Convolutional Neural Networks (CNNs) is one of the core algorithms for implementing artificial intelligence (AI), which has the characteristics of high parallelism and large amount of computations. With the rapid development of AI applications, general purpose processors such as CPU/GPU can't meet ...
This paper presents a configurable convolutional neural network accelerator (CNNA) for a system-on-chip (SoC). The goal was to accelerate inference in different deep learning networks on an embedded SoC platform. The presented CNNA has a scalable architecture that uses high-level synthesis (HLS) ...
The spiking neural network (SNN) has advantage in the edge AI applications for its spatiotemporal sparsity. The high energy efficiency is an important concern in the study of SNN accelerator designs. In this paper, a lightweight event-driven convolutional SNN accelerator that utilizes the sparsity...
parallelism of 100, two orders higher than implementations using only the spatial and wavelength degrees of freedom. We demonstrate this by performing a synchronous convolution of 100 clinical electrocardiogram signals from patients with cardiovascular diseases, and constructing a convolutional neural network ...
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many state-of-the-art (SOA) visual processing tasks. ... A Alessandro,M Hesham,C Enrico,...
Shafiee, A., et al.: ISAAC: a convolutional neural network accelerator with in-situ analog arithmetic in crossbars. In: 43rd ACM/IEEE Annual International Symposium on Computer Architecture, ISCA 2016, Seoul, South Korea, 18–22 June 2016, pp. 14–26 (2016). https://doi.org/10.1109/ISC...
Measurement Convolutional neural network Survey Cross-research 1. Introduction The convolutional neural network (CNN) is one of the fundamental technologies in the field of artificial intelligence (AI), and it is a promising tool for solving the problem of pattern recognition. The technology has been...
This paper presents a configurable Convolutional Neural Network Accelerator\n(CNNA) for a System on Chip design (SoC). The goal was to accelerate inference\nof different deep learning networks on an embedded SoC platform. The presented\n... K Bjerge,JH Schougaard,DE Larsen 被引量: 0发表: 20...
Designing efficient accelerator of depthwise separable convolutional neural network on FPGA In this paper, we propose a Field Programmable Gate Array (FPGA)-based depthwise separable CNN accelerator with all the layers working concurrently in a ... WAB Ding,ZAB Huang,ZA Huang,... - 《Journal of...
Hardware accelerators for convolutional neural network (CNN) inference have been extensively studied in recent years. The reported designs tend to utilize a similar underlying architecture based on multiplier-accumulator (MAC) arrays, which has the practical consequence of limiting the FPGA-based accelerat...