7 citations · 10 across the 7 of their papers we have counts for
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cs.AR2025
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…
cs.AR2024★ 1 cited
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…
cs.AR2024★ 7 cited
Fast Graph Vector Search via Hardware Acceleration and Delayed-Synchronization Traversal
Wenqi Jiang, Hang Hu, Torsten Hoefler +1
Vector search systems are indispensable in large language model (LLM) serving, search engines, and recommender systems, where minimizing online search latency is essential. Among v…