SoC FPGA for IoT Edge Computing

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Edge architecture from Fujisoft presented at ISDF 2016

One of the reasons for the explosive growth of IoT is that embedded devices with networking capabilities and sensor interfaces are cheap enough to deploy them at a plethora of locations.

However, network bandwidth is limited. Not only that, but also, the latency of the network can be of seconds or minutes. By the time the sensor data is acquired by the centralized computers, its value for decision making could be lost. In other words, for the IoT solution to be effective, it should not only deliver meaningful data securely (and filter it as much as possible to avoid network congestion), it should also analyze it and act upon it at the origination point of the data. At the very edge of the network.

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FPGAs and Deep Machine Learning

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The concept of machine learning is not new. Attempts at systems emulating intelligent behavior, like expert systems, go as far back as the early 1980’s. And the very notion of modern Artificial Intelligence has a long history. The name itself was coined at a Dartmouth College conference (1956), but the idea of an “electronic brain” was born together with the development of modern computers. AI as an idea accompanies us from the dawn of human history.

Three latest development are pushing forward “Machine Learning”:

  • Powerful distributed processors
  • Cheap and high volume storage
  • High bandwidth interconnection to bring the data to the processors

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Stratix 10MX – High memory bandwidth on SiP package

 

The Stratix® 10 MX DRAM system-in-package (SiP) family combines a 1 GHz high-performance monolithic FPGA fabric, state-of-the-art Intel Embedded Multi-die Interconnect Bridge (EMIB) technology, and High Bandwidth Memory 2 (HBM2), all in a single package (SiP).

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Image source: Altera

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Intel announces Xeon processor with FPGA accelerator

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Image source: Altera

Last year (December 2015), Intel completed the acquisition of Altera. As a result of this acquisition, the integration of processor and FPGA on a single chip is finally becoming a reality.

Intel envisions many applications for this combination of processor and FPGA. The FPGA will fulfill accelerator tasks, either by static configuration or dynamic reconfiguration.

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