A multi-core processor (MCP) is a microprocessor on a single integrated circuit (IC) with two or more separate central processing units (CPUs), called cores to emphasize their multiplicity (for example, dual-core or quad-core). Each core reads and executes program instructions, specifically ordinary CPU instructions (such as add, move data, and branch). However, the MCP can run instructions on separate cores at the same time, increasing overall speed for programs that support multithreading or other parallel computing techniques. Manufacturers typically integrate the cores onto a single IC die, known as a chip multiprocessor (CMP), or onto multiple dies in a single chip package. As of 2024, the microprocessors used in almost all new personal computers are multi-core. A multi-core processor implements multiprocessing in a single physical package. Designers may couple cores in a multi-core device tightly or loosely. For example, cores may or may not share caches, and they may implement message passing or shared-memory inter-core communication methods. Common network topologies used to interconnect cores include bus, ring, two-dimensional mesh, and crossbar. Homogeneous multi-core systems include only identical cores; heterogeneous multi-core systems have cores that are not identical (e.g. big.LITTLE have heterogeneous cores that share the same instruction set, while AMD Accelerated Processing Units have cores that do not share the same instruction set). Just as with single-processor systems, cores in multi-core systems may implement architectures such as VLIW, superscalar, vector, or multithreading. Multi-core processors are widely used across many application domains, including general-purpose, embedded, network, digital signal processing (DSP), and graphics (GPU). Core count goes up to even dozens, and for specialized chips over 10,000, and in supercomputers (i.e. clusters of chips) the count can go over 10 million (and in one case up to 20 million processing elements total in addition to host processors). The improvement in performance gained by the use of a multi-core processor depends very much on the software algorithms used and their implementation. In particular, possible gains are limited by the fraction of the software that can run in parallel simultaneously on multiple cores; this effect is described by Amdahl's law. In the best case, so-called embarrassingly parallel problems may realize speedup factors near the number of cores, or even more if the problem is split up enough to fit within each core's cache(s), avoiding use of much slower main-system memory. Most applications, however, are not accelerated as much unless programmers invest effort in refactoring. The parallelization of software is a significant ongoing topic of research. Cointegration of multiprocessor applications provides flexibility in network architecture design. Adaptability within parallel models is an additional feature of systems utilizing these protocols. In the consumer market, dual-core processors (that is, microprocessors with two units) started becoming commonplace on personal computers in the late 2000s. In the early 2010s, quad-core processors were also being adopted in that era for higher-end systems before becoming standard by the mid 2010s. In the late 2010s, hexa-core (six cores) started entering the mainstream and since the early 2020s has overtaken quad-core in many spaces.
Terminology The terms multi-core and dual-core most commonly refer to central processing units (CPUs), but are sometimes applied to digital signal processors (DSPs) and systems on chip (SoCs). The terms are generally used only to refer to multi-core microprocessors that are manufactured on the same integrated circuit die; separate microprocessor dies in the same package are generally referred to by another name, such as multi-chip module. This article uses the terms "multi-core" and "dual-core" for CPUs manufactured on the same integrated circuit, unless otherwise noted. In contrast to multi-core systems, the term multi-CPU refers to multiple physically separate processing-units (which often contain special circuitry to facilitate communication between each other). The terms many-core and massively multi-core are sometimes used to describe multi-core architectures with an especially high number of cores (tens to thousands). Some systems use many soft microprocessor cores placed on a single FPGA. Each "core" can be considered a "semiconductor intellectual property core" as well as a CPU core.
Development While manufacturing technology improves, reducing the size of individual gates, physical limits of semiconductor-based microelectronics have become a major design concern. These physical limitations can cause significant heat dissipation and data synchronization problems. Various other methods are used to improve CPU performance. Some instruction-level parallelism (ILP) methods such as superscalar pipelining are suitable for many applications, but are inefficient for others that contain difficult-to-predict code. Many applications are better suited to thread-level parallelism (TLP) methods, and multiple independent CPUs are commonly used to increase a system's overall TLP. A combination of increased available space (due to refined manufacturing processes) and the demand for increased TLP led to the development of multi-core CPUs.
Apple's Scorpius CPU In 1985, Apple engineer Sam Holland convinced Apple to develop its own 4-processor CPU chip to power future Macs called Scorpius. The processor's proposed feature set was highly ambitious, including four cores and SIMD (vector) support with inter-processor communication features. With the design beyond the fabrication capabilities of the time, the project was brought to an end in 1989.
Early innovations: the Stanford Hydra project In the 1990s, Kunle Olukotun led the Stanford Hydra Chip Multiprocessor (CMP) research project. This initiative was among the first to demonstrate the viability of integrating multiple processors on a single chip, a concept that laid the groundwork for today's multicore processors. The Hydra project introduced support for thread-level speculation (TLS), enabling more efficient parallel execution of programs.
… excerpt ends here. Continue reading the full article.
