A multi-core processor is a single computing component with two or
more independent actual central processing units (called "cores"), which
are the units that read and execute program instructions. The
instructions are ordinary CPU instructions such as add, move data, and
branch, but the multiple cores can run multiple instructions at the same
time, increasing overall speed for programs amenable to parallel
computing. Manufacturers typically integrate the cores onto a single
integrated circuit die (known as a chip multiprocessor or CMP), or onto
multiple dies in a single chip package.
Processors were originally developed with only one core. Multi-core processors were developed in the early 2000s by Intel, AMD and others. Multicore processors may have two cores (Dual core) (e.g. AMD Phenom II X2, Intel Core Duo), four cores (Quad core) (e.g. AMD Phenom II X4, Intel's quad-core processors, see i5, and i7 at Intel Core), 6-cores (e.g. AMD Phenom II X6, Intel Core i7 Extreme Edition 980X), 8-cores (e.g. Intel Xeon E7-2820, AMD FX-8350), 10-cores (e.g. Intel Xeon E7-2850) or more. 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 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. Just as with single-processor systems, cores in multi-core systems may implement architectures such as superscalar, VLIW, vector processing, SIMD, or multithreading.
Multi-core processors are widely used across many application domains including general-purpose, embedded, network, digital signal processing (DSP), and graphics.
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 be 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 so much unless programmers invest a prohibitive amount of effort in re-factoring the whole problem. The parallelization of software is a significant ongoing topic of research.
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An Intel Core 2 Duo E6750 dual-core processor.
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An AMD Athlon X2 6400+ dual-core processor.
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Processors were originally developed with only one core. Multi-core processors were developed in the early 2000s by Intel, AMD and others. Multicore processors may have two cores (Dual core) (e.g. AMD Phenom II X2, Intel Core Duo), four cores (Quad core) (e.g. AMD Phenom II X4, Intel's quad-core processors, see i5, and i7 at Intel Core), 6-cores (e.g. AMD Phenom II X6, Intel Core i7 Extreme Edition 980X), 8-cores (e.g. Intel Xeon E7-2820, AMD FX-8350), 10-cores (e.g. Intel Xeon E7-2850) or more. 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 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. Just as with single-processor systems, cores in multi-core systems may implement architectures such as superscalar, VLIW, vector processing, SIMD, or multithreading.
Multi-core processors are widely used across many application domains including general-purpose, embedded, network, digital signal processing (DSP), and graphics.
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 be 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 so much unless programmers invest a prohibitive amount of effort in re-factoring the whole problem. The parallelization of software is a significant ongoing topic of research.
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An Intel Core 2 Duo E6750 dual-core processor.
An AMD Athlon X2 6400+ dual-core processor.
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Number of cores Common names
1 single-core
2 dual-core
3 tri-core , triple-core
4 quad-core
5 penta-core
6 hexa-core
7 hepta-core
8 octa-core, octo-core
9 nona-core
10 deca-core
11 hendeca-core
12 dodeca-core
13 trideca-core
14 tetradeca-core
15 pentadeca-core
16 hexadeca-core
17 heptadeca-core
18 octadeca-core
19 enneadeca-core
20 icosa-core
2 dual-core
3 tri-core , triple-core
4 quad-core
5 penta-core
6 hexa-core
7 hepta-core
8 octa-core, octo-core
9 nona-core
10 deca-core
11 hendeca-core
12 dodeca-core
13 trideca-core
14 tetradeca-core
15 pentadeca-core
16 hexadeca-core
17 heptadeca-core
18 octadeca-core
19 enneadeca-core
20 icosa-core
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