Gheorghi Guzun

Associate Professor of Computer Engineering
San Jose State University
ENG 283E | gheorghi.guzun@sjsu.edu


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Bit-Sliced Vector (BSV)

Bit-Sliced Vector (BSV)

High-performance bit-sliced vector operations for AI workloads

Source Code

Bit-Sliced Vectors (BSV) are a compact representation for numeric and categorical data that enables fast analytical queries using bitwise operations. This project provides two complementary implementations:

bsiCPP is a C++ library for building, compressing, and querying bit-sliced vectors over large datasets. It supports hybrid compressed and non-compressed bit-vector operations and is designed for scalable data management workloads.

bsiPytorch extends BSV into the deep learning stack as a PyTorch + CUDA extension. It supports GPU-accelerated BSI quantization and compression experiments, tensor-core dot-product kernels, and end-to-end LLM evaluation benchmarks (e.g., OPT models on LAMBADA) to study the trade-offs between model accuracy, compression, and inference performance.

Contributors

To be added.

Publications

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