the largest key), then it's only O(log n); the cost of the binary search to determine it does actually need to be added to the end (excluding the occasional O(n) cost of resizing the arrays to fit more items). As a side effect of using backing arrays, SortedList offers IList Keys and Values views that simply use the backing keys or values arrays, as well as various methods utilising the array index of stored items, which SortedDictionary does not (and cannot) offer. The Comparison So, when should you use one and not the other? Well, here's the important differences: Memory usage SortedDictionary and SortedList have got very different memory profiles. SortedDictionary... has a memory overhead of one object instance, a bool, and two references per item. On 64-bit systems, this adds up to ~40 bytes, not including the stored item and the reference to it from the Node object. stores the items in separate objects that can be spread all over the heap. This helps to keep memory fragmentation low, as the individual node objects can be allocated wherever there's a spare 60 bytes. In contrast, SortedList... has no additional overhead per item (only the reference to it in the array entries), however the backing arrays can be significantly larger than you need; every time the arrays are resized they double in size. That means that if you add 513 items to a SortedList, the backing arrays will each have a length of 1024. To conteract this, the TrimExcess method resizes the arrays back down to the actual size needed, or you can simply assign list.Capacity = list.Count. stores its items in a continuous block in memory. If the list stores thousands of items, this can cause significant problems with Large Object Heap memory fragmentation as the array resizes, which SortedDictionary doesn't have. Performance Operations on a SortedDictionary always have O(log n) performance, regardless of where in the collection you're adding or removing items. In contrast, SortedList has O(n) performance when you're altering the middle of the collection. If you're adding or removing from the end (ie the largest item), then performance is O(log n), same as SortedDictionary (in practice, it will likely be slightly faster, due to the array items all being in the same area in memory, also called locality of reference). So, when should you use one and not the other? As always with these sort of things, there are no hard-and-fast rules. But generally, if you: need to access items using their index within the collection are populating the dictionary all at once from sorted data aren't adding or removing keys once it's populated then use a SortedList. But if you: don't know how many items are going to be in the dictionary are populating the dictionary from random, unsorted data are adding & removing items randomly then use a SortedDictionary. The default (again, there's no definite rules on these sort of things!) should be to use SortedDictionary, unless there's a good reason to use SortedList, due to the bad performance of SortedList when altering the middle of the collection.

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  • My Rant About the SEO Specialist

    Clients wishing to avail of search engine optimization services will have an important choice to make. They can choose between hiring SEO specialists or SEO generalists to provide the services they need. SEO specialists are technicians who concentrate on specific aspects of search engine optimization while generalists will take on all aspects of it. This article looks into the pros and cons of employing these service providers.

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  • Five Query Optimizations in MySQL

    Query optimization is an often overlooked part of applications. Sean Hull encourages at least some attention to query optimization up front and helps you identify some of the more common optimizations you may run across.

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  • NUMA-aware placement of communication variables

    - by Dave
    For classic NUMA-aware programming I'm typically most concerned about simple cold, capacity and compulsory misses and whether we can satisfy the miss by locally connected memory or whether we have to pull the line from its home node over the coherent interconnect -- we'd like to minimize channel contention and conserve interconnect bandwidth. That is, for this style of programming we're quite aware of where memory is homed relative to the threads that will be accessing it. Ideally, a page is collocated on the node with the thread that's expected to most frequently access the page, as simple misses on the page can be satisfied without resorting to transferring the line over the interconnect. The default "first touch" NUMA page placement policy tends to work reasonable well in this regard. When a virtual page is first accessed, the operating system will attempt to provision and map that virtual page to a physical page allocated from the node where the accessing thread is running. It's worth noting that the node-level memory interleaving granularity is usually a multiple of the page size, so we can say that a given page P resides on some node N. That is, the memory underlying a page resides on just one node. But when thinking about accesses to heavily-written communication variables we normally consider what caches the lines underlying such variables might be resident in, and in what states. We want to minimize coherence misses and cache probe activity and interconnect traffic in general. I don't usually give much thought to the location of the home NUMA node underlying such highly shared variables. On a SPARC T5440, for instance, which consists of 4 T2+ processors connected by a central coherence hub, the home node and placement of heavily accessed communication variables has very little impact on performance. The variables are frequently accessed so likely in M-state in some cache, and the location of the home node is of little consequence because a requester can use cache-to-cache transfers to get the line. Or at least that's what I thought. Recently, though, I was exploring a simple shared memory point-to-point communication model where a client writes a request into a request mailbox and then busy-waits on a response variable. It's a simple example of delegation based on message passing. The server polls the request mailbox, and having fetched a new request value, performs some operation and then writes a reply value into the response variable. As noted above, on a T5440 performance is insensitive to the placement of the communication variables -- the request and response mailbox words. But on a Sun/Oracle X4800 I noticed that was not the case and that NUMA placement of the communication variables was actually quite important. For background an X4800 system consists of 8 Intel X7560 Xeons . Each package (socket) has 8 cores with 2 contexts per core, so the system is 8x8x2. Each package is also a NUMA node and has locally attached memory. Every package has 3 point-to-point QPI links for cache coherence, and the system is configured with a twisted ladder "mobius" topology. The cache coherence fabric is glueless -- there's not central arbiter or coherence hub. The maximum distance between any two nodes is just 2 hops over the QPI links. For any given node, 3 other nodes are 1 hop distant and the remaining 4 nodes are 2 hops distant. Using a single request (client) thread and a single response (server) thread, a benchmark harness explored all permutations of NUMA placement for the two threads and the two communication variables, measuring the average round-trip-time and throughput rate between the client and server. In this benchmark the server simply acts as a simple transponder, writing the request value plus 1 back into the reply field, so there's no particular computation phase and we're only measuring communication overheads. In addition to varying the placement of communication variables over pairs of nodes, we also explored variations where both variables were placed on one page (and thus on one node) -- either on the same cache line or different cache lines -- while varying the node where the variables reside along with the placement of the threads. The key observation was that if the client and server threads were on different nodes, then the best placement of variables was to have the request variable (written by the client and read by the server) reside on the same node as the client thread, and to place the response variable (written by the server and read by the client) on the same node as the server. That is, if you have a variable that's to be written by one thread and read by another, it should be homed with the writer thread. For our simple client-server model that means using split request and response communication variables with unidirectional message flow on a given page. This can yield up to twice the throughput of less favorable placement strategies. Our X4800 uses the QPI 1.0 protocol with source-based snooping. Briefly, when node A needs to probe a cache line it fires off snoop requests to all the nodes in the system. Those recipients then forward their response not to the original requester, but to the home node H of the cache line. H waits for and collects the responses, adjudicates and resolves conflicts and ensures memory-model ordering, and then sends a definitive reply back to the original requester A. If some node B needed to transfer the line to A, it will do so by cache-to-cache transfer and let H know about the disposition of the cache line. A needs to wait for the authoritative response from H. So if a thread on node A wants to write a value to be read by a thread on node B, the latency is dependent on the distances between A, B, and H. We observe the best performance when the written-to variable is co-homed with the writer A. That is, we want H and A to be the same node, as the writer doesn't need the home to respond over the QPI link, as the writer and the home reside on the very same node. With architecturally informed placement of communication variables we eliminate at least one QPI hop from the critical path. Newer Intel processors use the QPI 1.1 coherence protocol with home-based snooping. As noted above, under source-snooping a requester broadcasts snoop requests to all nodes. Those nodes send their response to the home node of the location, which provides memory ordering, reconciles conflicts, etc., and then posts a definitive reply to the requester. In home-based snooping the snoop probe goes directly to the home node and are not broadcast. The home node can consult snoop filters -- if present -- and send out requests to retrieve the line if necessary. The 3rd party owner of the line, if any, can respond either to the home or the original requester (or even to both) according to the protocol policies. There are myriad variations that have been implemented, and unfortunately vendor terminology doesn't always agree between vendors or with the academic taxonomy papers. The key is that home-snooping enables the use of a snoop filter to reduce interconnect traffic. And while home-snooping might have a longer critical path (latency) than source-based snooping, it also may require fewer messages and less overall bandwidth. It'll be interesting to reprise these experiments on a platform with home-based snooping. While collecting data I also noticed that there are placement concerns even in the seemingly trivial case when both threads and both variables reside on a single node. Internally, the cores on each X7560 package are connected by an internal ring. (Actually there are multiple contra-rotating rings). And the last-level on-chip cache (LLC) is partitioned in banks or slices, which with each slice being associated with a core on the ring topology. A hardware hash function associates each physical address with a specific home bank. Thus we face distance and topology concerns even for intra-package communications, although the latencies are not nearly the magnitude we see inter-package. I've not seen such communication distance artifacts on the T2+, where the cache banks are connected to the cores via a high-speed crossbar instead of a ring -- communication latencies seem more regular.

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  • Fool Proof Guide to SEO

    Search Engine Optimization is now more important than ever. There is a huge competition for almost every imaginable market niche. The goal of optimization is to get pages on top positions in search results.

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  • SEO for single-page content-less Web App

    - by brillout.com
    as written in the title the website on which I try to do Search Engine Optimization has following two properties: doesn't have any content in the SEO sense: it doesn't hold any information and only offers functionality consists of only one page/URL since most of the SEO tips/tricks I read are based on content how do I perform SEO optimization on such a website? for more info: the website is basically just a timer/alarm/stopwatch

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  • Achieving a Strong SEO Rating

    SEO or Search Engine Optimization is a must if you are serious in having your website placed with the search engine, and with great results. There are important guidelines to be followed. It is really not that hard to understand even for beginners. For beginners the term optimization may sound somewhat difficult, when actually it is very doable.

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  • Website Health Check - Keyword Blunders - Part 1

    Website Health Check provides a report on the components of a website. Keyword is one of the most important components. Let's start with it. Keywords are the starting point of Search Engine Optimization (SEO). So, when you make a mistake with the keywords, your whole optimization process becomes a waste of time.

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  • SEO Techniques to Be Used by Every Website

    Search engine optimization is the buzz word in the world of internet. Every website wants to rank high in the search engine listings. There are different techniques and measures that you can take up for the process of search engine optimization. Here are some sure shot techniques that every website should apply in order to rank high.

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  • SQL SERVER Introduction to Extended Events Finding Long Running Queries

    The job of an SQL Consultant is very interesting as always. The month before, I was busy doing query optimization and performance tuning projects for our clients, and this month, I am busy delivering my performance in Microsoft SQL Server 2005/2008 Query Optimization and & Performance Tuning Course. I recently read white paper about Extended [...]...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.

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  • SEO Pricing - How it is Decided

    SEO or SE Optimization is presently the most commonly used and very effective form of advertising. Customers can expect to achieve very high Return on Investment in search engine optimization.

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  • The Benefits of Doing Proper Keyword Research

    First of all, let's get one thing straight: keyword research is the hands down the absolute base for any marketing or search engine optimization campaign. You can't get absolutely anything done without doing proper keyword research first. The simple reason behind this fact is that you will be needing the results provided by keyword services for everything from the actual content of your website, to future search engine optimization campaigns, pay per click campaigns, and so on.

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  • Know More About SEO Software

    SEO optimization is very essential to people who are looking for the current means to enhance the popularity of their sites on the internet. The SEO tool is one that delivers the success of your site and at the same time ensures that you get targeted traffic with ease. There is immense competition on the internet and it is for this reason why you should go in for SEO optimization so that you can have a winning edge over the other players in the online market.

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  • Basic SEO Mistakes

    Search engine optimization mistakes are quite common, and they are made by both seasoned SEO experts, and those who are new to it alike. Search engine optimization is a precise practice, thus there is no such thing as a tiny SEO mistake. The reason for this is that all SEO mistakes, big or small, all produce repercussions, which could affect the ranking if your website in one way or another.

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  • The Benefits of Using Online SEO Tools

    Search Engine Optimization (SEO) can be a labour intensive process. Why not save some time and effort and use a few online tools to help accomplish the task in less time? In this article, I will look at some common tools, and show how they can improve your optimization and save you time.

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  • Make Money Online - Use SEO

    Do you want a method to improve your e-marketing results? Then you have to try to take advantage of search engine optimization (SEO) and social media optimization. In this article we are going to give you six helpful tips on doing just that.

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  • Benefits of LSI Based SEO

    SEO or Search engine optimization is the largely talked regarding Internet technology these days, with online business houses basking under its glory. It is a method of optimizing a website with an extensive combination of tasks that will perk up websites charisma on the different search engines. To make the job simpler, a new tool has been introduced by the SEO experts that came to be identified as LSI or latent semantic indexing. The LSI has changed the world of search engine optimization.

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  • Role of SMO Services in Search Engine Ranking

    Those involved in the web business know very well about all the benefits that come with Social Media Optimization and the added advantages that one gets when Social Media Optimization campaigns are performed on websites. The campaigns are very rigorous and content rich and work on many aspects of the website such as it presence, visibility and certain other things that become evident when the website starts attracting business and starts making an impact.

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  • A New Approach to SEO

    SEO or search engine optimization has officially come out of its infancy, even though the concept might be new to you. If you are one of millions just starting to get their feet wet with search engine optimization, take heart. The basics have not changed much.

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