WebMar 12, 2024 · Bit-Pragmatic Deep Neural Network Computing. (NVIDIA, University of Toronto) CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-Circulant Weight Matrices. (Syracuse University, … WebJul 8, 2024 · Abstract: It is critical to continously improve the hardware efficiency of deep neural network accelerators for its application on resource constrained platform. This …
Neural-Networks-on-Silicon/README.md at master
WebOct 14, 2024 · Abstract. Deep Neural Networks expose a high degree of parallelism, making them amenable to highly data parallel architectures. However, data-parallel … WebFeb 16, 2024 · Abstract: We quantify a source of ineffectual computations when processing the multiplications of the convolutional layers in Deep Neural Networks (DNNs) and propose Pragrmatic (PRA), an architecture that exploits it improving performance and energy efficiency. physician hours
Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing
WebOct 1, 2024 · Bit-pragmatic deep neural network computing. In Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture. ACM, 382--394. Google Scholar Digital Library; Jorge Albericio, Patrick Judd, Tayler Hetherington, Tor Aamodt, Natalie Enright Jerger, and Andreas Moshovos. 2016. Cnvlutin: Ineffectual-neuron-free … WebDeep Neural Networks expose a high degree of parallelism, making them amenable to highly data parallel architectures. However, data-parallel architectures often accept … WebJun 22, 2016 · This work observes that a large fraction of the computations performed by Deep Neural Networks (DNNs) are intrinsically ineffectual as they involve a multiplication where one of the inputs is zero. This observation motivates Cnvolutin (CNV), a value-based approach to hardware acceleration that eliminates most of these ineffectual operations, … physician house calls chickasha ok