1 citations · 1 across the 4 of their papers we have counts for
5 papers
COMPASS: Steering Distributed Vector Search with Scientific Knowledge Graphs
Song Young Oh, Amal Gueroudji, Seth Ockerman +5
Vector databases use hashing to partition data across "shards," logical units for distributed execution. This placement, however, destroys semantic locality, forcing each query int…
When More Cores Hurts: The Vector Database Scaling Paradox in HPC
Seth Ockerman, Song Young Oh, Amal Gueroudji +12
Vector databases have been designed and optimized for cloud environments; however, emerging scientific AI workloads (e.g., molecular search, meteorological trajectory detection, an…
Exploring Distributed Vector Databases Performance on HPC Platforms: A Study with Qdrant
Seth Ockerman, Amal Gueroudji, Song Young Oh +5
Vector databases have rapidly grown in popularity, enabling efficient similarity search over data such as text, images, and video. They now play a central role in modern AI workflo…
PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows
Renan Souza, Amal Gueroudji, Stephen DeWitt +5
Large Language Models (LLMs) and other foundation models are increasingly used as the core of AI agents. In agentic workflows, these agents plan tasks, interact with humans and pee…
PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training
Seth Ockerman, Amal Gueroudji, Tanwi Mallick +4
Spatiotemporal graph neural networks (ST-GNNs) are powerful tools for modeling spatial and temporal data dependencies. However, their applications have been limited primarily to sm…