Advancements in Artificial Intelligence Circuits and Systems (AICAS)

T Miller, I Durlik, E Kostecka, P Mitan-Zalewska… - Electronics, 2023 - mdpi.com
In the rapidly evolving landscape of electronics, Artificial Intelligence Circuits and Systems
(AICAS) stand out as a groundbreaking frontier. This review provides an exhaustive …

OneSpace: Detecting cross-language clones by learning a common embedding space

M El Arnaoty, F Servant - Journal of Systems and Software, 2024 - Elsevier
Identifying clone code fragments across different languages can enhance the productivity of
software developers in several ways. However, the clone detection task is often studied in …

Sla-driven ml inference framework for clouds with heterogeneous accelerators

J Cho, D Zad Tootaghaj, L Cao… - … of Machine Learning …, 2022 - proceedings.mlsys.org
The current design of Serverless computing frameworks assumes that all the requests and
underlying compute hardware are homogeneous. This homogeneity assumption causes two …

“Last mile” optimization of edge computing ecosystem with deep learning models and specialized tensor processing architectures

Y Gordienko, Y Kochura, V Taran, N Gordienko… - Advances in …, 2021 - Elsevier
In the context of edge computing (EC) paradigm the new type of specific System on a Chip
(SoC) devices with tensor processing architectures (TPAs) appeared for running deep …

Deep learning inferencing with high-performance hardware accelerators

L Kljucaric, AD George - ACM Transactions on Intelligent Systems and …, 2023 - dl.acm.org
As computer architectures continue to integrate application-specific hardware, it is critical to
understand the relative performance of devices for maximum app acceleration. The goal of …

Optimization of deep learning methods for visualization of tumor heterogeneity and brain tumor grading through digital pathology

AH Truong, V Sharmanska… - Neuro-Oncology …, 2020 - academic.oup.com
Background Variations in prognosis and treatment options for gliomas are dependent on
tumor grading. When tissue is available for analysis, grade is established based on …

Linear-time self attention with codeword histogram for efficient recommendation

Y Wu, D Lian, NZ Gong, L Yin, M Yin, J Zhou… - Proceedings of the Web …, 2021 - dl.acm.org
Self-attention has become increasingly popular in a variety of sequence modeling tasks from
natural language processing to recommendation, due to its effectiveness. However, self …

Generalized neural closure models with interpretability

A Gupta, PFJ Lermusiaux - Scientific Reports, 2023 - nature.com
Improving the predictive capability and computational cost of dynamical models is often at
the heart of augmenting computational physics with machine learning (ML). However, most …

Snow depth extraction from time‐lapse imagery using a keypoint deep learning model

CM Breen, WR Currier, C Vuyovich… - Water Resources …, 2024 - Wiley Online Library
Snow pole time‐lapse photography, in which a snow pole of a known height is installed in
front of a camera and photographed repeatedly over the course of a snow season, allows a …

Scaling analysis of specialized tensor processing architectures for deep learning models

Y Gordienko, Y Kochura, V Taran, N Gordienko… - … learning: Concepts and …, 2020 - Springer
Specialized tensor processing architectures (TPA) targeted for neural network processing
has attracted a lot of attention in recent years. The computing complexity of the …