Stateful serverless analytics can be enabled using a remote memory system for inter-task communication, and for storing and exchanging intermediate data. However, existing …
H Tian, Y Zheng, W Wang - Proceedings of the ACM Symposium on …, 2019 - dl.acm.org
Cluster schedulers routinely face data-parallel jobs with complex task dependencies expressed as DAGs (directed acyclic graphs). Understanding DAG structures and runtime …
Emerging ML training deployments are trending towards larger models, and hybrid-parallel training that is not just dominated by compute-intensive all-reduce for gradient aggregation …
Modern Hybrid Transactional/Analytical Processing (HTAP) systems use an integrated data processing engine that performs analytics on fresh data, which are ingested from a …
A Jonathan, A Chandra, J Weissman - Proceedings of the 21st …, 2020 - dl.acm.org
Adaptability is critical for stream processing systems to ensure stable, low-latency, and high- throughput processing of long-running queries. Such adaptability is particularly challenging …
The popularity of big data and AI has led to many optimizations at different layers of distributed computation stacks. Despite–or perhaps, because of–its role as the narrow waist …
Cloud providers have recently introduced new offerings whereby spare computing resources are accessible at discounts compared to on-demand computing. Exploiting such …
Deep Neural Networks (DNNs) are witnessing increased adoption in multiple domains owing to their high accuracy in solving real-world problems. However, this high accuracy …
Cloud providers auction off unallocated resources at a low cost to avoid keeping hardware idle. One such mechanism is Harvest VMs (HVMs). These VMs grow and shrink as the …