NasZip delivers up to 8.4x speedup over CPU baselines and 1.69x over prior NDP accelerators for ANNS by combining near-data processing with statistics-based PCA early exiting, dynamic-float encoding, and data-aware neighbor mapping.
Locality-sensitive hashing scheme based on p-stable distributions
4 Pith papers cite this work. Polarity classification is still indexing.
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A pipeline using product quantization and systematic parameter evaluation creates data-driven soil taxonomies with higher specificity than human-derived classifications.
Dask parallelization of product quantization and inverted indexing allows large-scale approximate nearest neighbor search while preserving accuracy and reducing computation to medium-scale levels.
This survey discusses key components and challenges for Personal LLM Agents and reviews solutions for their capability, efficiency, and security.
citing papers explorer
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NasZip: Software and Hardware Co-Design to Accelerate Approximate Nearest Neighbor Search with DIMM-Based Near-Data Processing
NasZip delivers up to 8.4x speedup over CPU baselines and 1.69x over prior NDP accelerators for ANNS by combining near-data processing with statistics-based PCA early exiting, dynamic-float encoding, and data-aware neighbor mapping.
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Product Quantization for Surface Soil Similarity
A pipeline using product quantization and systematic parameter evaluation creates data-driven soil taxonomies with higher specificity than human-derived classifications.
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Large-Scale Data Parallelization of Product Quantization and Inverted Indexing Using Dask
Dask parallelization of product quantization and inverted indexing allows large-scale approximate nearest neighbor search while preserving accuracy and reducing computation to medium-scale levels.
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Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
This survey discusses key components and challenges for Personal LLM Agents and reviews solutions for their capability, efficiency, and security.