1 citations · 2 across the 6 of their papers we have counts for
6 papers
Application-Driven Architecture Exploration for Cross-Layer Heterogeneous Systems
Yuchen Fan, Minghong Sun, Jikui Ma +19
AI and HPC infrastructure increasingly serves workload portfolios that combine dense tensor computation, sparse kernels, large memory footprints, and communication-intensive collec…
An RDMA-First Object Storage System with SmartNIC Offload
Yu Zhu, Aditya Dhakal, Pedro Bruel +4
AI training and inference impose sustained, fine-grain I/O that stresses host-mediated, TCP-based storage paths. Motivated by kernel-bypass networking and user-space storage stacks…
RoCE BALBOA: Service-enhanced Data Center RDMA for SmartNICs
Maximilian Jakob Heer, Benjamin Ramhorst, Yu Zhu +4
Data-intensive applications in data centers, especially machine learning (ML), have made the network a bottleneck, which in turn has motivated the development of more efficient net…
Accelerating Recommender Model ETL with a Streaming FPGA-GPU Dataflow
Yu Zhu, Wenqi Jiang, Piyumi Jasin Pathiranage +2
The real-time performance of recommender models depends on the continuous integration of massive volumes of new user interaction data into training pipelines. While GPUs have scale…
Efficient Tabular Data Preprocessing of ML Pipelines
Yu Zhu, Wenqi Jiang, Gustavo Alonso
Data preprocessing pipelines, which includes data decoding, cleaning, and transforming, are a crucial component of Machine Learning (ML) training. Thy are computationally intensive…
ACCL+: an FPGA-Based Collective Engine for Distributed Applications
Zhenhao He, Dario Korolija, Yu Zhu +5
FPGAs are increasingly prevalent in cloud deployments, serving as Smart NICs or network-attached accelerators. Despite their potential, developing distributed FPGA-accelerated appl…