TLDR: Multi-core architectures refer to processors that integrate two or more independent cores within a single chip, enabling parallel execution of tasks. Introduced in the early 2000s as a solution to physical and thermal limits of single-core processors, these architectures improve performance, energy efficiency, and multitasking capabilities. Multi-core architectures are now the standard for CPUs, GPUs, and specialized processors, powering applications ranging from personal computing to cloud computing and artificial intelligence.

https://en.wikipedia.org/wiki/Multi-core_processor

Each core in a multi-core architecture operates as an independent processing unit, capable of executing its own thread or process. This design allows multiple threads to run simultaneously, enhancing performance for multi-threaded applications like video editing, 3D rendering, and machine learning. Processors such as Intel Core i9 and AMD Ryzen Threadripper feature up to dozens of cores, while server-grade chips like AMD EPYC scale beyond 64 cores to handle high-performance workloads in data centers and supercomputing environments.

https://www.amd.com/en/products/epyc

Software optimization is critical for leveraging the benefits of multi-core architectures. Frameworks and tools like Java concurrency libraries, OpenMP, and parallel processing APIs enable developers to distribute workloads efficiently across cores. However, tasks that are inherently sequential may not benefit significantly from additional cores. Balancing core count, clock speed, and memory bandwidth is essential for maximizing the advantages of multi-core architectures in diverse computational tasks.

https://www.oracle.com/java/technologies/javase/concurrency.html