Quad Core T3 P1 Update

[Blanche Bunnell]

Amulti-core processor is a microprocessor on a single integrated circuit with two or more separate processing units, called cores (for example, dual-core or quad-core), each of which reads and executes program instructions.[1] The instructions are ordinary CPU instructions (such as add, move data, and branch) but the single processor can run instructions on separate cores at the same time, increasing overall speed for programs that support multithreading or other parallel computing techniques.[2] 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. The microprocessors currently used in almost all 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,[3] 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).[4]

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.[5]

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.[6]

In the consumer market, dual-core processors (that is, microprocessors with two units) started becoming commonplace on personal computers in the late 2000s.[7] Quad-core processors were also being adopted in that era for higher-end systems before becoming standard. In the late 2010s, hexa-core (six cores) started entering the mainstream[8] and since the early 2020s has overtaken quad-core in many spaces.[9]

The terms multi-core and dual-core most commonly refer to some sort of central processing unit (CPU), but are sometimes also applied to digital signal processors (DSP) and system on a chip (SoC). 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).

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.

Several business motives drive the development of multi-core architectures. For decades, it was possible to improve performance of a CPU by shrinking the area of the integrated circuit (IC), which reduced the cost per device on the IC. Alternatively, for the same circuit area, more transistors could be used in the design, which increased functionality, especially for complex instruction set computing (CISC) architectures. Clock rates also increased by orders of magnitude in the decades of the late 20th century, from several megahertz in the 1980s to several gigahertz in the early 2000s.

As the rate of clock speed improvements slowed, increased use of parallel computing in the form of multi-core processors has been pursued to improve overall processing performance. Multiple cores were used on the same CPU chip, which could then lead to better sales of CPU chips with two or more cores. For example, Intel has produced a 48-core processor for research in cloud computing; each core has an x86 architecture.[12][13]

Since computer manufacturers have long implemented symmetric multiprocessing (SMP) designs using discrete CPUs, the issues regarding implementing multi-core processor architecture and supporting it with software are well known.

In order to continue delivering regular performance improvements for general-purpose processors, manufacturers such as Intel and AMD have turned to multi-core designs, sacrificing lower manufacturing-costs for higher performance in some applications and systems. Multi-core architectures are being developed, but so are the alternatives. An especially strong contender for established markets is the further integration of peripheral functions into the chip.

The proximity of multiple CPU cores on the same die allows the cache coherency circuitry to operate at a much higher clock rate than what is possible if the signals have to travel off-chip. Combining equivalent CPUs on a single die significantly improves the performance of cache snoop (alternative: Bus snooping) operations. Put simply, this means that signals between different CPUs travel shorter distances, and therefore those signals degrade less. These higher-quality signals allow more data to be sent in a given time period, since individual signals can be shorter and do not need to be repeated as often.

Assuming that the die can physically fit into the package, multi-core CPU designs require much less printed circuit board (PCB) space than do multi-chip SMP designs. Also, a dual-core processor uses slightly less power than two coupled single-core processors, principally because of the decreased power required to drive signals external to the chip. Furthermore, the cores share some circuitry, like the L2 cache and the interface to the front-side bus (FSB). In terms of competing technologies for the available silicon die area, multi-core design can make use of proven CPU core library designs and produce a product with lower risk of design error than devising a new wider-core design. Also, adding more cache suffers from diminishing returns.

Multi-core chips also allow higher performance at lower energy. This can be a big factor in mobile devices that operate on batteries. Since each core in a multi-core CPU is generally more energy-efficient, the chip becomes more efficient than having a single large monolithic core. This allows higher performance with less energy. A challenge in this, however, is the additional overhead of writing parallel code.[15]

Maximizing the usage of the computing resources provided by multi-core processors requires adjustments both to the operating system (OS) support and to existing application software. Also, the ability of multi-core processors to increase application performance depends on the use of multiple threads within applications.

Integration of a multi-core chip can lower the chip production yields. They are also more difficult to manage thermally than lower-density single-core designs. Intel has partially countered this first problem by creating its quad-core designs by combining two dual-core ones on a single die with a unified cache, hence any two working dual-core dies can be used, as opposed to producing four cores on a single die and requiring all four to work to produce a quad-core CPU. From an architectural point of view, ultimately, single CPU designs may make better use of the silicon surface area than multiprocessing cores, so a development commitment to this architecture may carry the risk of obsolescence. Finally, raw processing power is not the only constraint on system performance. Two processing cores sharing the same system bus and memory bandwidth limits the real-world performance advantage.

The trend in processor development has been towards an ever-increasing number of cores, as processors with hundreds or even thousands of cores become theoretically possible.[16] In addition, multi-core chips mixed with simultaneous multithreading, memory-on-chip, and special-purpose "heterogeneous" (or asymmetric) cores promise further performance and efficiency gains, especially in processing multimedia, recognition and networking applications. For example, a big.LITTLE core includes a high-performance core (called 'big') and a low-power core (called 'LITTLE'). There is also a trend towards improving energy-efficiency by focusing on performance-per-watt with advanced fine-grain or ultra fine-grain power management and dynamic voltage and frequency scaling (i.e. laptop computers and portable media players).

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