首页|Findings from Technical University Dresden (TU Dresden) Yields New Data on Networks (High-flexibility Designs of Quantized Runtime Reconfigurable Multi-precision Multipliers)
Findings from Technical University Dresden (TU Dresden) Yields New Data on Networks (High-flexibility Designs of Quantized Runtime Reconfigurable Multi-precision Multipliers)
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By a News Reporter-Staff News Editor at Network Daily News - A new studyon Networks is now available. According to news reporting out of Dresden, Germany, by NewsRx editors,research stated, “Recent research widely explored the quantization schemes on hardware. However, forrecent accelerators only supporting 8 bits quantization, such as Google TPU, the lower-precision inputs,such as 1/2-bit quantized neural network models in FINN, need to extend the data width to meet thehardware interface requirements.”Financial support for this research came from Center for Scalable Data Analytics and Artificial Intelligence(ScaDS.AI).
DresdenGermanyEuropeNetworksNeural NetworksTechnical University Dresden (TU Dresden)
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