94 citations · 130 across the 12 of their papers we have counts for
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cs.DC2018
NTX: An Energy-efficient Streaming Accelerator for Floating-point Generalized Reduction Workloads in 22nm FD-SOI
Fabian Schuiki, Michael Schaffner, Luca Benini
Specialized coprocessors for Multiply-Accumulate (MAC) intensive workloads such as Deep Learning are becoming widespread in SoC platforms, from GPUs to mobile SoCs. In this paper w…
cs.DC2018★ 1 cited
A Scalable Near-Memory Architecture for Training Deep Neural Networks on Large In-Memory Datasets
Fabian Schuiki, Michael Schaffner, Frank K. Gürkaynak +1
Most investigations into near-memory hardware accelerators for deep neural networks have primarily focused on inference, while the potential of accelerating training has received r…