Modern servers are actively deploying Solid-State Drives (SSDs) thanks to their high throughput and low latency. However, current server architects cannot achieve the full performance potential of commodity SSDs, as SSDs are complex devices designed for specific goals (e.g., latency, throughput, endurance, cost) with their internal mechanisms undisclosed to users. In this article, we propose SSDcheck , a novel SSD performance model to extract various internal mechanisms and predict the latency of next access to commodity black-box SSDs. We identify key performance-critical features (e.g., garbage collection, write buffering) and find their parameters (i.e., size, threshold) from each SSD by using our novel diagnosis code snippets. Then, SSDcheck constructs a performance model for a target SSD and dynamically manages the model to predict the latency of the next access. In addition, SSDcheck extracts and provides other useful internal mechanisms (e.g., fetch unit in multi-queue SSDs, background tasks triggering idle-time interval) for the storage system to fully exploit SSDs. By using those useful features and the performance model, we propose multiple practical use cases. Our evaluations show that SSDcheck’s performance model is highly accurate, and proposed use cases achieve significant performance improvement in various scenarios.

中文翻译：

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黑盒 SSD 的性能建模和实际用例

现代服务器正在积极部署固态驱动器 (SSD)，这要归功于其高吞吐量和低延迟。然而，当前的服务器架构师无法实现商品 SSD 的全部性能潜力，因为 SSD 是为特定目标（例如延迟、吞吐量、耐用性、成本）而设计的复杂设备，其内部机制未向用户公开。在本文中，我们提出SSD检查，一种新颖的 SSD 性能模型，用于提取各种内部机制并预测下一次访问商品黑盒 SSD 的延迟。我们使用我们新颖的诊断代码片段识别关键性能关键特征（例如，垃圾收集、写入缓冲）并从每个 SSD 中找到它们的参数（即大小、阈值）。然后，SSDcheck 为目标 SSD 构建性能模型并动态管理模型以预测下一次访问的延迟。此外，SSDcheck 为存储系统提取并提供了其他有用的内部机制（例如，多队列 SSD 中的获取单元、触发空闲时间间隔的后台任务）以充分利用 SSD。通过使用这些有用的特性和性能模型，我们提出了多个实际用例。