一作FAST 2026Oral· Storage & File Systems
Preparation Meets Opportunity: Enhancing Data Preprocessing for ML Training With Seneca
Omkar Desai · Ziyang Jiao · Shuyi Pei · Janki Bhimani · Bryan S. Kim
摘要
Input data preprocessing is a common bottleneck when concurrently training multimedia machine learning (ML) models in modern systems. To alleviate these bottlenecks and reduce the training time for concurrent jobs, we present Seneca, a data loading system that optimizes cache partitioning and dat...
效率与系统OpenReview