Microsoft unveiled

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Microsoft for business Stay a step ahead with powerful apps for productivity, connection, and security. A number of companies—both large companies and a slew of startups—are building hardened DPUs. Although some of these chips have high peak performance, they must choose their operators and data types at design time, which limits their flexibility.

Project Brainwave takes a different approach, providing a design that scales across a range of data types, with the desired data type being a synthesis-time decision. The design combines both the ASIC digital signal processing blocks on the FPGAs and the synthesizable logic to provide a greater and more optimized number of functional units. First, we have defined highly customized, narrow-precision data types that increase performance without real losses in model accuracy.

Second, we can incorporate research innovations into the hardware platform quickly typically a few weeks , which is essential in this fast-moving space. As a result, we achieve performance comparable to — or greater than — many of these hard-coded DPU chips but are delivering the promised performance today. Third, Project Brainwave incorporates a software stack designed to support the wide range of popular deep learning frameworks. Send MSN Feedback. How can we improve?

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