3 papers
cs.AR2025
AutoRAC: Automated Processing-in-Memory Accelerator Design for Recommender Systems
Feng Cheng, Tunhou Zhang, Junyao Zhang +6
The performance bottleneck of deep-learning-based recommender systems resides in their backbone Deep Neural Networks. By integrating Processing-In-Memory~(PIM) architectures, resea…
cs.CV2025
CSCO: Connectivity Search of Convolutional Operators
Tunhou Zhang, Shiyu Li, Hsin-Pai Cheng +3
Exploring dense connectivity of convolutional operators establishes critical "synapses" to communicate feature vectors from different levels and enriches the set of transformations…
cs.IR2025
DistDNAS: Search Efficient Feature Interactions within 2 Hours
Tunhou Zhang, Wei Wen, Igor Fedorov +8
Search efficiency and serving efficiency are two major axes in building feature interactions and expediting the model development process in recommender systems. On large-scale ben…