How do I know when to use hardware acceleration?

I'm not sure I know what hardware acceleration ("...use of computer hardware to perform some function faster") is, but when I play flash games, or 3D FPS games, I'm asked if I want to use hardware acceleration.

What criteria should I mentally weigh before checking or un-checking a box? Does hardware acceleration always refer to my graphics card?

Solution 1:

Hardware acceleration is where certain processes - usually 3D graphics processing - is performed on specialist hardware on the graphics card (the GPU) rather than in software on the main CPU.

In general you should always enable hardware acceleration as it will result in better performance of your application. This will usually be a higher frame rate (the number of images displayed per second), and the higher the frame rate the smoother the animation.

GPU's also perform the physics calculations used in many 3D games to simulate falling objects, water, the motion of cars etc. This means that if you don't have hardware acceleration the game won't run at it's full potential or even at all.

Hardware acceleration is also used when displaying normal video, again to allow the CPU to do other things. This means you can play a video on one monitor while still working on that report on the other.

As music2myear points out, any specific purpose hardware can be used to accelerate the processing of whatever it is designed for. This can also include sound cards, but video cards are the most common and what most people will understand by the term.

So, in general, I'd say that you'd always want to enable hardware acceleration. The only time I can think of that you wouldn't would be if you were running off your laptop's battery and wanted to conserve power. Enabling it could take more juice than not having it on - but it would depend on the hardware, some specialist hardware could use less power than it would take using the more general CPU/memory/etc in the computer.

The only way to be sure would be to measure the drain on the battery with hardware acceleration on and again with it off when doing the same tasks.

Solution 2:

If you have a discrete video card you'll probably want to at least try Hardware Acceleration. Though some drivers and models of cards may have compatibility issues and you may end up turning it off.

Basically, as you've stated, the acceleration off-loads the processing of the graphics to the GPU.

As the web has become more graphically rich, the graphical elements have put a strain on the CPU, or at least can be offloaded, and so newer versions of Flash and most current generation browsers offer graphical hardware acceleration. You'll want to make sure you've got the latest graphics card drivers and the latest versions of your browser and plugins to ensure maximal compatibility.

Solution 3:

When the option of hardware acceleration is allowed, it is always a wonderful idea to use it: usually, the application (or part of it) runs faster and, at the same time, using less energy. Moreover, the CPU will be free to process something else!!

Unfortunately, hardware acceleration doesn’t always work as smoothly as it should. The first time I recall encountering the option was when I disabled it in Chrome, because it was seemingly making my browser run much less stably. Here’s the cases where you should probably disable hardware acceleration:

• If your CPU is really strong and your other components are really weak, acceleration may actually be ineffective in comparison to just letting the powerhouse take care of things. Additionally, if your components are prone to overheating/are damaged in any way, intensive use through hardware acceleration may be causing problems you wouldn’t experience otherwise.
• The software designed to utilize the hardware isn’t doing it well or can’t run as stably as it does when using only the CPU. This is a common reason to disable hardware acceleration in an app’s options, unfortunately, but it does happen.

Hardware acceleration combines the flexibility of general-purpose processors, such as CPUs, with the efficiency of fully customized hardware, such as GPUs and ASICs, increasing efficiency by orders of magnitude when any application is implemented higher up the hierarchy of digital computing systems. For example, visualization processes may be offloaded onto a graphics card in order to enable faster, higher-quality playback of videos and games, while also freeing up the CPU to perform other tasks.

There is a wide variety of dedicated hardware acceleration systems. One popular form is tethering hardware acceleration, which, when acting as a WiFi hotspot, will offload operations involving tethering onto a WiFi chip, reducing system workload and increasing energy efficiency. Hardware graphics acceleration, also known as GPU rendering, works server-side using buffer caching and modern graphics APIs to deliver interactive visualizations of high-cardinality data. AI hardware acceleration is designed for such applications as artificial neural networks, machine vision, and machine learning hardware acceleration, often found in the fields of robotics and the Internet of Things.

Systems often provide the option to enable or disable hardware acceleration. For instance, hardware acceleration is enabled by default in Google Chrome, but this capability can be turned off or relaunched in the system settings under “use hardware acceleration when available.” In order to determine if hardware acceleration is working properly, developers may perform a browser hardware acceleration test, which will detect any compatibility issues.

The most common hardware used for acceleration include:

• Graphics Processing Units (GPUs): originally designed for handling the motion of image, GPUs are now used for calculations involving massive amounts of data, accelerating portions of an application while the rest continues to run on the CPU. The massive parallelism of modern GPUs allows users to process billions of records instantly.
• Field Programmable Gate Arrays (FPGAs): a hardware description language (HDL)-specified semiconductor integrated circuit designed to allow the user to configure a large majority of the electrical functionality. FPGAs can be used to accelerate parts of an algorithm, sharing part of the computation between the FPGA and a general-purpose processor.
• Application-Specific Integrated Circuits (ASICs): an integrated circuit customized specifically for a particular purpose or application, improving overall speed as it focuses solely on performing its one function. Maximum complexity in modern ASICs has grown to over 100 million logic gates.