CPUs and GPUs are similar, made up of millions of transistors and processing thousands of operations per second. Despite their similarities,...
CPUs and GPUs are similar, made up of millions of transistors and processing thousands of operations per second. Despite their similarities, initially, they were created to solve different problems. In the article, we understand how the CPU and GPU differ and what tasks they solve.WHAT ARE CPU AND GPU
The central processing unit (CPU ) is the central node that controls all the processes in the computer. For example, it performs arithmetic and logical operations with data, transfers results to external devices, and stores the results of operations performed. Any gadgets work with the CPU, be it a tablet or a smartphone.A graphics processing unit (GPU) is a microprocessor that speeds up the graphics that are displayed on the screen. Previously, it was used mainly for rendering images, and 3D modeling. Now GPUs are used for high-performance computing, machine learning, and scientific research.
DIFFERENCES BETWEEN GPU AND CPU
Number of Cores
The CPU usually has 4-8 cores that work independently of each other. The CPU architecture is usually based on the principle of fewer but more powerful processing cores. There are much more cores in the GPU - from 100 to 1000, but they are less powerful than the CPU.Data processing method
The CPU is a general-purpose processor, it performs sequential tasks. For example, computing, managing the operating system, and executing programs.In turn, the GPU processes data in parallel, allowing it to perform intensive tasks such as graphics rendering, 3D modeling, machine learning, and HCI.
Device memory usage
For the CPU, cache memory is a key parameter, so it takes up a large amount of device memory. The GPU does not need a large cache. For example, 128-256 kB is sufficient for rendering images.Calculation speed
Clock speed is one of the main technical indicators of any processor, which is measured in hertz. The higher this indicator, the more calculations per unit of time the equipment will have time to do. Unlike the CPU, applications on the GPU run faster, without jumps.Number of threads
The central processor supports up to two computing threads per core, and the graphics processor supports several thousand threads per multiprocessor, of which there are several in the chip. To switch from one thread to another, the CPU needs hundreds of cycles, while the GPU switches several threads in one cycle.CPU AND GPU TASKS
When using the CPU:- work with common applications such as word processing, spreadsheets, or other office documents;
- processing large amounts of data, but this data is not graphics;
- performing multiple tasks in sequence.
When is a GPU best suited:
- working with graphics such as 3D modeling, data visualization, and image or video processing;
- machine learning or scientific calculations that require processing power;
- use of parallel algorithms.
WHEN CPU AND GPU WORK TOGETHER
The CPU and GPU can work together to increase data throughput and simultaneous computing. The GPU can augment the architecture of the CPU to perform repetitive computations in parallel while other activities are performed sequentially on the CPU. Plus, each of the processors is engaged in its immediate tasks: the GPU performs complex calculations, and the CPU coordinates a wide range of actions.
WHAT IS THE DIFFERENCE BETWEEN PROCESSORS FOR COMPUTERS AND SERVERS
Computer processors differ in architecture from server processors. The CPU on servers put forward special requirements for reliability and reliability. These processors are designed for round-the-clock operation and high loads.GPUs for servers are also tuned for load in non-stop mode. Even if the processors for the computer and the server are externally similar, their technical characteristics will differ. Nvidia offers dedicated GPU lines for server hardware called TESLA and QUADRO. AMD has FirePro or Radeon & Vega for servers.
RENT OF CLOUD SERVERS WITH GPU
Now renting cloud servers with GPUs is one of the most popular services for businesses. Companies get computing power to solve a variety of problems without the need for investments in equipment and long waiting times for deliveries. In the cloud, you can use resources depending on the needs of the project.AI Cloud service - GPU cloud computing. This is a rental of cloud servers with GPUs. They enable businesses to work effectively with machine learning, advanced analytics, AI, high-performance computing, and 3D modeling.
