CV-rules equivalently characterize serializability via explicit orders satisfying C-rule and V-rule, used to verify five protocols including SSN and Aria with Lean mechanization of most results.
Lazylsh: Approximate nearest neighbor search for multiple distance functions with a single index,
4 Pith papers cite this work, alongside 67 external citations. Polarity classification is still indexing.
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A modular systemisation plus practitioner objectives framework organises DP graph release methods and yields an open social-network benchmark of SotA edge- and node-DP algorithms.
Co-design of 14.5x compacted index, asynchronous scheduler, and multiplication-free kernel for PIM-based graph ANNS delivers up to 20x CPU and 17.1x GPU throughput on billion-scale benchmarks.
PystachIO is a PyTorch-based distributed OLAP engine that delivers up to 3x end-to-end speedups for storage-resident queries by combining fast RDMA networks, NVMe storage, and I/O-computation overlap optimizations.
citing papers explorer
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CV-Rules: Serializability Verification of Concurrency Control Protocols via Explicit Transaction Ordering
CV-rules equivalently characterize serializability via explicit orders satisfying C-rule and V-rule, used to verify five protocols including SSN and Aria with Lean mechanization of most results.
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SoK: Practical Aspects of Releasing Differentially Private Graphs
A modular systemisation plus practitioner objectives framework organises DP graph release methods and yields an open social-network benchmark of SotA edge- and node-DP algorithms.
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Co-Designing Graph-based Approximate Nearest Neighbor Search at Billion Scale for Processing-in-Memory
Co-design of 14.5x compacted index, asynchronous scheduler, and multiplication-free kernel for PIM-based graph ANNS delivers up to 20x CPU and 17.1x GPU throughput on billion-scale benchmarks.
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PystachIO: Efficient Distributed GPU Query Processing with PyTorch over Fast Networks & Fast Storage
PystachIO is a PyTorch-based distributed OLAP engine that delivers up to 3x end-to-end speedups for storage-resident queries by combining fast RDMA networks, NVMe storage, and I/O-computation overlap optimizations.