What are the differences between CPU and GPU?

The CPU (Central Processing Unit) and GPU (Graphics Processing Unit) are both types of processors used in computers, but they have different designs and purposes. CPU handles many functions of the system while the GPU handles graphics related tasks. CPUs are versatile processors optimized for single-threaded tasks and general-purpose computing, while GPUs are highly parallel processors designed for tasks that can be divided into multiple data streams. Both have their strengths and are used in various applications, depending on the workload requirements. Here are the key differences between CPUs and GPUs:

Architecture: 

CPUs and GPUs have different architectures optimized for different types of tasks. CPUs are designed for general-purpose computing and are responsible for executing most of the instructions in a computer program. They have a few powerful cores that can handle complex tasks and perform a wide range of calculations. On the other hand, GPUs are specialized for parallel processing and are designed to handle large amounts of data simultaneously. They consist of hundreds or even thousands of smaller, less powerful cores that can work together on multiple tasks at the same time.

Instruction Set: 

CPUs and GPUs have different instruction sets tailored to their respective architectures. CPUs have a diverse instruction set that can handle a wide range of tasks, including arithmetic, logical operations, data manipulation, and control flow. GPUs have a more limited instruction set focused on graphics-related operations such as rendering, shading, and image processing. However, modern GPUs also support general-purpose computing through frameworks like CUDA (Compute Unified Device Architecture) and OpenCL.

Performance: 

GPUs excel at parallel processing tasks where large amounts of data can be processed simultaneously. They can perform calculations on multiple data elements simultaneously, making them highly efficient for tasks like 3D rendering, video encoding, scientific simulations, machine learning, and cryptocurrency mining. CPUs, with their powerful cores, are better suited for single-threaded tasks that require high per-core performance, such as general computing, operating systems, web browsing, and everyday tasks.

Memory Hierarchy: 

CPUs and GPUs have different memory architectures. CPUs have multiple levels of cache memory, including L1, L2, and sometimes L3 caches, which are located closer to the CPU cores. These caches store frequently accessed data to minimize the latency of accessing main memory. GPUs, on the other hand, have larger on-chip memory called VRAM (Video RAM), which is designed to store massive amounts of data needed for parallel processing. GPUs can transfer data between CPU and GPU memory, but it incurs additional latency compared to CPU caches.

Power Consumption: 

CPUs and GPUs have different power requirements and consumption levels. CPUs are designed to operate at lower power levels since they are typically used in a wide range of devices, including laptops and mobile devices, where power efficiency is crucial. GPUs, especially high-end models, require more power due to their larger number of cores and the need to handle intense computational workloads. Consequently, GPUs generate more heat and often require additional cooling mechanisms like fans or liquid cooling.