# An Architecture for Memory Centric Active Storage (MCAS)

arXiv: https://arxiv.org/abs/2103.00007 · HTML: https://mlsanity.com/paper/2103.00007/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2021.

## Built on by (most cited first, 3 of 3)

- [Fast Feature Selection with Fairness Constraints](https://mlsanity.com/paper/2202.13718/) (2022)
- [Non-Volatile Memory Accelerated Posterior Estimation](https://mlsanity.com/paper/2202.10522/) (2022)
- [Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis](https://mlsanity.com/paper/2202.11518/) (2022)

## Abstract (arXiv)

The advent of CPU-attached persistent memory technology, such as Intel's Optane Persistent Memory Modules (PMM), has brought with it new opportunities for storage. In 2018, IBM Research Almaden began investigating and developing a new enterprise-grade storage solution directly aimed at this emerging technology. MCAS (Memory Centric Active Storage) defines an evolved network-attached key-value store that offers both near-data compute and the ability to layer enterprise-grade data management services on shared persistent memory. As a converged memory-storage tier, MCAS moves towards eliminating the traditional separation of compute and storage, and thereby unifying the data space. This paper provides an in-depth review of the MCAS architecture and implementation, as well as general performance results.