Programming and computation procedures
GPU, AI, and ML are acronyms used in computer science to refer to programming and computation procedures that govern modern usage of computer by man and their capabilities. GPUs refers to ‘Graphics Processing Units’ in plural while singular it’s GPU. GPUs act as a coprocessor in the computation process. Application and significance of GPUs as early as 1990 due to demand for real-time and more realistic simulation of graphics in computer games. Sequential changes occurred in 2003 when Harris introduced GPGPU. GPGPU is an abbreviation coined to refer to general-purpose GPUs. AI is an initial for Artificial Intelligence, while ML denotes Machine.
Concerning the development of computers and computation procedures, GPUs is a core component of power behind the growth and progression of AI we witness today. There are two brands of GPUs that ignited the current counter culture of digital growth. AMD and NVIDIA are the first companies that introduced software GPUs that are multi-core computing platforms. Previous versions used in 2d and 3d graphics output were architecturally hardware in nature (NVIDIA Corporation.
NVIDIA first product, CUDA (Compute Unified Device Architecture) launched in 2006 and had no computing capacity. Modern NVIDIA CUDA was introduced in the market in 2011 and have advanced computing capabilities. From 2012 CUDA GPUs has transformed computation performance by 500X. DGX-1 compared to CPU can compute 140X faster. Efficiency facilitated by GPUs as coprocessors have contributed to the exponential growth of the Internet of Things. IoT developed through the concept of Machine Learning (ML) and Artificial Intelligence (AI). AI and ML have facilitated real-time information and simulation in all sectors and industries. Modern GPUs initiated and controlled the current ‘Fourth Industrial Revolution’ characterized by automation of processes and services. Digital transformation launched digital economy facilitated by IoT product of ML&AI through GPUs (Mclellan, 2018).