Dynamic Garbage Collection Workload Sizing for NAND Memory
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Solution Overview
Problem
Garbage collection in NAND-based memory devices consumes resources and can impact user experience and device lifetime due to write amplification, particularly when dealing with conflicting workload types such as sustained and burst workloads, where traditional methods fail to dynamically adjust to changing conditions effectively.
Innovation Solution
Implementing a dynamically adjusted garbage collection workload that minimizes the number of garbage collection executions by sizing workload portions based on observed idle periods, prioritizing SLC cache garbage collection, and verifying that portions are beyond a threshold before execution, thereby maximizing idle period usage and reducing write amplification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If garbage collection is performed frequently to maintain free space in NAND memory, then the availability of free space is improved, but write amplification increases and device lifetime decreases
Solution Approach 1:
The garbage collection workload is dynamically adjusted based on observed idle periods. The system monitors idle times and derives a metric to divide the garbage collection workload into portions, executing larger portions during longer idle periods and smaller portions during shorter idle periods. This dynamic adjustment optimizes free space maintenance while minimizing write amplification and preserving device lifetime.
2Ease of operation
If garbage collection is executed during idle periods to reduce impact on user experience, then user experience is improved, but the number of executions increases if workload portions are not optimized, leading to increased write amplification
Solution Approach 1:
The garbage collection workload is divided into portions based on the idle period metric. During each idle period, only a calculated portion of the total garbage collection workload is executed, rather than completing the entire workload. This partial action approach ensures that garbage collection is performed during idle periods to maintain user experience, while the portioning prevents excessive executions and minimizes write amplification.
3Speed
If SLC cache garbage collection is prioritized to maintain cache performance, then write performance is improved, but resource consumption increases during sustained workloads
Solution Approach 1:
The garbage collection workload division prioritizes SLC cache garbage collection based on the derived metric from idle periods. During idle periods, a larger portion of the workload is allocated to SLC cache maintenance to preserve fast write performance. During sustained workloads with shorter idle periods, the portion executed is reduced, thereby lowering resource consumption while maintaining essential cache functionality.
Data Source
AI summary
Devices and techniques for a dynamically adjusting a garbage collection workload are described herein. For example, memory device idle times can be recorded. From these recorded idle times, a metric can be derived. A current garbage collection workload can be divided into portions based on the metric. Then, a first portion of the divided garbage collection workload can be performed at a next idle time.