Dardargelinta qalabku^(Hardware) waxay isticmaashaa qalab kombuyuutar oo si gaar ah loo dhisay (ie, silikoon microchips) si loo qabto hawlo cidhiidhi ah oo ka dhaqso badan CPU -ga ujeedo-guud ah (cutubka habaynta dhexe).

Maxay taasi uga dhigan tahay isticmaale ahaan? Badana waxaad heli doontaa ikhtiyaarka ah inaad damiso ama damiso codsiyadaada. Haddaba sidee faa'iido u leedahay dardargelinta qalabka, maxayse qabataa?

Waa maxay Dardargelinta Qalabka^{(Hardware Acceleration)} ( Daabacaadda Fudud^{(Simple Edition)} )

Halkan waxaa ah sharraxaad fudud oo ku saabsan dardargelinta qalabka. U gudub^(Skip) qaybta xigta si aad si qotodheer ugu eegno habka. 

CPU - gu kombayutarkaagu waxa uu xalin karaa uun nooc kasta oo mushkilad xisaabeed ah. Wareegyada CPU^(CPU) waxay isticmaalaan qaybo badan si ay wax uga qabtaan noocyo badan oo hawlo ah. Waxay qaataan meelo badan, waxay dhaliyaan kuleyl badan, oo aan si qurux badan loo naqshadayn sida wareegga loo dhisay hal shaqo. 

Xawaaraynta qalabka, wareegga khaaska ah ee isku dhafan ama microprocessor wuxuu qabtaa hal hawl gaar ah ama shaqo cidhiidhi ah oo la xidhiidha. Naqshadeynta wareegga laguma lumin wax kale, tani waxay bixisaa faa'iido waxqabad oo muhiim ah. 

Mararka qaarkood qalabkaas ayaa lagu dhex dhisay CPU laftiisa. Inta badan CPU-yada^(CPUs) casriga ah waxay u heellan yihiin qaybo gudaha ah kuwaas oo dardargeliya noocyada xisaabta gaarka ah ee loo isticmaalo hawlaha sida codaynta fiidyowga^{(video encoding)} iyo siraynta^(encryption) .

Marka la soo koobo, dardargelinta qalabku waxay ka dhigan tahay in shaqo gaar ah la siinayo qalab gaar ah oo ka mid ah baayacmushtarka iyo dhagaxyada.

Waa maxay faa'iidooyinka^(Benefits) dardargelinta qalabku^{(Hardware Acceleration)} ?

Sidee bay dardargelinta qalabku uga faa'iidaysanaysaa arjiga aad isticmaalayso? Badanaa waxay kuxirantahay nooca qalabka iyo nooca dardargelinta, laakiin faa'iidooyinka caadiga ah waxay khuseeyaan xaaladaha badankood.

• Dardargelinta qalabku^(Hardware) waxay si weyn u wanaajisaa waxqabadka. Codsigaagu wuxuu u socon doonaa si habsami leh, ama codsigu wuxuu ku dhamaystiri doonaa hawl wakhti aad u gaaban.

• Waxay u fasaxaysaa CPU -gaaga inuu sameeyo waxyaabo kale oo u horseedaya waxqabadka nidaamka horumaray. CPU - gu wuxuu shaqada u dejin karaa qalabka gaarka ah ka dibna la sii wado, tusaale ahaan, ku socodsiinta ciyaaraha fiidyaha isla mar ahaantaana uu la socdo fiidyowyada qulqulka ama adeegsiga codsi sida Discord .

• Dardargelinta^(Hardware) qalabku waxa ay muhiim u tahay aaladaha ku shaqeeya baytari. Waa sababta talefankaaga casriga ah ama tablet-kaagu ay u ciyaari karaan muqaal waqti dheer adiga oo aan taangiga ku xidhin baytarigaaga. Chip yar oo khaas ah ayaa had iyo jeer isticmaala awood ka yar kan weyn ee CPU .

Ma jiraan^(Are) waxyaabo hoos u dhigaya ^(Downsides)dardargelinta qalabka^{(Hardware Acceleration)} ?

Guud ahaan, dardargelinta qalabku waa wax aad rabto inaad ka baxdo, laakiin waxaa jira xaalado qaarkood oo ay ku noqon karto cillad. 

• Dardargelinta qalabku^(Hardware) waxay badanaa keentaa xasillooni darro. In kasta oo ay gaabis yihiin, CPU-yadu^(CPUs) waxay u muuqdaan kuwo si heersare ah loogu kalsoonaan karo. Tusaale ahaan, waxaa jirta dhibic yar in lahaanshaha dardargelinta qalabka ay dedejiso dhoofinta fiidyowga ka dibna ay dhacdo shil ka hor inta uusan dhammaan.

• Dardargelinta^(Hardware) qalabku waa mid aan u jilicsanayn horumarka cusub. Tusaale ahaan, waxaa laga yaabaa inaad ku haysato kombuyuutarkaaga dardargelinta hardware-ka hab gaar ah oo fiidiyoow ah, laakiin haddii wax ka fiicani yimaado waa inaad soo iibsataa qalab cusub si aad u taageerto. 

• Nooca dardargelinta qalabka nidaamkaagu waxa laga yaabaa inaanay bixin natiijooyinka ugu fiican. Markaa haddii aad ka door bidayso tayada xawaaraha, way fiicnaan lahayd inaad u ogolaato CPU inay qabato shaqada xaaladaha qaarkood. Tusaale ahaan, haddii aadan haysan taageero qalab oo loogu talagalay codeeynta HEVC laakiin aad rabto faa'iidooyinkeeda tayada ee H.264 CODEC , waa inaad ku tiirsan tahay codeynta ku saleysan CPU .

Halkeen Ka Isticmaali Karaa Dardargelinta Qalabka^{(Use Hardware Acceleration)} ?

Waxaa jira qaabab aad u badan oo ah dardargelinta qalabka la heli karo si halkan loogu wada taxo, laakiin kuwani waa kuwa yar oo caadi ah oo aad la kulmi doonto celcelis ahaan isticmaale kombuyuutar.

Dardar galinta Hardware Browser^{(Browser Hardware Acceleration)}

Daalacashada shabakadu waxay noqon kartaa codsiyo ^(Web)culus oo CPU^(CPU-heavy) la yaab leh . Mareegaha casriga ahi^(Modern) waxay leeyihiin saamayn garaafeed qurxoon iyo aragtiyo iyo dhawaaqyo aaminnimo sare leh. Codsiyada mareegaha^(Web) ee isticmaala sawirada 3D waxay ka faa'iidaystaan ​​dardargelinta qalabka  GPU .

Dardargelinta qalabku^(Hardware) inta badan waa u daaran yahay codsiyadan, waana inaad kaliya u damisaa cilad- saaridda^{(troubleshooting)} .

Dardargelinta Codaynta Fiidiyowga^{(Video Encoding Acceleration)}

• Inta badan CPU-yada hadda waxay leeyihiin dardargelinta heerka caadiga ah ee fiidiyowga H.264 , iyo taageerada H.265 ayaa sidoo kale sii kordheysa. 
• Nvidia GPU-yadii^{(Nvidia GPUs)} dhawaa waxay sidoo kale leeyihiin "NVENC" encoder chip u go'ay kaasoo la wareegaya shaqada duubista ama baahinta muuqaalka ciyaarta si aysan u saameyn waxqabadka ciyaarta.
• Codsiyada sida Adobe Premiere Pro waxay bixiyaan dardargelinta qalabka GPU-ku-salaysan, sidaas darteed wanaajinta waxqabadka marka la daabaco oo la dhoofiyo mashaariicda.

Dardargelinta GPGPU (Ujeedada Guud GPU).^{(GPGPU (General Purpose GPU) Acceleration)}

Soo-saareyaal garaafeedku waxay nolosha ku bilaabeen dardar-geliyayaal garaafyo 3D ah, laakiin GPU-yada^(GPUs) casriga ahi waxay si degdeg ah u samayn karaan hawlo kala duwan oo fudud oo kala duwan. Processor-yaashani waxay ka kooban yihiin boqollaal ama kun oo Processor-yareyaal yar yar oo fudud oo dhammaantood si barbar socda u shaqeeya. 

Tani waxay ka dhigaysaa inay ku habboon yihiin noocyada xogta qaarkood ee jajabinta kuwaas oo u baahan in lagu dhex maro algorithm. GPU-yada^(GPUs) waxaa loo qaabeeyey habkan sababtoo ah samaynta garaafyada waxay ku lug leedahay habaynta qiyamka pixels si siman. Markaa GPU -gaagu waxa uu go'aamiyaa waxa mid kasta oo ka mid ah malaayiinta pixels ee shaashadda ay tahay inay u ekaato isku mar. Waxay soo baxday in barashada qoto dheer iyo codsiyada macdanta xogta ay sidoo kale ka faa'iidaystaan ​​habkan xisaabinta.

Raadinta Ray raadinta iyo Dardargelinta Barashada Mashiinka^{(Ray Tracing and Machine Learning Acceleration)}

Horumarinta GPU^(GPU) waxay hadda ku dareen la-processor-yaal u go'ay oo qabta shaqo khaas ah oo xitaa ka sii badan kuwa GPU -ga. 

• Jiilkii ugu dambeeyay ee Nvidia GPUs waxay leeyihiin qaybo gaar ah oo dardargeliya xisaabta raadinta rayiga^{(ray tracing)} , taasoo ah habka sawirida sawirada 3D iyadoo la sawirayo sida iftiinku ugu faafo goobta.
• GPU-yadani^(GPUs) waxay leeyihiin processor dheeraad ah oo aad ugu wanaagsan samaynta waxa loogu yeero xisaabta "tensor". Kuwani waxay faa'iido u leeyihiin codsiyada isticmaala barashada mashiinka shabakada neerfaha, taas oo ku sii badanaysa hawlaha xisaabinta maalin kasta.

Dardargelintu Waa Meel kasta

Waxaa jira dardargelinta qalabka ku dhawaad ​​qalab kasta oo maalmahan ah iyo sida shaqooyinka xisaabinta qaarkood ay noqdaan kuwa caan ah, saynisyahannada kombuyuutarku waxay abuuri doonaan xitaa habab aad u go'an si ay uga dhigaan inay si dhakhso leh oo hufan u shaqeeyaan. 

Markaa dib u fadhiiso oo ku raaxayso xawaaraha!

What Is Hardware Acceleration and How Is It Useful?

Hardware аcceleration uses speciallу-built computer hardware (і.e., silіcon microchips) to do a narrow sеt of tasks faster than a genеral-purpose CPU (central processing unit).

What does that mean to you as the user? You’ll often have the option of turning hardware acceleration on or off in your applications. So how useful is hardware acceleration, and what does it do?

What Is Hardware Acceleration (Simple Edition)

Here’s a simple explanation of hardware acceleration. Skip to the next section for an in-depth look at the process. 

The CPU in your computer can solve just about any type of mathematical problem. CPU circuits use more components to deal with many kinds of tasks. They take up more space, generate more heat, and aren’t as elegantly designed as a circuit built for a single job. 

With hardware acceleration, a special integrated circuit or microprocessor does one specific task or a narrow set of related jobs. The circuit’s design is not wasted on anything else, and this provides a significant performance advantage. 

Sometimes that hardware is built into the CPU itself. Most modern CPUs have dedicated internal sections that accelerate specific types of math used for tasks such as video encoding and encryption.

In short, hardware acceleration means giving a specific job to a unique piece of hardware that’s a jack of one trade and rocks at it.

What Are the Benefits of Hardware Acceleration?

How does hardware acceleration benefit the application you’re using? It often depends on the type of hardware and the type of acceleration, but the usual benefits apply to most situations.

• Hardware acceleration greatly improves performance. Your application will run more smoothly, or the application will complete a task in a much shorter time.

• It frees up your CPU to do other things leading to improved system performance. The CPU can offload work to the specialized hardware and then get on with, for example, running video games simultaneously with streaming videos or using an application like Discord.

• Hardware acceleration can be crucial for battery-powered devices. It’s why your smartphone or tablet can play video for such a long time without tanking your battery. A small specialized chip almost always uses less power than a large, complex CPU.

Are There Downsides to Hardware Acceleration?

In general, hardware acceleration is something that you’ll want to leave on, but there are some cases where it can be a drawback. 

• Hardware acceleration often causes instability. Despite being slow, CPUs tend to be highly reliable. For example, there’s little point in having hardware acceleration speed up video exports and then have the process crash before it finishes.

• Hardware acceleration is inflexible to new developments. For example, you may have hardware acceleration in your computer for a specific video encoding method, but if something better comes along you’ll have to buy new hardware to support it. 

• The type of hardware acceleration your system supports might not offer the best results. So if you favor quality over speed, it would be better to let the CPU handle the work in some cases. For example, if you don’t have hardware support for HEVC encoding but want its quality advantages over the H.264 CODEC, you’ll have to rely on CPU-based encoding.

Where Can I Use Hardware Acceleration?

There are too many forms of hardware acceleration available to list them all here, but here are a few common ones that you will encounter as an average computer user.

Browser Hardware Acceleration

Web browsers can be surprisingly CPU-heavy applications. Modern websites have fancy graphical effects and high-fidelity sights and sounds. Web applications that use 3D graphics benefit from GPU hardware acceleration. 

Hardware acceleration is usually on by default in these applications, and you should only disable it for troubleshooting.

Video Encoding Acceleration

• Most CPUs now have acceleration for the common H.264 video standard, and support for H.265 is growing too. 
• Recent Nvidia GPUs also have a dedicated “NVENC” encoder chip that takes over the work of recording or streaming game footage so that it doesn’t affect game performance.
• Applications such as Adobe Premiere Pro offer GPU-based hardware acceleration, thus improving performance while editing and exporting projects.

GPGPU (General Purpose GPU) Acceleration

Graphical Processors started life as 3D graphics accelerators, but modern GPUs can do a fairly wide range of simple operations very quickly. These processors consist of hundreds or thousands of simple small processors that all work in parallel. 

This makes them ideal for certain types of data crunching that need to be run through an algorithm. GPUs are designed this way because rendering graphics involves processing pixel values in parallel. So your GPU determines what each of the millions of pixels on the screen should look like at the same time. It turns out that deep learning and data mining applications also benefit from this approach to computation.

Ray Tracing and Machine Learning Acceleration

GPU developers have now added dedicated co-processors that do an even more specialized job than the GPU cores. 

• The latest generation of Nvidia GPUs have special components that accelerate the mathematics of ray tracing, which is a method of drawing 3D graphics by simulating how light propagates through a scene.
• These GPUs have an additional processor that’s very good at doing so-called “tensor” mathematics. These are useful in applications that use neural net machine learning, which is becoming more common in everyday computing tasks.

Acceleration Is Everywhere

There’s hardware acceleration in almost every computing device these days and as certain computing jobs become popular, computer scientists will create even more dedicated systems to make them work faster and more efficiently. 

So sit back and enjoy the speed!

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