# In-memory hyperdimensional computing

arXiv: https://arxiv.org/abs/1906.01548 · HTML: https://mlsanity.com/paper/1906.01548/

## Key facts

- Cited by 48 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jun 2019.

## Built on by (most cited first, 30 of 48)

- [A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations](https://mlsanity.com/paper/2111.06077/) (2021)
- [Constrained Few-shot Class-incremental Learning](https://mlsanity.com/paper/2203.16588/) (2022)
- [A Neuro-vector-symbolic Architecture for Solving Raven's Progressive Matrices](https://mlsanity.com/paper/2203.04571/) (2022)
- [Vector Symbolic Architectures as a Computing Framework for Emerging Hardware](https://mlsanity.com/paper/2106.05268/) (2021)
- [Applications and Techniques for Fast Machine Learning in Science](https://mlsanity.com/paper/2110.13041/) (2021)
- [LeHDC: Learning-Based Hyperdimensional Computing Classifier](https://mlsanity.com/paper/2203.09680/) (2022)
- [Non-Exemplar Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement](https://mlsanity.com/paper/2303.10891/) (2023)
- [A Brain-Inspired Low-Dimensional Computing Classifier for Inference on Tiny Devices](https://mlsanity.com/paper/2203.04894/) (2022)
- [Hyperseed: Unsupervised Learning with Vector Symbolic Architectures](https://mlsanity.com/paper/2110.08343/) (2021)
- [MIMHD: Accurate and Efficient Hyperdimensional Inference Using Multi-Bit In-Memory Computing](https://mlsanity.com/paper/2106.12029/) (2021)
- [Hyperdimensional Computing vs. Neural Networks: Comparing Architecture and Learning Process](https://mlsanity.com/paper/2207.12932/) (2022)
- [Learning from Hypervectors: A Survey on Hypervector Encoding](https://mlsanity.com/paper/2308.00685/) (2023)
- [A 5 μ W Standard Cell Memory-based Configurable Hyperdimensional Computing Accelerator for Always-on Smart Sensing](https://mlsanity.com/paper/2102.02758/) (2021)
- [HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration](https://mlsanity.com/paper/2206.04746/) (2022)
- [Generalized Holographic Reduced Representations](https://mlsanity.com/paper/2405.09689/) (2024)
- [Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework](https://mlsanity.com/paper/2110.00214/) (2021)
- [Hyperdimensional computing encoding for feature selection on the use case of epileptic seizure detection](https://mlsanity.com/paper/2205.07654/) (2022)
- [Vector-Symbolic Architecture for Event-Based Optical Flow](https://mlsanity.com/paper/2405.08300/) (2024)
- [Automated Architecture Search for Brain-inspired Hyperdimensional Computing](https://mlsanity.com/paper/2202.05827/) (2022)
- [Streaming Encoding Algorithms for Scalable Hyperdimensional Computing](https://mlsanity.com/paper/2209.09868/) (2022)
- [Resource-Efficient Federated Hyperdimensional Computing](https://mlsanity.com/paper/2306.01339/) (2023)
- [HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning](https://mlsanity.com/paper/2403.05763/) (2024)
- [MicroHD: An Accuracy-Driven Optimization of Hyperdimensional Computing Algorithms for TinyML systems](https://mlsanity.com/paper/2404.00039/) (2024)
- [Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware](https://mlsanity.com/paper/2405.01305/) (2024)
- [Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks](https://mlsanity.com/paper/2203.06223/) (2022)
- [Associative Memory Based Experience Replay for Deep Reinforcement Learning](https://mlsanity.com/paper/2207.07791/) (2022)
- [Hyperdimensional computing: a fast, robust and interpretable paradigm for biological data](https://mlsanity.com/paper/2402.17572/) (2024)
- [Brain-inspired Cognition in Next Generation Racetrack Memories](https://mlsanity.com/paper/2111.02246/) (2021)
- [HYPERLOCK: In-Memory Hyperdimensional Encryption in Memristor Crossbar Array](https://mlsanity.com/paper/2201.11362/) (2022)
- [EnHDC: Ensemble Learning for Brain-Inspired Hyperdimensional Computing](https://mlsanity.com/paper/2203.13542/) (2022)

## Abstract (arXiv)

Hyperdimensional computing (HDC) is an emerging computational framework that takes inspiration from attributes of neuronal circuits such as hyperdimensionality, fully distributed holographic representation, and (pseudo)randomness. When employed for machine learning tasks such as learning and classification, HDC involves manipulation and comparison of large patterns within memory. Moreover, a key attribute of HDC is its robustness to the imperfections associated with the computational substrates on which it is implemented. It is therefore particularly amenable to emerging non-von Neumann paradigms such as in-memory computing, where the physical attributes of nanoscale memristive devices are exploited to perform computation in place. Here, we present a complete in-memory HDC system that achieves a near optimum trade-off between design complexity and classification accuracy based on three prototypical HDC related learning tasks, namely, language classification, news classification, and hand gesture recognition from electromyography signals. Comparable accuracies to software implementations are demonstrated, experimentally, using 760,000 phase-change memory devices performing analog in-memory computing.