Adaptable platform eyes challenges of future computing

March 19, 2018 // By Christoph Hammerschmidt
In a move to do away with the limitations of conventional processing architectures, FPGA expert Xilinx devised a computing architecture that is said to be more adaptive to different types of data structures and real-time requirements. Accordingly, the platform is called “Adaptive Compute Acceleration Platform” (ACAP).

Designed to meet the computing demands of future automation landscapes in the areas of robotics, Internet of Things, automotive and many other fields of computing, including Artificial Intelligence, ACAP is a multi-core, heterogeneous platform that can be changed at the hardware level (even dynamically, during operation) to adapt to the needs of a wide range of applications and workloads. The company claims that ACAP delivers levels of performance and performance per-watt that is unmatched by CPUs or GPUs (see Interview with Xlinix CEO Victor Peng on the limitations of current computing architectures).

Future applications in the abovementioned areas have a number of challenges in store – to name a few of them are processing high amounts of data under tough real-time conditions, even stricter safety requirements along with the need to avoid delay times, video transcoding, data compression, AI inference, machine vision and network acceleration – and some of them combined at the same time. The ACAP platform is designed to meet these challenges, Xilinx promises. Now the company has announced the first product for the ACAP family. Baptized “Everest”, it will be manufactured in the latest semiconductor technology with structures as small as 7 nanometers. Tape-out is expected to take place later this year.


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