A multi-core processor is a single computing component with two or more independent actual processors (called "cores"), which are the units that read and execute program instructions.[1] The instructions are ordinary cpu instructions like 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. A many-core processor is a multi-core processor in which the number of cores is large enough that traditional multi-processor techniques are no longer efficient — largely because of issues with congestion in supplying instructions and data to the many processors. The many-core threshold is roughly in the range of several tens of cores; above this threshold network on chip technology is advantageous. Tilera processors feature a switch in each core to route data through an on-chip mesh network to lessen the data congestion, enabling their core count to scale up to 100 cores.
A dual-core processor has two cores (e.g. AMD Phenom II X2, Intel Core Duo), a quad-core processor contains four cores (e.g. AMD Phenom II X4, intel's quad-core processors, see i3, i5, and i7 at Intel Core), a hexa-core processor contains six cores (e.g. AMD Phenom II X6, Intel Core i7 Extreme Edition 980X), an octa-core processor contains eight cores (e.g. AMD FX-8150). 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 which 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 parallelized to run on multiple cores simultaneously; 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[2]. The parallelization of software is a significant ongoing topic of research.
Contents |
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).
The terms many-core and massively multi-core are sometimes used to describe multi-core architectures with an especially high number of cores (tens or hundreds).
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.
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 dual-core architectures. For decades, it was possible to improve performance of a CPU by shrinking the area of the integrated circuit, which drove down the cost per device on the IC. Alternatively, for the same circuit area, more transistors could be utilized in the design, which increased functionality, especially for 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 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 which had two or more cores. Intel has produced a 48-core processor for research in cloud computing.[3]
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.
Additionally:
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 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.
The largest boost in performance will likely be noticed in improved response-time while running CPU-intensive processes, like antivirus scans, ripping/burning media (requiring file conversion), or file searching. For example, if the automatic virus-scan runs while a movie is being watched, the application running the movie is far less likely to be starved of processor power, as the antivirus program will be assigned to a different processor core than the one running the movie playback.
Assuming that the die can fit into the package, physically, the 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 multi-core is generally more energy-efficient, the chip becomes more efficient than having a single large monolithic core. This allows to get higher performance with less energy. The challenge of writing parallel code clearly offsets this benefit.[4]
Maximizing the utilization 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. The situation is improving: for example the Valve Corporation's Source engine offers multi-core support,[5][6] and Crytek has developed similar technologies for CryEngine 2, which powers their game, Crysis. Emergent Game Technologies' Gamebryo engine includes their Floodgate technology[7] which simplifies multicore development across game platforms. In addition, Apple Inc.'s second latest OS, Mac OS X Snow Leopard has a built-in multi-core facility called Grand Central Dispatch for Intel CPUs.
Integration of a multi-core chip drives chip production yields down and they are more difficult to manage thermally than lower-density single-chip designs. Intel has partially countered this first problem by creating its quad-core designs by combining two dual-core 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. 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. If a single core is close to being memory-bandwidth limited, going to dual-core might only give 30% to 70% improvement. If memory bandwidth is not a problem, a 90% improvement can be expected. It would be possible for an application that used two CPUs to end up running faster on one dual-core if communication between the CPUs was the limiting factor, which would count as more than 100% improvement.
The general trend in processor development has moved from dual-, tri-, quad-, hexa-, octo-core chips to ones with tens or even hundreds of cores. In addition, multi-core chips mixed with simultaneous multithreading, memory-on-chip, and special-purpose "heterogeneous" cores promise further performance and efficiency gains, especially in processing multimedia, recognition and networking applications. There is also a trend of 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).
The composition and balance of the cores in multi-core architecture show great variety. Some architectures use one core design repeated consistently ("homogeneous"), while others use a mixture of different cores, each optimized for a different, "heterogeneous" role.
The article "CPU designers debate multi-core future by Rick Merritt, EE Times 2008,[8] includes these comments:
Chuck Moore [...] suggested computers should be more like cellphones, using a variety of specialty cores to run modular software scheduled by a high-level applications programming interface.[...] Atsushi Hasegawa, a senior chief engineer at Renesas, generally agreed. He suggested the cellphone's use of many specialty cores working in concert is a good model for future multi-core designs.
[...] Anant Agarwal, founder and chief executive of startup Tilera, took the opposing view. He said multi-core chips need to be homogeneous collections of general-purpose cores to keep the software model simple.
An outdated version of an anti-virus application may create a new thread for a scan process, while its GUI thread waits for commands from the user (e.g. cancel the scan). In such cases, a multicore architecture is of little benefit for the application itself due to the single thread doing all heavy lifting and the inability to balance the work evenly across multiple cores. Programming truly multithreaded code often requires complex co-ordination of threads and can easily introduce subtle and difficult-to-find bugs due to the interleaving of processing on data shared between threads (thread-safety). Consequently, such code is much more difficult to debug than single-threaded code when it breaks. There has been a perceived lack of motivation for writing consumer-level threaded applications because of the relative rarity of consumer-level demand for maximum use of computer hardware. Although threaded applications incur little additional performance penalty on single-processor machines, the extra overhead of development has been difficult to justify due to the preponderance of single-processor machines. Also, serial tasks like decoding the entropy encoding algorithms used in video codecs are impossible to parallelize because each result generated is used to help create the next result of the entropy decoding algorithm.
Given the increasing emphasis on multicore chip design, stemming from the grave thermal and power consumption problems posed by any further significant increase in processor clock speeds, the extent to which software can be multithreaded to take advantage of these new chips is likely to be the single greatest constraint on computer performance in the future. If developers are unable to design software to fully exploit the resources provided by multiple cores, then they will ultimately reach an insurmountable performance ceiling.
The telecommunications market had been one of the first that needed a new design of parallel datapath packet processing because there was a very quick adoption of these multiple-core processors for the datapath and the control plane. These MPUs are going to replace[9] the traditional Network Processors that were based on proprietary micro- or pico-code.
Parallel programming techniques can benefit from multiple cores directly. Some existing parallel programming models such as Cilk++, OpenMP, OpenHMPP, FastFlow, Skandium, and MPI can be used on multi-core platforms. Intel introduced a new abstraction for C++ parallelism called TBB. Other research efforts include the Codeplay Sieve System, Cray's Chapel, Sun's Fortress, and IBM's X10.
Multi-core processing has also affected the ability of modern computational software development. Developers programming in newer languages might find that their modern languages do not support multi-core functionality. This then requires the use of numerical libraries to access code written in languages like C and Fortran, which perform math computations faster than newer languages like C#. Intel's MKL and AMD's ACML are written in these native languages and take advantage of multi-core processing.
Managing concurrency acquires a central role in developing parallel applications. The basic steps in designing parallel applications are:
On the other hand, on the server side, multicore processors are ideal because they allow many users to connect to a site simultaneously and have independent threads of execution. This allows for Web servers and application servers that have much better throughput.
Typically, proprietary enterprise-server software is licensed "per processor". In the past a CPU was a processor and most computers had only one CPU, so there was no ambiguity.
Now there is the possibility of counting cores as processors and charging a customer for multiple licenses for a multi-core CPU. However, the trend seems to be counting dual-core chips as a single processor: Microsoft, Intel, and AMD support this view. Microsoft have said they would treat a socket as a single processor.[10]
Oracle counts an AMD X2 or Intel dual-core CPU as a single processor but has other numbers for other types, especially for processors with more than two cores. IBM and HP count a multi-chip module as multiple processors. If multi-chip modules count as one processor, CPU makers have an incentive to make large expensive multi-chip modules so their customers save on software licensing. It seems that the industry is slowly heading towards counting each die (see Integrated circuit) as a processor, no matter how many cores each die has.
Embedded computing operates in an area of processor technology distinct from that of "mainstream" PCs. The same technological drivers towards multicore apply here too. Indeed, in many cases the application is a "natural" fit for multicore technologies, if the task can easily be partitioned between the different processors.
In addition, embedded software is typically developed for a specific hardware release, making issues of software portability, legacy code or supporting independent developers less critical than is the case for PC or enterprise computing. As a result, it is easier for developers to adopt new technologies and as a result there is a greater variety of multicore processing architectures and suppliers.
As of 2010[update], multi-core network processing devices have become mainstream, with companies such as Freescale Semiconductor, Cavium Networks, Wintegra and Broadcom all manufacturing products with eight processors. For the system developer, a key challenge is how to exploit all the cores in these devices to achieve maximum networking performance at the system level, despite the performance limitations inherent in an SMP operating system. To address this issue, companies such as 6WIND provide portable packet processing software architected so that the networking data plane runs in a fast path environment outside the OS, while retaining full compatibility with standard OS APIs[11].
In digital signal processing the same trend applies: Texas Instruments has the three-core TMS320C6488 and four-core TMS320C5441, Freescale the four-core MSC8144 and six-core MSC8156 (and both have stated they are working on eight-core successors). Newer entries include the Storm-1 family from Stream Processors, Inc with 40 and 80 general purpose ALUs per chip, all programmable in C as a SIMD engine and Picochip with three-hundred processors on a single die, focused on communication applications.
|
||||||||||||||||||||||||||||