Once a humble graphics chip, the GPU has become technology\u2019s most versatile workhorse. Born from the 1987 VGA controller\u2019s pixel-pushing dreams, it evolved through gaming\u2019s demands for ever-prettier pixels. Like a mighty river absorbing tributaries, the GPU assimilated everything: DSP vector engines, Google\u2019s TPU matrix magic, smartphone AI accelerators\u2014all swallowed whole. Today\u2019s monsters pack 4 trillion transistors and power everything from your phone to data-center behemoths. The question isn\u2019t whether CPUs will be absorbed next\u2014history says they will\u2014but whether we\u2019re heading toward Cerebras-style mega-chips or AMD\u2019s chiplet constellations. Either way, the GPU\u2019s appetite remains insatiable.<\/em><\/p>\n Resistance is futile; you will be assimilated.<\/sup><\/em><\/strong><\/p>\n As the mighty GPU powers more of our lives\u2014from driving our cars, powering our connection to the world through smartphones, entertaining us with amazing simulations in games, and consuming all available power for data centers\u2014a moment of reflection on how this ubiquitous equivalent to a technological weed has taken over our lives seems appropriate.\u00a0<\/p>\n The idea of manipulating individual pixels emerged with the VGA controller in 1987. That gave rise to the adoption of serious graphics in games. That, in turn, drove the demand for more control, higher resolutions, and more colors, leading to the GPU with multiple pipelines, soon to be renamed \u201cshaders.\u201d The size and quantity of shaders expanded as fast as Moore\u2019s Law would allow (it was, after all,\u00a0the law<\/em>).<\/p>\n The idea of a dedicated graphics processor spread to other platforms, and stand-alone graphics co-processors were finding homes in mobile phones. The concept of the SoC, enabled by Moore\u2019s Law alongside the GPU, is on a path of assimilation and technology sharing. SIMD gave way to SIMT, and the abandonment of color LUTs in favor of unified programmable shaders in the early 2000s.<\/p>\n Simultaneously, DSPs, which had been esoteric music and image engines, added vector capabilities, enabling them to perform matrix math, and were then assimilated into what would become the NPU.<\/p>\n Goggle produced the first dedicated matrix engine for AI with their TPU in the mid 2010s, which was assimilated into GPUs by 2017.<\/p>\n In the late mid-2010s, the first dedicated AI engines began to appear as video processors (VPUs), and within three years, they were assimilated into smartphone SoCs, but they did establish the beginning of dedicated AI processors.<\/p>\n Figure 1. The evolution of the GPU.<\/sup><\/em><\/strong><\/p>\n Like the Mississippi, Volga, Yangtze, and the Nile, technology has flowed into the GPU over its 27-year history. And although physical VGA sequencers have given way to GOP under UEFI (in 2011), they still have a heritage going back to 1987.<\/p>\n Today, we have powerful x86 and Arm CPUs with integrated GPUs that are entering the AI market in the form of the AI PC. At the same time, we have giant GPUs being tightly coupled with Arm, RISC-V, as well as x86 processors.\u00a0<\/p>\n It seems that if history is any teacher, it\u2019s just a (short) matter of time until the Arm or RISC-V CPU is assimilated into the mighty GPU. It\u2019s a matter of size and memory. The industry is at a crossroads of ever-larger integrated systems like Cerebras and Nvidia versus the pursuit of chiplets sitting on a bed of interposers like AMD and Intel. Hybrid approaches are already being tested, along with the integration of area-hungry SRAM to try to break the memory bandwidth barrier.\u00a0<\/p>\n We have 40 years of assimilation and integration to help us predict the future. You could mark T-0 with the integration of the FPU in the 80386 in 1985, or maybe the GPU into an iGPU in the Westmere architecture in 2010.\u00a0\u00a0And if Cerebras is an example, there doesn\u2019t seem to be an asymptote on how far assimilation can go.\u00a0<\/p>\n Resistance\u00a0IS<\/em>\u00a0futile, you\u00a0WILL<\/em>\u00a0be assimilated.<\/p>\n![\"GPU](\"https:\/\/www.jonpeddie.com\/wp-content\/uploads\/2026\/02\/gpu1.svg\" "\\"gpu1\\"\/")
<\/figure>\n![\"\"](\"https:\/\/www.jonpeddie.com\/wp-content\/uploads\/2026\/02\/gpu2.jpg\" "\\"gpu2\\"")
<\/figure>\n