Accelerating Inference of Convolutional Neural Networks Using In-memory Computing


Abstract: "In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One prominent application of IMC is that of performing matrix-vector multiplication in (1) time complexity by mapping the synaptic weights of a neural-network layer to the devices of an ... » read more

Startup Funding: December 2020


AI hardware startups were hot in our December startup-funding focus, with two companies landing rounds exceeding $100M and plenty of others seeing investment. Two Chinese EDA companies received funding in a bid to boost the country's semiconductor ecosystem. One company providing control systems for fabs achieved $8M in Series A, and both autonomous driving and electric vehicles pulled in lots ... » read more

5 Predictions For AI Innovation In 2021


By Arun Venkatachar and Stelios Diamantidis Artificial intelligence (AI) has emerged as one of the most important watchwords in all of technology. The once-utopian vision of developing machines that can think and behave like humans is becoming more of a reality as engineering innovations enable the performance required to process and interpret previously unimaginable amounts of data efficien... » read more

The Emergence Of Hardware As A Key Enabler For The Age Of Artificial Intelligence


Over the past few decades, software has been the engine of innovation for countless applications. From PCs to mobile phones, well-defined hardware platforms and instruction set architectures (ISA) have enabled many important advancements across vertical markets. The emergence of abundant-data computing is changing the software-hardware balance in a dramatic way. Diverse AI applications in fa... » read more

Power/Performance Bits: July 21


AI hardware Researchers at Purdue University, University of California San Diego, Argonne National Laboratory, University of Louisville, Brookhaven National Laboratory, and University of Iowa developed hardware that can learn skills, offloading some of the energy needed by AI software. "Software is taking on most of the challenges in AI. If you could incorporate intelligence into the circui... » read more

3 Types Of AI Hardware


As AI chips become more pervasive, three primary approaches are moving to the forefront. Bradley Geden, director of product marketing at Synopsys, looks at how to take advantage of repeatability, what the different flavors look like, the difference between flat and hierarchical design, and what impact black-box arrays have on programmability. » read more

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