A GPU or other accelerators are ideal for deep learning training with neural network layers or on massive sets of certain data, like 2D images.ĭeep learning algorithms were adapted to use a GPU-accelerated approach. Today, GPUs run a growing number of workloads, such as deep learning and artificial intelligence (AI). Such an approach is most often employed with devices for which a compact size and energy efficiency are important, such as laptops, tablets, smartphones, and some desktops. They bring the power to handle the processing of graphics-related data and instructions for common tasks like exploring the web, streaming 4K movies, and casual gaming. Their integration with CPUs allows them to deliver space, cost, and energy efficiency benefits over dedicated graphics processors. Integrated graphics processors offer several benefits. Certain CPUs can come with a built-in GPU instead of relying on dedicated or discrete graphics. Integrated or shared graphics are built onto the same chip as the CPU.
While graphics and the increasingly lifelike visuals of today’s top games remain their principal function, GPUs have evolved to become more general-purpose parallel processors as well, handling a growing range of applications. Over time, these fixed-function engines became more programmable and more flexible. GPUs began as specialized ASICs developed to accelerate specific 3D rendering tasks.
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This makes it uniquely well equipped for jobs ranging from serial computing to running databases. A powerful execution engine, the CPU focuses its smaller number of cores on individual tasks and on getting things done quickly. The CPU is suited to a wide variety of workloads, especially those for which latency or per-core performance are important. But CPUs and GPUs have different architectures and are built for different purposes. What Is the Difference Between a CPU and GPU?ĬPUs and GPUs have a lot in common. The GPU is a processor that is made up of many smaller and more specialized cores. By working together, the cores deliver massive performance when a processing task can be divided up and processed across many cores. It is essential to all modern computing systems as it executes the commands and processes needed for your computer and operating system. The CPU is also important in determining how fast programs can run, from surfing the web to building spreadsheets. What are CPUs used for? What are GPUs used for? Knowing the role that each device plays is important when shopping for a new computer and comparing specifications.Ĭonstructed from millions of transistors, the CPU can have multiple processing cores and is commonly referred to as the brain of the computer. A central processing unit (CPU) and a graphics processing unit (GPU) have very different roles. Whether for deep learning applications, massive parallelism, intense 3D gaming, or another demanding workload, systems today are being asked to do more than ever before.
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