24 citations · 56 across the 4 of their papers we have counts for
4 papers
PROV-IO+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems
Runzhou Han, Mai Zheng, Suren Byna +8
Data provenance, or data lineage, describes the life cycle of data. In scientific workflows on HPC systems, scientists often seek diverse provenance (e.g., origins of data products…
SaiT: Sparse Vision Transformers through Adaptive Token Pruning
Ling Li, David Thorsley, Joseph Hassoun
While vision transformers have achieved impressive results, effectively and efficiently accelerating these models can further boost performances. In this work, we propose a dense/s…
Learned Token Pruning for Transformers
Sehoon Kim, Sheng Shen, David Thorsley +4
Deploying transformer models in practice is challenging due to their inference cost, which scales quadratically with input sequence length. To address this, we present a novel Lear…
Post-Training Piecewise Linear Quantization for Deep Neural Networks
Jun Fang, Ali Shafiee, Hamzah Abdel-Aziz +3
Quantization plays an important role in the energy-efficient deployment of deep neural networks on resource-limited devices. Post-training quantization is highly desirable since it…