gpu - OpenGenus IQ: Learn Algorithms, DL, System Design

Graphics Processing Unit (GPU) vs Tensor Processing Unit (TPU) vs Field Programmable Gate Arrays (FPGA)

Graphics Processing Unit (GPU), Tensor Processing Unit (TPU) and Field Programmable Gate Array (FPGA) are processors with a specialized purpose and architecture. We have compared these in respect to Memory Subsystem Architecture, Compute Primitive, Performance, Purpose, Usage and Manufacturers.

gpu

Central Processing Unit (CPU) vs Graphics Processing Unit (GPU) vs Tensor Processing Unit (TPU)

Central Processing Unit (CPU), Graphics Processing Unit (GPU) and Tensor Processing Unit (TPU) are processors with a specialized purpose and architecture. We have compared these in respect to Memory Subsystem Architecture, Compute Primitive, Performance, Purpose, Usage and Manufacturers.

Machine Learning (ML)

Key ideas that makes Graphics Processing Unit (GPU) work so fast

We have explored the key ideas that are used in Graphics Processing Unit to make it so fast. Ideas include many cores in parallel, pack cores full of ALUs by sharing instruction stream by explicit SIMD vector instruction and avoid latency stalls by interleaving execution of many groups.

Machine Learning (ML)

Basic Graphics Processing Unit (GPU) design concepts

we have explored some of the basic architecture concepts in Graphics Processing Unit (GPU) such as graphics pipeline, vector processing, primitive processing, rasterization, fragment processing, pixel operations, graphics architecture and shader programming model There are five basic graphics entity

Machine Learning (ML)

What is a Graphics Processing Unit (GPU)?

A graphics processing unit (GPU) is a processor like CPU and TPU for faster graphics processing. Specifically, it designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer to be displayed on a screen. GPUs are developed by Intel, Nvidia and AMD (ATI).