Performance Analysis of a Phase-Change Memory System on Various CNN Inference Workloads-Reference-Cited by-同舟云学术

Performance Analysis of a Phase-Change Memory System on Various CNN Inference Workloads

Published:2022-10-19 Issue: Volume: Page:
ISSN:
Container-title:2022 19th International SoC Design Conference (ISOCC)
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Author:

Jang Jihoon¹,Kim Hyun¹,Lee Hyokeun²

Affiliation:

1. Research Center for Electrical and Information Technology Seoul National University of Science and Technology,Department of Electrical and Information Engineering,Seoul,Korea

2. Inter-University Semiconductor Research Center Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea

Funder

National Research Foundation of Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10031262/10031265/10031496.pdf?arnumber=10031496

Reference8 articles.

1. Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving

2. McSimA+: A manycore simulator with application-level+ simulation and detailed microarchitecture modeling

3. FP-AGL: Filter Pruning With Adaptive Gradient Learning for Accelerating Deep Convolutional Neural Networks

4. Scalable high performance main memory system using phase-change memory technology

5. Zero-Centered Fixed-Point Quantization With Iterative Retraining for Deep Convolutional Neural Network-Based Object Detectors

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