Wednesday, March 28, 2012

Analog Devices’ highest performance Blackfin processors feature accelerated vision analytics and low power consumption

NORWOOD, USA: Analog Devices Inc. has introduced a series of 1-GHz, dual-core, Blackfin processors. The ADSP-BF608 and ADSP-BF609 are optimized for embedded vision applications, featuring a high performance video analytics accelerator, called the Pipelined Vision Processor (PVP).

The PVP is comprised of a set of configurable processing blocks designed to accelerate up to five concurrent image algorithms, enabling a very high level of analytics performance. These processors are ideal for many applications such as automotive advanced driver assistance systems (ADAS), industrial machine vision, and security/surveillance systems.

The ADSP-BF606 and ADSP-BF607 are available without the PVP and are designed to provide flexibility for a wide variety of general purpose digital signal processing applications such as wireless communications, industrial process control, and electric power grid monitoring/protection.

These four new processors all have two 500MHz cores, the largest on-chip memory available within the Blackfin family, and have been optimized for low power operation. Additional features which are optimized for power efficiency include a new high-bandwidth switched fabric data movement infrastructure, a rich peripheral set and safety oriented features. Low power consumption has a number of benefits including high temperature operation, smaller foot prints and lower system cost. Typical power consumption for the BF609 is 400mWatts.

“Embedded vision technology enables electronic products to be much more intelligent and responsive,” said Jeff Bier, Founder of the Embedded Vision Alliance. “Vision algorithms are computationally demanding and very diverse. Hence, high-performance, cost-effective programmable processors are essential for these applications. I applaud Analog Devices’ leadership in fielding a powerful architecture targeting embedded vision applications.”

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