Using a random forest to predict quantized reuse distance in an SSD write buffer
H Cha, IK Kim, T Kim - Computing, 2024 - Springer
Efficient management of the write buffer in solid-state drives (SSDs) can be achieved by
predicting future I/O request patterns using machine learning techniques. However, the …
predicting future I/O request patterns using machine learning techniques. However, the …
A machine-learning-based data classifier to reduce the write amplification in SSDs
Solid-state drives (SSDs) that consist of flash memory have the advantages of non-volatility,
fast speed, shock resistance, low-power consumption, and small size. Two critical …
fast speed, shock resistance, low-power consumption, and small size. Two critical …
Intelligent prediction of flash lifetime via online domain adaptation
R Ma, F Wu, C Xie - 2021 IEEE 39th International Conference …, 2021 - ieeexplore.ieee.org
To resolve the low generalization ability of the flash lifetime model caused by a small
training sample, we propose a multiple source ensemble online domain adaptation scheme …
training sample, we propose a multiple source ensemble online domain adaptation scheme …
Machine Learning for 3D NAND Flash and Solid State Drives Reliability/Performance Optimization
Abstract Solid State Drives (SSDs) are the storage backbone of many applications ranging
from consumer electronics up to exa-scaled data centers (Zuolo in Proc IEEE 105: 1589 …
from consumer electronics up to exa-scaled data centers (Zuolo in Proc IEEE 105: 1589 …