Graphic Processing Unit (GPU)
Last updated
Last updated
A GPU is like a turbocharged CPU, a powerhouse of processing that is specially designed for graphics and visual effects and is now being used for all sorts of complex computing such as AI.
A graphics processing unit (GPU) is a computer chip that performs rapid mathematical calculations, primarily for the purpose of rendering images.
GPUs use parallel processing to speed up their operations. They divide tasks into smaller parts and distribute them among multiple processor cores (up to hundreds of cores) running within the same GPU.
GPUs are similar in function to CPU: they contain cores, memory, and other components.
Instead of emphasizing context switching to manage multiple tasks, GPU acceleration emphasizes parallel data processing through a large number of cores.
Contemporary computers have between two and twelve cores, and GPUs might have a few hundred or even a few thousand cores.
Traditionally GPUs have been used in processing 3D content/data in gaming. Over time, they are being used for other activities like bitcoin mining or many machine-learning use cases.
Machine learning is a computationally demanding process as it necessitates the input of large volumes of data for analysis. Due to the highly resource-intensive nature of machine learning, GPUs are an essential component.
The GPU, although a powerful performance booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe haven for stealthy malware and the weakest link as this paper claims.
Also, a new paper demonstrates how GPUs come with their own unique “fingerprints". Where third parties can get track you in stealthy surveillance activities.
Fingerprinting exploits how today’s browser can expose plenty of minor details about your computer to a website, such as the software version, screen resolution, fonts, time zone, and IP address. Since not every computer has the same settings, the ad industry can take these details to fingerprint your PC and track your browser as it moves from one site to another.
Researchers have now confirmed that there is a new high-accuracy method of identifying users, GPU fingerprints relying on WebGL 2.0 APU.
