29 citations · 83 across the 13 of their papers we have counts for
6 papers · 1 filter
FusionStitching: Boosting Execution Efficiency of Memory Intensive Computations for DL Workloads
Guoping Long, Jun Yang, Wei Lin
Performance optimization is the art of continuous seeking a harmonious mapping between the application domain and hardware. Recent years have witnessed a surge of deep learning (DL…
Characterizing Deep Learning Training Workloads on Alibaba-PAI
Mengdi Wang, Chen Meng, Guoping Long +4
Modern deep learning models have been exploited in various domains, including computer vision (CV), natural language processing (NLP), search and recommendation. In practical AI cl…
RPM-Oriented Query Rewriting Framework for E-commerce Keyword-Based Sponsored Search
Xiuying Chen, Daorui Xiao, Shen Gao +5
Sponsored search optimizes revenue and relevance, which is estimated by Revenue Per Mille (RPM). Existing sponsored search models are all based on traditional statistical models, w…
DL2: A Deep Learning-driven Scheduler for Deep Learning Clusters
Yanghua Peng, Yixin Bao, Yangrui Chen +3
More and more companies have deployed machine learning (ML) clusters, where deep learning (DL) models are trained for providing various AI-driven services. Efficient resource sched…
Tag2Vec: Learning Tag Representations in Tag Networks
Junshan Wang, Zhicong Lu, Guojie Song +3
Network embedding is a method to learn low-dimensional representation vectors for nodes in complex networks. In real networks, nodes may have multiple tags but existing methods ign…
AliGraph: A Comprehensive Graph Neural Network Platform
Rong Zhu, Kun Zhao, Hongxia Yang +5
An increasing number of machine learning tasks require dealing with large graph datasets, which capture rich and complex relationship among potentially billions of elements. Graph…