<inline-formula> <tex-math notation="TeX">\(\mathsf{B}^{p}\) </tex-math></inline-formula>-<inline-formula> <tex-math notation="TeX">\(\mathsf{Tree}\) </tex-math></inline-formula>: A Predictive <inline-formula> <tex-math notation="TeX">\(\mathsf{B}^{+}\) </tex-math></inline-formula>-<inline-formula> <tex-math notation="TeX">\(\mathsf{Tree}\) </tex-math></inline-formula> for Reducing Writes on Phase Change Memory

Abstract

Phase change memory (PCM) has been considered an attractive alternative to flash memory and DRAM. It has promising features, including non-volatile storage, byte addressability, fast read and write operations, and supports random accesses. However, there are challenges in designing algorithms for PCM-based memory systems, such as longer write latency and higher energy consumption compared to DRAM. In this paper, we propose a new predictive B + -tree index, called the B p -tree, which is tailored for database systems that make use of PCM. Our B p -tree reduces data movements caused by tree node splits and merges that arise from insertions and deletions. This is achieved by pre-allocating space on PCM for near future data. To ensure the space are allocated where they are needed, we propose a novel predictive model to ascertain future data distribution based on the current data. In addition, as in [4], when keys are inserted into a leaf node, they are packed but need not be in sorted order. We have implemented the B p -tree in PostgreSQL and evaluated it in an emulated environment. Our experimental results show that the B p -tree significantly reduces the number of writes, therefore making it write and energy efficient and suitable for a PCM-like hardware environment.

A New Embedded Key–Value Store for NVM Device Simulator

“…The limited writing lifetime is the shortcoming for NVM such as PCM. Therefore, there is much research on how to reduce the write times of NVM devices [24][25][26][27]. Shimin Chen proposed an unordered leaf node B+ tree to reduce the write caused by sorting [24].…”