What Is Hardware Acceleration and How Is It Useful?:
Hardware acceleration uses specially manufactured computer hardware (i.e., silicon microchips) to perform a narrow set of tasks faster than the general purpose cpu (Central processing unit).
What does this mean for you as a user? You often have the option to turn hardware acceleration on or off in your applications. So how useful is hardware acceleration, and what does it do?
What is Hardware Acceleration (Simple Version)
Here is a simple description of hardware acceleration. Skip to the next section for an in-depth look at the process.
Your computer’s CPU can solve any number of mathematical problems. CPU circuits use more components to deal with a wide variety of tasks. They take up more space, generate more heat, and are not as elegantly designed as circuits built for the same job.
With hardware acceleration, a specialized integrated circuit or microprocessor performs a specific task or a narrow set of related functions. The design of the circuit isn’t wasted on anything else, and it provides a significant performance advantage.
In short, hardware acceleration means giving a specific function to a unique piece of hardware which is a jack of a business and rocks at it.
What are the benefits of hardware acceleration?
How does hardware acceleration benefit the application you are using? This often depends on the type of hardware and the type of acceleration, but the general benefits apply to most situations.
- Hardware acceleration greatly improves performance. Your application will run more smoothly, or the application will complete a task in much less time.
- This frees up your CPU to do other things Better system performance. The CPU can offload work to particular hardware and then proceed, for example, playing video games or using applications with streaming video. discord.
- Hardware acceleration can be important for battery-powered devices. This is the reason why your smartphone or tablet can play videos 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 you might want to skip, but there are some cases where it can be a drawback.
- Hardware acceleration often causes instability. Despite being slow, CPUs are highly reliable. For example, hardware acceleration doesn’t make sense to accelerate video exports and then the process crashes before it’s finished.
- Hardware acceleration is inflexible to new developments. For example, your computer may have hardware acceleration for a specific video encoding method, but if something better comes along you’ll need to purchase new hardware to support it.
- The type of hardware acceleration your system supports may not produce the best results. So if you favor quality over speed, it’s better to let the CPU do the work in some cases. For example, if you don’t have hardware support for HEVC encoding, but you want its quality advantage over H.264 codec, you’ll need 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 some common ones you’ll 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 turned on by default in these applications, and you should just disable it for Troubleshooting.
video encoding acceleration
- Most CPUs now have acceleration for normal 264 video standard, and support for H.265 is also on the rise.
- Recent Nvidia GPUs also have a dedicated “NVENC” encoder chip that handles the recording or streaming of game footage so that it doesn’t affect game performance.
- application like Adobe Premiere Pro provides GPU-based hardware acceleration, thus improving performance when editing and exporting projects.
GPGPU (General Purpose GPU) Acceleration
Graphical processors started life as 3D graphics accelerators, but modern GPUs can perform a wide range of simple tasks much faster. These processors consist of hundreds or thousands of simple small processors that all operate in parallel.
This makes them ideal for some types of data crunching that need to run through algorithms. GPUs are designed this way because rendering graphics involves processing pixel values in parallel. So your GPU determines how each of the millions of pixels on the screen should look 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 perform even more specialized tasks than GPU cores.
- The latest generation of Nvidia GPUs has special components that speed up math Ray tracing, which is a method of drawing 3D graphics by simulating the propagation of light through a scene.
- These GPUs have an additional processor that is very good at doing so-called “tensor” math. These are useful in applications that use neural net machine learning, which is becoming more common in everyday computing tasks.
acceleration is everywhere
These days almost every computing device has hardware acceleration and as some computing jobs become popular, computer scientists will create even more dedicated systems so that they can work faster and more efficiently.
So sit back and enjoy the speed!