CPU Vs GPU: What Is The Difference?

Modern computing systems are built to address a wide range of business requirements and personal interests. A computer’s central processing unit (CPU) is responsible for controlling the data flow and carrying out instructions. It is unquestionably the most essential piece among many critical computer components comprising a modern machine.

While CPUs are extremely important for complex computing tasks, some applications benefit from running on a more specialized processor. Employing a graphics processing unit (GPU) rather than a general-purpose processor can result in substantially improved performance for certain tasks that can be more efficiently addressed with parallel processing. GPUs have become increasingly important to handle the parallel instruction processing necessary to power artificial intelligence (AI) applications.

This article examines the key differences between CPUs and GPUs. One main difference is that a computer can operate with only a CPU, but a GPU needs to be paired with a CPU to function properly. We will investigate how these processors differ physically and the types of problems they are best suited to address. Finally, we will examine typical usage scenarios for both processing units.

What Is a Central Processing Unit (CPU)?

A CPU is the main computer component and is responsible for the majority of processing tasks. It essentially acts as a computer’s brain. The CPU processes instructions from a computer’s memory to perform specific arithmetic, logical, control, and input/output operations.

CPU components

CPUs are constructed using several key components that perform serial instruction processing.

• Control unit: The control unit (CU) manages the CPU’s operation. It coordinates the activities of the other CPU components as it executes instructions to perform tasks required by the operating system or applications. The CU decodes instructions to determine CPU activity, generates signals to other components like the ALU, manages data flow, and ensures the operations of all parts of the CPU are synchronized.
• Arithmetic logic unit: The ALU is a primary CPU component responsible for multiple tasks essential to a computer system’s operation based on signals sent from the CPU’s control unit. A CPU’s arithmetic logic units perform basic arithmetic functions like addition and multiplication. It also performs logical operations such as AND, NOT, or XOR for decision-making and comparisons. The performance of a CPU can be substantially affected by the speed and efficiency of arithmetic logic units.
• Cores: A CPU core is a processing unit within a CPU that independently executes instructions. CPU cores enable the processor to perform multiple tasks simultaneously. CPUs can have multiple cores, with more cores typically resulting in improved multithreading capability. Cores share resources like buses and cache memory, which can impact their performance. Modern CPU architecture enables cores to adjust performance dynamically based on workload requirements.
• Cache memory: The CPU cache memory is dedicated storage for frequently accessed data. This high-speed, built-in memory can substantially increase processing speed by reducing the need to load data from other locations. There can be multiple caches of varying sizes to handle data overflow. While a larger cache can hold more data, it may result in slower operations than a smaller, optimized cache.
• Registers: CPU registers are small and fast storage locations inside the CPU. They are critical to the CPU’s operation and store instructions and temporary data. Registers are directly accessible by the CPU, making them much faster than the main memory. A register is usually no larger than 64 bits, limiting the amount of data it can hold. A CPU can have several types of registers including general-purpose registers used for various purposes and specialized registers such as the program counter that holds the address of the next instruction.
• Buses: A bus provides a high-speed, internal connection that transfers information between the CPU and other computing resources. Buses can be serial, transferring data one bit at a time, or parallel, capable of transmitting multiple bits simultaneously. Different types of buses are used as the CPU performs various tasks. For example, data buses carry data between the CPU and other components while an address bus transmits the memory location of data elements. Bus width and speed can impact the CPU’s performance.
• Clock: The CPU clock, also known as the system clock, continuously generates pulses to synchronize the operation of the CPU and other computer components. Clock speed is measured in hertz (Hz) and indicates how many cycles a CPU can execute per second. For example, a clock speed of 2 GHz generates two billion cycles per second. The clock provides timing control and synchronization for all internal components. Modern CPUs can dynamically adjust clock speed to reduce power consumption and minimize heat generation.

CPU characteristics and functionality

The main function of a central processing unit is to perform logical operations and instructions received from the computer’s memory. The ability to perform these operations and process data efficiently is a function of the combined capabilities of its components. CPUs are designed to perform serial processing. They execute elements in the instruction cycle one at a time.

A CPU’s components determine its serial computing capabilities. The clock speed provides a benchmark for the amount of processing the chip can handle. A higher clock speed generally indicates a faster-performing computer. Cache memory must be tuned to balance the volume of data it can hold and the latency in accessing that information.

The number of cores is another factor in determining the power of a CPU. Additional cores allow the CPU to perform multithreading to perform calculations and other tasks more efficiently. A multi-core CPU with a high clock speed usually furnishes the best performance.

CPU Architectures

Multiple CPU architectures have been developed to address computational requirements. They can generally be categorized as either a Complex Instruction Set Computer (CISC) or a Reduced Instruction Set Computer based on the number of machine instructions it contains.

The following are some popular CPU architectures found in modern computers.

• 32-bit x86 – This architecture is commonly found in laptop and desktop computers and processes data in 32-bit chunks per clock cycle. It is a CISC architecture first released by Intel in 1978.
• 64-bit x86 – This more modern CPU processes data 64 bits at a time and can address more memory than 32-bit processors. Intel and AMD use the architecture which is a popular solution for home computers and servers
• ARM64 – This RISC architecture can process more instructions per second than Intel processors. They are energy-efficient, making them a good choice for sustainable computing initiatives.
• PowerPC – This RISC architecture is based on IBM’s POWER architecture.  Memory access is separated from computational instructions by a register-to-register design.

Types of CPUs

CPUs are manufactured with specific characteristics and form factors to address various computing tasks.

Desktop CPUs

Desktop CPUs are available in multiple models offering different performance levels suitable for various tasks. The Intel Core Series and AMD’s Ryzen line are desktop CPUs used in many popular desktop machines.

Mobile CPUs

Mobile devices like laptops need to balance performance and power consumption. The Intel Core Mobile and AMD Ryzen Mobile processors are popular mobile CPUs providing good performance while supporting energy efficiency.

Embedded CPUs

Embedded CPUs are specialized microprocessors designed to perform specific tasks in embedded systems. These dedicated devices typically provide limited and specialized functionality compared with a general-use computer system. Features of embedded CPUs include durability, low power consumption, and real-time operation. Embedded CPUs often integrate multiple components on a single chip to reduce their size and energy requirements.

Server CPUs

Server CPUs need additional power and functionality to handle multiple tasks supporting business applications. A server CPU may offer more cores and error-correcting code memory support. Examples of server CPUs include the Intel Xeon and AMD EPYC lines of processors.

Low-power CPUs

Devices with energy constraints like equipment used for IoT (Internet of Things) implementations require specialized, low-power CPUs. Examples of these energy-efficient CPUs include ARM-based processors and Intel’s Atom designed for compact devices.

Gaming CPUs

Gaming platforms may employ specialized CPUs optimized for the high performance required by video and computer games. These CPUs provide higher clock speeds and can perform overclocking when necessary to facilitate a smoother gaming experience.

High-performance CPUs

Supercomputers and machines running processor-intensive tasks benefit from specialized high-performance CPUs. This type of CPU focuses on supporting high-performance computing with multithreading and typically has multiple cores.

What is a Graphics Processing Unit (GPU)?

A graphics processing unit is a specialized processor designed to render images and perform complex mathematical calculations. GPUs typically work in conjunction with a CPU. Some architectures place the CPU and GPU on the same chip. The terms GPU and graphics card are sometimes incorrectly used interchangeably. The GPU is the processor inside a graphics card.

GPU Cores

GPU cores are the processor’s foundational processing unit. Cores share similar characteristics that support the GPU’s functionality.

• GPU cores handle multiple tasks simultaneously, supporting the parallel processing necessary to display graphical data efficiently. Each core can manage numerous threads to streamline concurrent operations.
• GPU cores are constructed differently than CPU cores, enabling many cores to be deployed to address parallel workloads and advanced scientific research. In some cases, a high-performance GPU may have thousands of cores.
• Cores are optimized to increase the processor’s performance with the floating-point calculations important for tasks like displaying images or teaching machine learning models. They share resources such as cache memory for efficiency.

GPU components

GPUs utilize several key components to perform concurrent calculations and parallel computing capabilities.

• Streaming multiprocessors and cores: These processors represent the GPU’s basic processing units used to execute multiple threads. NVIDIA GPUs employ CUDA cores and AMD GPUs use stream processors for this component. More cores enable the GPU to handle parallel computing tasks more efficiently.
• Memory: Video RAM (VRAM) is specialized memory the GPU utilizes for computer graphics as it provides faster data transfer than system memory. The GPU also has cache memory to improve processing speed by storing frequently accessed data.
• Framebuffer: This component stores the GPUs finished image before it is displayed. Before reaching the framebuffer, a rasterizer converts vector graphics into pixel-based graphics, and textures are applied to 3D models.
• Cooling systems and power management circuits: GPUs can get very hot. Managing power consumption and effectively cooling the processor are critical factors in maintaining high performance.

GPU characteristics and functionality

GPUs demonstrate characteristics and functionality that differentiate them from CPUs. The following are some areas where a GPU can outperform a CPU.

Computer graphics

GPUs were originally developed primarily for rendering graphics to support video games and other visual computerized activities. GPUs are integral to the manufacture of high-performing gaming platforms. They are also critical for displaying complex information graphically to make it more easily understood.

Parallel processing

GPUs are essential for parallel processing applications that handle large volumes of data. The many cores in a GPU can quickly perform repetitive calculations to address the computing needs of financial simulations and other processor-intensive tasks.

Throughput and dedicated memory

Thousands of cores and dedicated memory enable GPUs to perform multiple operations simultaneously and more quickly than CPUs accessing system RAM. Better performance across a range of graphics and processor-intensive applications is possible by leveraging the power of GPUs.

Compatibility

GPUs are compatible with graphics APIs like DirectX or frameworks such as CUDA for parallel processing. This compatibility lets developers benefit from specific GPU capabilities when designing new products.

Types of GPUs

Graphics processing units are available in multiple styles for specific usage scenarios.

• Dedicated GPUs: A dedicated or discrete GPU is typically a standalone graphics card or video card used for high-performance tasks.
• Integrated GPUs: This type of GPU is built on a single chip with the CPU to share resources such as system memory and reduce energy consumption.
• Hybrid GPUs: Hybrid GPUs can switch between dedicated and integrated capabilities to provide enhanced performance or conserve energy based on application requirements.

CPU Vs GPU for Specific Usage Scenarios

The types of tasks and applications running on a given computer must be considered when choosing between a CPU and GPU. Many tasks will run efficiently with a CPU that provides enough speed, cores, and memory. In other cases, users will greatly benefit from the features and performance of a GPU.

The chart below indicates how CPUs and GPUs address some specific usage scenarios. This information may help you select the appropriate platform for your application.

Atlantic Net Servers Feature Modern CPUs and GPUs

Atlantic Net offers customers modern CPU and GPU server hosting solutions designed to address your unique business objectives and requirements. Our servers can support virtually any application with an appropriate choice of processor and other components.

Talk to us today and learn how we can help your business grow with the right CPU or GPU.