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EEJournal and The Linley Newsletter cover the newly announced, AI-optimized Intel® Stratix® 10 NX FPGA

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Last month, Intel announced the company’s first AI-optimized FPGA, the Intel® Stratix® 10 NX FPGA. (See “Intel has just announced its first AI-optimized FPGA – the Intel® Stratix® 10 NX FPGA – to address the rapid increase in AI model complexity.”) Earlier this week, The Linley Newsletter and EEJournal provided their perspectives on this announcement in articles written by Linley Gwennap and Kevin Morris, respectively.

Gwennap’s article in the Linley Newsletter, titled “Stratix 10 NX Adds AI Blocks,” said:

“Intel is determined to cover all aspects of the AI-accelerator market. Its latest offering for neural networks is the Stratix 10 NX, a new family in its 14nm FPGA line that revamps the DSP block to improve AI performance.”

The Linley Group also published a much longer version of this article with additional details and analysis in its Microprocessor Report newsletter (paid subscription required).

Morris’ long article on the EEJournal.com Web site, titled “Intel Announces Stratix 10 NX,” said:

“In the case of the new Stratix 10 NX [FPGA], the company is going after the AI inference market primarily via new AI-optimized arithmetic blocks called AI Tensor Blocks. These blocks would have previously been called “DSP” blocks, but the new versions contain dense arrays of lower-precision multipliers typically used for AI model arithmetic.”

Morris' article also discusses a larger aspect of Intel’s work on AI, specifically the Intel® oneAPI development project, which is aimed at creating a standards-based, unified programming model for CPUs, GPUs, FPGAs, and other hardware accelerators. Morris writes:

“…Intel seems to be hanging their hat on their ambitious “oneAPI” which is a standards-based, unified programming model that aims to facilitate integration of heterogeneous Xeon-based platforms with various accelerators such as FPGAs. Intel’s approach makes sense, given the breadth of their offering…”


For more information, please see both of these recent articles.


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