Relieving Compression-Induced Local Wear on Non-Volatile Memory Block via Sliding Writes

Area of Science:

• Computer Engineering
• Data Storage Technologies
• Memory Systems

Background:

• Non-volatile memory (NVM) devices offer advantages like non-volatility and large capacity, making them suitable for various memory applications.
• Limited endurance of NVM devices remains a significant challenge, particularly for large-scale data centers.
• Compression algorithms are employed to reduce NVM space and improve lifetime extension methods, but their impact on NVM longevity is not fully understood.

Purpose of the Study:

• To investigate the impact of compression algorithms on NVM lifetime.
• To identify and quantify the phenomenon of intra-block wear unevenness caused by compression.
• To propose a novel method for mitigating compression-induced wear in NVM devices.

Main Methods:

• Analysis of bit flips occurring during the execution of typical compression algorithms.
• Introduction of a new metric, 'local bit flips', to characterize intra-block wear.
• Development and implementation of a sliding write method named SlidW to redistribute compressed data within memory blocks.
• Experimental evaluation of SlidW's effectiveness in balancing wear and extending NVM lifetime.

Main Results:

• Compression algorithms can lead to increased bit flips in compressed data areas, causing uneven wear within memory blocks.
• The proposed 'local bit flips' metric effectively describes this intra-block wear phenomenon.
• The SlidW method successfully distributes compressed data across the entire memory block, mitigating uneven wear.
• Experimental results demonstrate that SlidW significantly enhances NVM lifetime.

Conclusions:

• Compression algorithms, while beneficial for space saving, can negatively impact NVM endurance due to uneven wear.
• The SlidW sliding write method offers an effective solution to counteract compression-induced intra-block wear.
• Implementing SlidW can lead to improved NVM device longevity, crucial for data center applications.