GIA: Multi-core Processor Market to Reach $116.3B by 2020

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The global market for multi-core processors is projected to reach $116.3 billion by 2020, driven by rising demand for faster computing speeds, and spiraling sales of portable computing devices, according to a new report by market analyst firm Global Industry Analysts Inc. (GIA).

Multi-core architectures are gaining prominence in the semiconductor and electronics industries, with new smartphones featuring dual, triple, quad, and octa core processors. With consumers and businesses demanding enhanced computing performance from their devices, semiconductor companies are migrating to multi-core processors as an alternative to single core processing systems.

A key factor driving smartphone processing speeds is the evolution of smartphones into personal organizers, music players, game consoles, video players, and web browsers. The resulting need for superior image and data processing is driving adoption of multi-core processors.

The transition of chip designs to multi-core processing architectures has facilitated considerable improvements in product performance, while simultaneously cutting down cost of production. Multi-core technology is particularly useful when dealing with demanding tasks and applications such as 3D gaming, video editing and encoding. Multi-core technology’s ability to bring about incremental improvements in power and speed of processing for a range of applications and services, while also offering advanced management and control capabilities constitutes a key factor fuelling its adoption in various end-use verticals.

Key end-use sectors poised to generate strong demand for multi-core processors include consumer electronics, transportation, automotive, industrial, medical, and communications. In the coming years, industrial automation, healthcare, automotive and energy sectors are expected to generate significant demand for multi-core processors. However, while multi-core processors significantly improve the performance of a device, the extent of such improvements depends on the type of software algorithm used and its implementation.



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