![]() The most common hardware used for acceleration include: 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. Systems often provide the option to enable or disable hardware acceleration. 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. 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. ![]() ![]() 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. There is a wide variety of dedicated hardware acceleration 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. 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. ![]()
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