Overview
This research paper, to be presented at SC'25 Workshop in October 2025, represents a first step toward characterizing vector database performance on high-performance computing (HPC) platforms, specifically focusing on Qdrant.
Research Motivation
As AI workloads increasingly run on HPC infrastructure, understanding vector database behavior in these environments becomes critical for:
- Scientific computing applications
- Large-scale AI model training and inference
- Data-intensive research workflows
- Multi-node distributed computing scenarios
Key Contributions
Performance Characterization
- Throughput analysis across node counts
- Latency measurements under various loads
- Scalability patterns in HPC environments
- Resource utilization (CPU, memory, network)
- I/O characteristics
HPC-Specific Insights
- Impact of high-bandwidth interconnects (InfiniBand)
- Effects of parallel file systems
- Scaling behavior with compute node count
- Comparison with cloud-based deployments
Experimental Setup
Hardware
- Modern HPC cluster configuration
- Multi-node distributed deployment
- High-performance networking
- Parallel storage systems
Workloads
- Scientific dataset vectors
- Various dimensionalities (128 to 2048)
- Different dataset sizes (millions to billions of vectors)
- Mixed read/write patterns
Findings
- Vector databases show promise on HPC platforms
- Network topology significantly impacts distributed performance
- Storage backend choice affects write performance
- Opportunities for HPC-specific optimizations identified
Implications
For HPC Centers
- Guidance on deploying vector databases
- Infrastructure recommendations
- Resource allocation strategies
For Vector Database Developers
- HPC-specific optimization opportunities
- Integration points with HPC tools
- Performance tuning recommendations
Future Research Directions
- GPU acceleration on HPC platforms
- Integration with HPC schedulers
- Multi-tenancy in HPC environments
- Optimization for scientific workflows
Conference
Presented at SC'25 (International Conference for High Performance Computing, Networking, Storage, and Analysis) Workshop, October 2025.
