14 citations · 19 across the 9 of their papers we have counts for
9 papers
Code Transpilation for Hardware Accelerators
Yuto Nishida, Sahil Bhatia, Shadaj Laddad +3
DSLs and hardware accelerators have proven to be very effective in optimizing computationally expensive workloads. In this paper, we propose a solution to the challenge of manually…
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Arash Ardakani, Altan Haan, Shangyin Tan +4
Transformer-based models, such as BERT and ViT, have achieved state-of-the-art results across different natural language processing (NLP) and computer vision (CV) tasks. However, t…
An Evaluation of Memory Optimization Methods for Training Neural Networks
Xiaoxuan Liu, Siddharth Jha, Alvin Cheung
As models continue to grow in size, the development of memory optimization methods (MOMs) has emerged as a solution to address the memory bottleneck encountered when training large…
NumS: Scalable Array Programming for the Cloud
Melih Elibol, Vinamra Benara, Samyu Yagati +4
Scientists increasingly rely on Python tools to perform scalable distributed memory array operations using rich, NumPy-like expressions. However, many of these tools rely on dynami…
VSS: A Storage System for Video Analytics [Technical Report]
Brandon Haynes, Maureen Daum, Dong He +4
We present a new video storage system (VSS) designed to decouple high-level video operations from the low-level details required to store and efficiently retrieve video data. VSS i…
Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads
Parmita Mehta, Sven Dorkenwald, Dongfang Zhao +7
Scientific discoveries are increasingly driven by analyzing large volumes of image data. Many new libraries and specialized database management systems (DBMSs) have emerged to supp…