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Towards Systems Education for Artificial Intelligence: A Course Practice in Intelligent Computing Architectures
With the rapid development of artificial intelligence (AI) community, education in AI is receiving more and more attentions. There have …
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Towards Systems Education for Artificial Intelligence: A Course Practice in Intelligent Computing Architectures
Hardware Security in Spin-Based Computing-In-Memory: Analysis, Exploits, and Mitigation Techniques
Computing-in-memory (CIM) is proposed to alleviate the processor-memory data transfer bottleneck in traditional von Neumann …
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Hardware Security in Spin-Based Computing-In-Memory: Analysis, Exploits, and Mitigation Techniques
TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework with Anonymized Intermediate Representations
The success of deep learning partially benefits from the availability of various large-scale datasets. These datasets are often …
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TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework with Anonymized Intermediate Representations
An STT-MRAM based reconfigurable computing-in-memory architecture for general purpose computing
Recently, many researches have proposed computing-in-memory architectures trying to solve von Neumann bottleneck issue. Most of the …
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An STT-MRAM based reconfigurable computing-in-memory architecture for general purpose computing
SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training
Training Convolutional Neural Networks (CNNs) usually requires a large number of computational resources. In this paper, SparseTrain is …
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SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training
TCIM: Triangle Counting Acceleration With Processing-In-MRAM Architecture
Triangle counting (TC) is a fundamental problem in graph analysis and has found numerous applications, which motivates many TC …
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TCIM: Triangle Counting Acceleration With Processing-In-MRAM Architecture
Fast Physics-based Electromigration Analysis for Full-chip Networks by Efficient Eigenfunction-based Solution
Electromigration (EM) becomes one of the most challenging reliability issues for current and future ICs in 10-nm technology and below. …
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Fast Physics-based Electromigration Analysis for Full-chip Networks by Efficient Eigenfunction-based Solution
Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization
The Bayesian method is capable of capturing real-world uncertainties/incompleteness and properly addressing the overfitting issue faced …
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Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization
Bulkyflip: A NAND-SPIN-Based Last-Level Cache With Bandwidth-Oriented Write Management Policy
High capacity last-level caches (LLCs) are being used to help alleviate the growing speed gap between the processor and main memory. …
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Bulkyflip: A NAND-SPIN-Based Last-Level Cache With Bandwidth-Oriented Write Management Policy
Exploiting Near-Memory Processing Architectures for Bayesian Neural Networks Acceleration
Bayesian inference is an effective approach to capture the model uncertainty as well as tackle the over-fitting problem in deep neural …
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Exploiting Near-Memory Processing Architectures for Bayesian Neural Networks Acceleration