GPU Definition | The Role of a Graphics Processing Unit Explained

The graphics processing unit is an essential computing technology responsible for rendering 3D videos and animations and smooth decoding. It is a vital technology used for personal and business computing, and it helps in rendering graphics and videos. The specialized processing unit is also an excellent choice for machine-learning tasks.

The GPU comes as a stand-alone card to plug in the PCI express bus. On the other hand, the GPU can be part of the motherboard chipset, and you can find it on the CPU chip. Stand-alone GPUs feature their own memory but GPUs that are part of the CPU or motherboard chipset share memory with the CPU.

So, what is the best GPU definition?

GPU card blue

What Does GPU Mean?

GPU stands for the graphics processing unit. It is a processor that specializes in image rendering on your PC's screen. Graphics processing units offer the fastest processing of graphics. The GPU for gaming comes as a stand-alone card that you plug in the PCI express bus. The GPU's circuitry can be a component of the central processing unit chip or the motherboard chipset.

The GPU technology is essential in rendering graphics, editing videos and graphics, and ensures smooth decoding. An integrated GPU is used in mining digital currencies, including Bitcoin. As mentioned earlier, GPUs are used to render graphics. Additionally, they are used to do parallel operations on various data sets that are used for AI and scientific applications that need repetitive computations.

Apart from its CPU, a supercomputer can also feature thousands of integrated GPUs. Graphical processing is a complex task for your computer's CPU. Solving the complexity of graphics processing has resulted in advancements in technology beyond graphics.

Graphics require complex mathematics to render, and the maths should compute in parallel to work well. CPUs may not have the capacity to work with such workloads, and that's where GPU computing comes in.

GPUs are similar in function to CPUs, and they contain memory, core, and other components. However, instead of switching context to manage various tasks, GPUs feature parallel processing capabilities, and they use a large number of cores for parallel data processing.

GPU with blue background

Individual cores of the GPU are less powerful than the core of a CPU. Additionally, the graphics processing units feature less interoperability with houseless memory and various hardware APIs. They are best at working on an immense amount of data in parallel. GPUs will take multiple instructions together and push them out at high processing power to hasten data processing and display.

Advantages of GPUs 

While CPUs are ideal for general data computing, GPUs are used for high-performance computing. Some advantages of an integrated graphics processing unit include:

  • Incredible parallel computing: GPUs are effective in extensive calculations with parallel operations such as modeling complex systems

  • High Data Processing: A graphics processing unit features several cores that perform the same operation on various data items in parallel. Thus, it speeds up tasks beyond what a CPU can by pushing large amounts of data through a workload

The two advantages are the main functions of a GPU as they help in complex graphics processing. However, engineers and developers employ the GPU in other high-performance tasks, including:

  • Cryptocurrency mining involves complex and rapid mathematical calculations to solve complex cryptographic equations. The mining process uses a GPU to handle large amounts of cryptographic data.

Analytics and data science: GPUs assist analytics programs in processing immense volumes of base data from various sources.

Disadvantages 

  • Computing power and complexities: While a GPU effectively handles large amounts of data, they are not as effective if the computing requirements are chaotic. For instance, sequential operations and branching logic paths curtail the GPU's effectiveness.

  • Expensive: Although GPUs' price has gone down over the years, they are still expensive. The cost goes up if you are talking about a GPU with a specific task such as data mining or analytics.

Multitasking: Although GPUs are excellent in handling large amounts of data, they are not effective in multitasking. Thus, GPUs are not the best for tasks such as general-purpose computing.

What Is the Role of a Graphics Processing Unit?

The graphics processing unit is an essential technology for personal and business computing. GPU is ideal for parallel computing and is helpful for a wide range of applications, including video editing and graphics rendering. GPUs are popular for their role in gaming as they can handle complex gaming computations.

Besides their role in gaming, GPUs are also gaining popularity in artificial intelligence (AI) applications and in creative production. Initially, the graphics processing units were meant to enhance 3D graphics rendering. However, they became more programmable and flexible over time, pushing their capabilities beyond the 3D rendering. Thus, graphic designers and programmers can develop realistic scenes and interesting visual effects using shadowing techniques and lighting.

Other developers also use the power of GPU in deep learning and high-performance computing to accelerate additional workloads.

GPU cartooned

The GPU and the CPU work together on your computer. The GPU is a complement to the CPU in your computer. CPU is ideal for general computing purposes, and it also helps in general multitasking tasks. However, the CPU cannot handle complex computing tasks such as analytics, machine learning, cryptographic computations, etc.

On the other hand, the GPU is similar to the CPU in various aspects, such as it comes with cores and memory. However, the individual cores of the GPU are weaker than that of the CPU. Whereas the CPU cannot handle complex computations, the GPU is the master of complexities. It is ideal for dealing with complex processes such as data analytics. But the GPU is not effective in dealing with general computing processes and multitasking.

The GPU and CPU work together in your computer to deal with general and complex processes. When you want to purchase a monitor, it'll be beneficial to understand both roles to ensure full utilization.

Is the Graphics Processing Unit a Graphics Card? 

It is not uncommon to find the terms graphics card and GPU used interchangeably though they are distinguished. The motherboard in your computer carries the CPU. In the same way, a graphics card is an add-in board that carries the GPU. The graphics card also contains other components that enable the GPU to connect with other system parts and function well.

GPUs are of two types that include the discrete and integrated GPUs.

Integrated GPUs

An integrated GPU doesn't feature a separate card, but it is embedded with the CPU. Most of the GPUs in the market are integrated GPUs. A CPU that features an integrated CPU on its motherboard allows lighter systems, lower system costs, and reduced power consumption.

Discrete GPUs 

A discrete GPU comes as a distinct chip that you mount on a circuit board. You attach a discrete GPU to a PCI Express slot. Most computing applications can use integrated GPUs. However, if the applications are more demanding and resource-intensive, a discrete GPU, also known as a dedicated graphics card, is an excellent option.

Discrete GPUs have more energy consumption, and they also create a lot of heat due to the processing power. The GPU requires cooling to offer maximum performance
Gpu card blue-violet


Differences Between a GPU and CPU

The most significant difference between a GPU architecture and a CPU is in how they function. A CPU is ideal for multitasking and handles a wide range of general computing tasks fast as measured by the CPU clock speed. A CPU is limited in the complexity and concurrency of functions it can handle. For instance, a central processing unit will have challenges handling complex games, machine learning, and data analytics.

On the other hand, a GPU helps in rendering high-resolution photos and videos fast and concurrently. They can also perform parallel operations on multiple data sets. They come in handy in performing tasks such as scientific computation, cryptographic computations, and machine learning.

CPU card

GPUs feature thousands of cores that run simultaneously. Therefore, they allow immense parallelism, a process that involves each core focusing on making efficient calculations. GPUs can process data in a bigger magnitude than CPUs due to the immense parallelism. However, they are not as versatile as the central processing units. CPUs feature large sets of instructions that enable them to control every input and output from your computer, which is not possible with a GPU.

While individual CPU cores are smarter and faster, the massive number of cores and massive parallelism of GPU compensate for the single-core speed. GPUs are a perfect choice for repetitive tasks.

Conclusion 

GPU or graphics processing unit is a technology that unlocks possibilities in machine learning, gaming, content creation, and data analytics. It is a vital technology both for personal and business computing. Unlike the CPU that comes with a smart and fast core, GPUs feature hundreds of cores, with each working individually and focusing on making efficient calculations. GPUs come in two types that include the discrete and integrated GPUs. Integrated GPUs are embedded alongside the CPU while the discrete ones are mounted on a circuit board, and you attach them on a PCI Express slot.

About Dusan Stanar

I'm the founder of VSS Monitoring. I have been both writing and working in technology in a number of roles for dozens of years and wanted to bring my experience online to make it publicly available. Visit https://www.vssmonitoring.com/about-us/ to read more about myself and the rest of the team.

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