1.2k citations · 3.2k across the 31 of their papers we have counts for
31 papers
VELTAIR: Towards High-Performance Multi-tenant Deep Learning Services via Adaptive Compilation and Scheduling
Zihan Liu, Jingwen Leng, Zhihui Zhang +3
Deep learning (DL) models have achieved great success in many application domains. As such, many industrial companies such as Google and Facebook have acknowledged the importance o…
The Serverless Computing Survey: A Technical Primer for Design Architecture
Zijun Li, Linsong Guo, Jiagan Cheng +3
The development of cloud infrastructures inspires the emergence of cloud-native computing. As the most promising architecture for deploying microservices, serverless computing has…
Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators
Yangjie Zhou, Mengtian Yang, Cong Guo +5
Many of today's deep neural network accelerators, e.g., Google's TPU and NVIDIA's tensor core, are built around accelerating the general matrix multiplication (i.e., GEMM). However…
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
Shulai Zhang, Zirui Li, Quan Chen +3
Federated learning (FL) is a distributed machine learning paradigm that allows clients to collaboratively train a model over their own local data. FL promises the privacy of client…
Pagurus: Eliminating Cold Startup in Serverless Computing with Inter-Action Container Sharing
Zijun Li, Quan Chen, Minyi Guo
Serverless computing provides fine-grain resource sharing between Cloud tenants through containers. Each function invocation (action) runs in an individual container. When there is…
ZIPPER: Exploiting Tile- and Operator-level Parallelism for General and Scalable Graph Neural Network Acceleration
Zhihui Zhang, Jingwen Leng, Shuwen Lu +5
Graph neural networks (GNNs) start to gain momentum after showing significant performance improvement in a variety of domains including molecular science, recommendation, and trans…