8 citations · 13 across the 5 of their papers we have counts for
5 papers
AttMEMO : Accelerating Transformers with Memoization on Big Memory Systems
Yuan Feng, Hyeran Jeon, Filip Blagojevic +3
Transformer models gain popularity because of their superior inference accuracy and inference throughput. However, the transformer is computation-intensive, causing a long inferenc…
Hydra: Hybrid Server Power Model
Nigel Bernard, Hoa Nguyen, Aman Chandan +4
With the growing complexity of big data workloads that require abundant data and computation, data centers consume a tremendous amount of power daily. In an effort to minimize data…
Revealing Secrets From Pre-trained Models
Mujahid Al Rafi, Yuan Feng, Hyeran Jeon
With the growing burden of training deep learning models with large data sets, transfer-learning has been widely adopted in many emerging deep learning algorithms. Transformer mode…
Characterization of Semantic Segmentation Models on Mobile Platforms for Self-Navigation in Disaster-Struck Zones
Ryan Zelek, Hyeran Jeon
The role of unmanned vehicles for searching and localizing the victims in disaster impacted areas such as earthquake-struck zones is getting more important. Self-navigation on an e…
Tango: A Deep Neural Network Benchmark Suite for Various Accelerators
Aajna Karki, Chethan Palangotu Keshava, Spoorthi Mysore Shivakumar +3
Deep neural networks (DNNs) have been proving the effectiveness in various computing fields. To provide more efficient computing platforms for DNN applications, it is essential to…