Results 1 -
7 of
7
A mean field model for a class of garbage collection algorithms in flash-based solid state drives
- In Proceedings of the 8th USENIX conference on File and storage technologies, FAST’10
, 2010
"... Garbage collection (GC) algorithms play a key role in reducing the write amplification in flash-based solid state drives, where the write amplification affects the lifespan and speed of the drive. This paper introduces a mean field model to assess the write amplification and the distribution of the ..."
Abstract
-
Cited by 4 (2 self)
- Add to MetaCart
(Show Context)
Garbage collection (GC) algorithms play a key role in reducing the write amplification in flash-based solid state drives, where the write amplification affects the lifespan and speed of the drive. This paper introduces a mean field model to assess the write amplification and the distribution of the number of valid pages per block for a class C of GC algorithms. Apart from the Random GC algorithm, class C includes two novel GC algorithms: the d-Choices GC algorithm, that selects d blocks uniformly at random and erases the block containing the least number of valid pages among the d selected blocks, and the Random++ GC algorithm, that repeatedly selects another block uniformly at random until it finds a block with a lower than average number of valid blocks. Using simulation experiments we show that the proposed mean field model is highly accurate in predicting the write amplification (for drives with N = 50000 blocks). We further show that the d-Choices GC algorithm has a write amplification close to that of the Greedy GC algorithm even for small d values, e.g., d = 10, and offers a more attractive trade-off between its simplicity and its performance than the Windowed GC algorithm introduced and analyzed in earlier studies. The Random++ algorithm is shown to be less effective as it is even inferior to the FIFO algorithm when the number of pages b per block is large (e.g., for b ≥ 64).
Performance of garbage collection algorithms for flash-based solid state drives with hot/cold
"... data ..."
(Show Context)
J.C.S.: Stochastic analysis on RAID reliability for solid-state drives
- In: Proceedings of the 32nd IEEE International Symposium on Reliable Distributed Systems (2013
"... ar ..."
(Show Context)
A Particle Process Underlying SSD Storage Structures
"... ABSTRACT We introduce a particle process that models the evolution of page configurations in solid-state-drive (SSD) storage devices. These devices use integrated circuitry as memory to store data. Typically, pages (units of storage) are organized into blocks of a given size. Three operations are p ..."
Abstract
- Add to MetaCart
(Show Context)
ABSTRACT We introduce a particle process that models the evolution of page configurations in solid-state-drive (SSD) storage devices. These devices use integrated circuitry as memory to store data. Typically, pages (units of storage) are organized into blocks of a given size. Three operations are permitted: write, read, and clean. Rewrites are not allowed, i.e., a page has to be "cleaned" before the write operation can be repeated. While the read and write operations are permitted on individual pages, the clean operation can be executed on whole blocks only. Analysis of our particle process captures a key tradeoff in the operation of SSD's.
Analysis of the d-choices garbage collection algorithm with memory in flash-based SSDs
"... Garbage collection algorithms have a profound impact on the performance and life span of flash-based solid state drives. Recently, the d-choices garbage collection algorithm was shown to provide an excellent tradeoff between simplic-ity and performance [21]. In this paper, we introduce the d-choices ..."
Abstract
- Add to MetaCart
(Show Context)
Garbage collection algorithms have a profound impact on the performance and life span of flash-based solid state drives. Recently, the d-choices garbage collection algorithm was shown to provide an excellent tradeoff between simplic-ity and performance [21]. In this paper, we introduce the d-choices garbage collection algorithm with memory and an-alyze its write performance using both synthetic and real life workloads. The synthetic workloads consist of uniform ran-dom writes and the write amplification is analyzed by means of a mean field model. For the trace-based workloads we rely on simulation experiments and consider systems using either a single or a double write frontier. Apart from studying the impact of adding memory to the d-choices garbage collec-tion algorithm, the paper also presents the first trace-based evidence that the double write frontier is very effective in reducing the write amplification in the presence of hot and cold data. 1.
collection algorithms in solid-state drive systems
"... Stochastic modeling and optimization of garbage ..."
(Show Context)
Queueing Systems manuscript No. (will be inserted by the editor) A Mean Field Model for a Class of Garbage Collection Algorithms in Flash-based Solid State Drives
"... Abstract Garbage collection (GC) algorithms play a key role in reducing the write amplification in flash-based solid state drives, where the write amplification affects the lifespan and speed of the drive. This paper introduces a mean field model to assess the write amplification and the distributio ..."
Abstract
- Add to MetaCart
(Show Context)
Abstract Garbage collection (GC) algorithms play a key role in reducing the write amplification in flash-based solid state drives, where the write amplification affects the lifespan and speed of the drive. This paper introduces a mean field model to assess the write amplification and the distribution of the number of valid pages per block for a class C of GC algorithms. Apart from the Random GC algorithm, class C includes two novel GC algorithms: the d-Choices GC algorithm, that selects d blocks uniformly at random and erases the block containing the least number of valid pages among the d selected blocks, and the Random++ GC algorithm, that repeatedly selects another block uniformly at random until it finds a block with a lower than average number of valid blocks. Using simulation experiments we show that the proposed mean field model is highly accurate in predicting the write amplification (for drives with N = 50, 000 blocks). We further show that the d-Choices GC algorithm has a write amplification close to that of the Greedy GC algorithm even for small d values, e.g., d = 10, and offers a more attractive trade-off between its simplicity and its performance than the Windowed GC algorithm introduced and analyzed in earlier studies. The Random++ algorithm is shown to be less effective as it is even inferior to the FIFO algorithm when the number of pages b per block is large (e.g., for b ≥ 64). 1