{"id":88861,"date":"2026-02-20T11:13:07","date_gmt":"2026-02-20T05:43:07","guid":{"rendered":"https:\/\/vajiramandravi.com\/current-affairs\/?p=88861"},"modified":"2026-02-20T11:13:07","modified_gmt":"2026-02-20T05:43:07","slug":"graphics-processing-unit-explained","status":"publish","type":"post","link":"https:\/\/vajiramandravi.com\/current-affairs\/graphics-processing-unit-explained\/","title":{"rendered":"Graphics Processing Unit Explained: How GPU Power AI and Modern Computing"},"content":{"rendered":"<h2><b>GPU Latest News<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">In 1999, Nvidia introduced the <\/span><b>GeForce 256<\/b><span style=\"font-weight: 400;\"> as the world\u2019s <\/span><b>first<\/b><span style=\"font-weight: 400;\"> GPU, designed primarily to enhance video game graphics and performance.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Over the past 25 years, GPUs have evolved far beyond gaming, becoming essential components of the digital economy and powering core technologies such as artificial intelligence and large-scale computing.<\/span><\/li>\n<\/ul>\n<h2><b>GPU: Understanding the Basics<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">A Graphics Processing Unit (GPU) is a specialised processor designed to perform many simple calculations simultaneously.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Unlike a Central Processing Unit (CPU), which handles fewer but more complex tasks quickly and efficiently, a GPU excels at parallel processing\u2014handling large volumes of repetitive computations at once.<\/span><\/li>\n<\/ul>\n<h3><b>Why GPUs Are Ideal for Graphics<\/b><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Rendering images on a screen requires updating millions of pixels multiple times per second.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">For example, a 1920\u00d71080 display has over 2 million pixels per frame, and at 60 frames per second, more than 120 million pixel updates are required every second.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Each pixel\u2019s colour depends on lighting, texture, shadows, and object properties.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Since the same calculations are repeated across pixels, GPUs are better suited than CPUs for this kind of workload.<\/span><\/li>\n<\/ul>\n<h3><b>Parallel Processing Made Simple<\/b><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">A GPU can be imagined as a large team of workers, each handling a small portion of a task simultaneously.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">While each GPU core is less powerful than a CPU core, the GPU contains hundreds or thousands of such cores.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">This allows it to process large, repetitive workloads far more quickly than a CPU working alone.<\/span><\/li>\n<\/ul>\n<h2><b>How a GPU Works: The Rendering Process Explained<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">When a video game displays a scene, it sends the GPU objects built from triangles.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The GPU processes them through a four-step rendering pipeline to produce the final image.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Vertex Processing<\/b><span style=\"font-weight: 400;\"> &#8211; The GPU calculates where each triangle should appear on the screen. Using mathematical operations with matrices, it rotates, moves, and adjusts objects according to the camera\u2019s perspective.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Rasterisation &#8211;<\/b><span style=\"font-weight: 400;\"> Once positioned, the GPU determines which screen pixels each triangle covers. This step converts geometric shapes into pixel-level data ready for colouring.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Fragment (Pixel) Shading<\/b><span style=\"font-weight: 400;\"> &#8211; For each pixel fragment, the GPU calculates the final colour. It applies textures, lighting, shadows, reflections, and other visual effects using small programs called shaders.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Frame Buffer Output<\/b><span style=\"font-weight: 400;\"> &#8211; The computed pixel colours are written to memory known as the frame buffer. The display system then reads this buffer to render the final image on the screen.<\/span><\/li>\n<\/ul>\n<h3><b>Parallel Processing and Memory Design<\/b><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">GPUs execute shader programs simultaneously across many vertices and pixels.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">To handle massive data flows\u2014such as 3D models and textures\u2014they use dedicated high-bandwidth memory called <\/span><b>VRAM<\/b><span style=\"font-weight: 400;\"> (video RAM).\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Smaller, faster caches and shared memory structures help prevent bottlenecks.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Because GPUs excel at repeating similar calculations across large datasets, they are widely used beyond graphics in machine learning, image processing, and scientific simulations.<\/span><\/li>\n<\/ul>\n<h2><b>Where Is the GPU Located<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>The GPU as a Silicon Chip<\/b><span style=\"font-weight: 400;\"> &#8211; A GPU is built on a silicon die \u2014 a flat piece of semiconductor material measured in square millimetres. Like a CPU, it is a physical chip mounted inside a computing device.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Dedicated Graphics Card Setup<\/b><span style=\"font-weight: 400;\"> &#8211; In systems with a separate graphics card, the GPU die sits beneath a metal heat sink at the centre of the card. It is surrounded by VRAM chips and connects to the motherboard through a high-speed interface.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Integrated Graphics in Modern Devices<\/b><span style=\"font-weight: 400;\"> &#8211; In laptops and smartphones, the GPU is often integrated with the CPU on the same die. This design is common in modern systems-on-a-chip (SoCs), which combine multiple components that were previously separate into a single package.<\/span><\/li>\n<\/ul>\n<h2><b>GPUs Vs CPUs<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">GPUs are not fundamentally smaller than CPUs. Both use similar silicon transistors and advanced fabrication nodes (e.g., 3\u20135 nm).\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The difference lies in microarchitecture \u2014 how transistors are organised and used.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">CPUs dedicate more die area to complex control logic, cache, and decision-making features.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">GPUs allocate more space to repeated compute units and wide data paths, enabling parallel processing.<\/span><\/li>\n<\/ul>\n<h2><b>How Much Energy Do GPUs Consume<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Energy During Training<\/b><span style=\"font-weight: 400;\"> &#8211; In a scenario using four Nvidia A100 GPUs (250 W each) for 12 hours of neural network training, total energy consumption would be about 12 kWh, as the GPUs run near full capacity.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Energy During Inference<\/b><span style=\"font-weight: 400;\"> &#8211; Once deployed, if one GPU handles predictions, energy use drops to roughly 2 kWh for inference.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Total System Consumption<\/b><span style=\"font-weight: 400;\"> &#8211; Including additional server components (CPU, RAM, storage, cooling), total daily power use can reach around 6 kWh when running continuously, accounting for 30\u201360% overhead.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Real-World Comparison<\/b><span style=\"font-weight: 400;\"> &#8211; This is comparable to running an air conditioner for 4\u20136 hours, a water heater for 3 hours, or 60 LED bulbs for 10 hours daily.<\/span><\/li>\n<\/ul>\n<p><b>Source:<\/b> <strong><a href=\"https:\/\/www.thehindu.com\/sci-tech\/science\/what-is-a-gpu-how-does-it-work-explained\/article70650287.ece\" target=\"_blank\" rel=\"nofollow noopener\">TH<\/a><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A Graphics Processing Unit (GPU) powers AI, gaming, and data processing. Learn how a Graphics Processing Unit works, differs from CPUs, and consumes energy.<\/p>\n","protected":false},"author":18,"featured_media":88866,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[18],"tags":[5576,60,22,59],"class_list":{"0":"post-88861","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-upsc-mains-current-affairs","8":"tag-gpu","9":"tag-mains-articles","10":"tag-upsc-current-affairs","11":"tag-upsc-mains-current-affairs","12":"no-featured-image-padding"},"acf":[],"_links":{"self":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/88861","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/comments?post=88861"}],"version-history":[{"count":4,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/88861\/revisions"}],"predecessor-version":[{"id":88878,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/88861\/revisions\/88878"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media\/88866"}],"wp:attachment":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media?parent=88861"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/categories?post=88861"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/tags?post=88861"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}