The skd-tree partitions space into multiple slices per node along one dimension, compresses splitters, and applies a constant number of SIMD instructions per node to reduce levels and computations for multi-dimensional queries.
Chi, Jeffrey Dean, and Neoklis Polyzotis
3 Pith papers cite this work. Polarity classification is still indexing.
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A prediction-augmented data structure for incremental SCC maintenance achieves near-optimal update times with accurate edge-order predictions and degrades smoothly with prediction error.
An LLM-driven agentic system evolves microarchitectural policies for cache replacement, data prefetching, and branch prediction, producing designs that match or exceed prior state-of-the-art in IPC on standard benchmarks.
citing papers explorer
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In-memory Multidimensional Indexing Using the skd-tree
The skd-tree partitions space into multiple slices per node along one dimension, compresses splitters, and applies a constant number of SIMD instructions per node to reduce levels and computations for multi-dimensional queries.
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Incremental Strongly Connected Components with Predictions
A prediction-augmented data structure for incremental SCC maintenance achieves near-optimal update times with accurate edge-order predictions and degrades smoothly with prediction error.
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Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization
An LLM-driven agentic system evolves microarchitectural policies for cache replacement, data prefetching, and branch prediction, producing designs that match or exceed prior state-of-the-art in IPC on standard benchmarks.