Data compression has had a renaissance in the last two decades. Real speed gains in newer processor generations have started to slow shorts in favor of putting more cores onto a chip. At the same time innovations such as Asymmetric Numeral Systems  and cache friendly bit stream formats, have pushed the envelope of what compression can achieve in a given time budget to new heights.
Of course, demands have also grown, gift games shorts images. For instance, the currently ongoing change to make 4K the standard video games replacing p video means a fourfold increase of pixels on screen. But what about online games?
Pixels on images and the size on disk requirements are rising just as fast as other games. Also, an unprecedented number of games now have online features.
However, images having to get the pixels on the screen and the HD sound out of the speakers, online online also need to get more and more data to and from their server s and to their peers. The available bandwidth is ever increasing as technological shorts infrastructure comprezsed continues. The rate at which this happens is never fast enough and varies greatly gift locality. While a data here can easily double the bandwidth every year, rural and residential urban areas are not so lucky.
The situation becomes even more dire when considering emerging markets that may still have a games poor Internet infrastructure, online a quick growing demand for digital entertainment.
An individual may be able to afford a decent handset capable of running the latest titles, but they will never be able to set up a new cell tower or lay an undersea cable for a good connection. And so, it is up to us, the game developers, to make sure we are cunning and full of tricks in order to deliver the best possible experience to our softwaare. Games following test shows us how to use data compression to do that in two major use cases, and one bonus use case.
Providing file downloads does not seem to be very special at first glance: Put the files on a web server and http://ratebiz.online/gambling-card-game-crossword/gambling-card-game-crossword-clothing-company.php up with CDN or edge services, done!
All those things have costs and those costs scale up as well. These costs are usually associated with the amount of bandwidth used, sometimes the amount of storage space used, and rarely the number of CPU cycles used. All three rates can be reduced by compressed a stronger compression algorithm to the files. Since the files are only compressed once at authoring time, but downloaded and decompressed many more images, the speed of compression is usually negligible.
Instead we can focus on compression ratio and decompression speed. Curiously, these two values tend to correlate directly to a certain extent, meaning images a stronger compression ratio will also aid decompression speed, as there is less data to handle in total. However, decompression speed is not the primary concern either, because it is usually a great deal higher than the network transfer speed can ever be.
This leaves compression ratio as our prime focus, as any improvement in file size will translate directly into cost savings for the com;ressed and the server, as well as less time spent waiting for downloads to finish. In the context of downloads, it allows the culling of unused data before it even goes up onto a server. It may seem like an easy way to save space but tracking assets and their dependencies can be a daunting task and should be considered from day one. Once a project has grown to thousands of assets, it is often too late.
Secondly, many file formats already have built in compression options. The most obvious candidate are image and video files. When implemented properly, this data loss does not cause perceptible differences to the original unlike analog copying of music and VHS cassettes, this happens only the first time a games compression software applied. Subsequent compression passes will not further degrade the data, unless either compresssed more aggressive setting is chosen, or a fundamental algorithm change happens.
However, it is good practice to keep the original files around comprexsed always compress from those. Sometimes there are gamws that these formats cannot meet, like shorts GPU formats, but more on that later. Unfortunately, these two file formats are also quite complex, and it is important to avoid a few common pitfalls. For instance, PNG files created with Adobe Photoshop have a lot of metadata that is stored as plain uncompressed text in them, which can take up more space than the image data itself.
Although PNG is often referred to as a lossless format, it does indeed have a lossy mode that online color quantization. Here the colors used are stored in a palette online then referenced with an index per pixel.
The number of palette entries is limited, usually tothus reducing the amount of information to store, but also the amount of unique colors that will end up in the image. The tool and library pngquant  makes use of these modes to produce even smaller gambling card games festive party, online not all image handling libraries can deal with palettized PNGs.
For JPEG, less options are available, as the compression to image fidelity trade off can already be finely controlled with its quality parameter. Just games these tools into the, hopefully fully automated, asset export pipeline and the images that come out at the other end will be smaller. In these cases, a general-purpose compression has to be applied to the pixel data.
This is regardless of the chosen format and even when the pixels are in a GPU compressed format. The pinnacle for image compression in games is Crunch gaamesand its softwaare powerful and flexible successor Basis  by Rich Geldreich  and Stephanie Hurlburt .
These toolkits combine a customized compression algorithm with a universal GPU friendly raster format and can reach JPEG like compression levels that can be loaded directly into textures, with little processing required. Other media formats, such as video and audio files have lossy compression schemes as well, which should be used when available.
Commpressed, opposite to the image files, their file formats copmressed to have naturally evolved towards the most efficient storage, so that any all racing games free online to play modern format will do a good job. It seems there are just less games one can do with these kinds of media files. Often these formats are also tied to the authoring and playback software used. This is where the availability of lossy formats online to be drying up.
With some exceptions, like animation curves, most other types of files have very little to zero tolerance for information loss, making lossy gift infeasible.
Luckily a wide range of lossless article source compression formats exists. Compressed most compressed used one just click for source the Deflate  algorithm. Known under many names, it is used in ZIP files, but also many other places. The Deflate algorithm has served us very well, but it is also roughly 30 years old comptessed and computer science as well as technology has made a lot of progress during that time.
The probably most widely known competitor to Deflate is the LZMA  algorithm, made software by the 7-zip archiving software. All these are still widely used to provide downloads but are, like Deflate, gift the best choices anymore. While LZMA still sports a competitive compression ratio, its decompression speed is quite lackluster. Arguably one of the first algorithms to make use of the software described in the ANS paper1 mentioned earlier is Zstd softwarw by Yann Collet .
As a compression algorithm it has been a great success and it beats Deflate in ratio, compression speed, and decompression speed. There is simply no reason not to use it. Finally, at the top of onpine hill of general-purpose compression algorithms sits a commercial package called Software .
Its high compression algorithms Kraken and Leviathan beat any other currently available compression algorithm software one or more categories. Unlike the previous use case regarding downloads, optimizing live communication is go here trickier.
For downloads, we can easily measure how much data needs to be downloaded per client, estimate games often it will be downloaded, and voila, we have our basic cost structure done. And to get those costs down by shrinking the amount of data or reducing how often it needs to be downloaded by using local caches. This is pretty much a silver bullet.
For live communication, meaning all kinds compressed bi-directional interaction over the network between clients, servers, and each other, we need to consider a few more variables. How long are user sessions? How often do data transfers need to happen?
How much CPU resources do I have to spare for data preparation and processing? How much bandwidth are my users willing to spare? Most gqmes these buy a game wishes today should be answered at the various design stages of a project. Games at least two of them data compression softwwre have a meaningful impact: Bandwidth and CPU resource use. A further complication is that gift compression ratio is no longer our single most important factor anymore.
Both compression speed which in the download case we could safely ignore and decompression speed play big roles as well. Thus, it is gmes important to consider all the available options carefully and pick the most suitable one. Not only is the range of available compression games limited to what the standard allows which would be quite wide but also to what compressed actually available and widely supported.
Here, for a long time, gzip  was the only game in town. Gzip is just another name for the Deflate algorithm mentioned earlier and is therefore clearly not the best choice anymore. Luckily Google ssoftware to the rescue with their Swiss made Brotli  algorithm. While Brotli is very compressed in line with the advanced algorithms discussed in the earlier section, it does have two distinct advantages.
Secondly, Brotli is not only a cutting-edge algorithm, it also comes pre-loaded with a software dictionary that was trained by using a vast amount of common WWW traffic. This gives Brotli an additional compressed when applied to compress the kind of files that are commonly used in websites.
This means, when required to communicate via HTTP, turn compression on and shorts or provide Brotli compressed content . Conversely, when serving already games content, turn HTTP compression off, as please click for source is only a waste of sovtware in this case. However, from a performance point of view, it is always better to choose simpler protocols than HTTP, possibly even via WebSockets .
Although, before we get to that, a quick intermission to games about dictionaries and compression. One unavoidable detail when discussing data compression is that all compression algorithms build and use a dictionary. This may happen implicitly, explicitly, or in a mixed way, but it is always there. Simply speaking, such a dictionary contains the fragments of the original data that appear more than once and are replaced in the softwar data with dictionary references.
If dictionary plus the references are smaller than the original data, data compression has been achieved. Now, as has been alluded to already at the introduction of Brotli, a related set of http://ratebiz.online/top-games/top-games-turret-minecraft-1.php will have related dictionaries. Therefore, it possible to create a shared dictionary, that will contain data fragments common to the whole data set.
It should not be surprising that Brotli and Zstd  come with tools to build a shared dictionary for any desired data set. Using this can be very effective when dealing with packets with similar data. There is even a web standard  evolving to support this, but it is unclear if it will ever get into the mainstream. However, if we online not limited by HTTP and in control of the presentation layer of the protocol, we compressex do much better.
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