Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems
Summary: GPU-accelerated cross-comparison of pathology image regions on CPU-GPU hybrids, using a customized GPU kernel and a pipelined framework with task migration for spatial operations. Real-world datasets show ~18× speedup over parallelized spatial DB approaches, enabling cost-efficient high-throughput analysis. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kaibo Wang
- 2. Yin Huai
- 3. Rubao Lee
- 4. Fusheng Wang
- 5. Xiaodong Zhang
- 6. Joel H. Saltz
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,261 | Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce | 2013 | VLDB | 0.00012989236 |
| 1,273 | The Yin and Yang of Processing Data Warehousing Queries on GPU Devices | 2013 | VLDB | 0.00012912938 |
| 2,067 | HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics | 2016 | VLDB | 9.6392739e-05 |
| 2,330 | Concurrent Analytical Query Processing with GPUs | 2014 | VLDB | 9.0192228e-05 |
| 2,751 | Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores | 2015 | VLDB | 8.1760621e-05 |
| 5,125 | The Art of Balance: A RateupDBTM Experience of Building a CPU/GPU Hybrid Database Product | 2021 | VLDB | 5.679423e-05 |
| 11,013 | X-TED: Massive Parallelization of Tree Edit Distance | 2024 | VLDB | 4.1945683e-05 |
| 11,126 | High-Performance Spatial Data Analytics: Systematic R&D for Scale-Out and Scale-Up Solutions from the Past to Now | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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