What is hardware acceleration?

Hardware acceleration refers to the process of moving some software running on the CPU to idle hardware resources, which can be graphics cards, sound cards, graphics processing units (GPUs) or special devices (such as artificial intelligence accelerators), to optimize resource usage and performance. Most browsers also have acceleration features.

CPU is the core of all computer systems. It is designed to manage all tasks, but managing all tasks is not efficient. Therefore, video encoding, decoding, and graphics rendering can be performed on dedicated devices such as GPUs. Hardware acceleration offloads day-to-day tasks from the CPU to specially designed hardware that can perform the work more efficiently.

Key Uses of Hardware Acceleration

1. Artificial intelligence data processing

An increasing number of hardware accelerators are being integrated into systems on chips (SoCs) to support various AI applications. Due to the complexity of artificial intelligence, running artificial intelligence first requires hardware acceleration. AI accelerators are designed to accelerate AI work. They perform these operations with an efficiency that traditional CPUs cannot achieve.

2. Audio processing

Some PC audio adapters feature hardware acceleration, which helps perform hardware mixing of any number of audio files being processed by the audio driver.
Hardware acceleration improves audio processing performance by freeing the CPU from audio mixing work.

3. Encryption hardware acceleration

The encryption process can be expensive when done using software. Hardware accelerators can perform these operations to improve performance and reduce usage costs. Crypto hardware acceleration refers to the use of hardware to perform encryption functions, and generally hardware acceleration is faster than software acceleration.

4. Video encoding and decoding

Upgrading our videos to higher resolutions more than doubles the workload on the CPU, resulting in CPU overload, throttling, high CPU usage, and process interruptions. Leverage the huge parallel processing capabilities of the GPU to successfully reduce CPU processing time and power consumption.

5.AI drawing and modeling

Currently we are using computer design programs (such as modeling, drawing tools, etc.) to perform basic drawing and modeling processes. These modeling and drawing operations are very computationally demanding. Therefore, after we model and draw, we need to wait for a long time for computer processing before we can finally get our finished product, which increases our time cost. Hardware acceleration can greatly reduce computer rendering time and improve our work efficiency.

When to use hardware acceleration?

We may need to use hardware acceleration when we encounter the following situations:
· Long application load times: When more GPU processors are available for processing, more tasks can be completed simultaneously, which increases efficiency and reduces the time required to obtain results and responses.
· Slow speed: Multiple GPUs on a computer system can handle different jobs individually and complete calculations faster than using just one CPU processor.
· Excessive power consumption: Systems using GPUs can reduce power consumption because it does not require all components of the system to be running at the same time.

Advantages of hardware acceleration

Hardware accelerators have the undisputed advantage of making computing operations more efficient and productive. The main purpose of hardware acceleration is to minimize CPU overload and memory consumption. This can make applications run faster and more efficiently, free up bandwidth, and improve system reliability and reliability.