Design and implementation of an efficient and parallel bad block checker for parallelism of storage devices

Cloud computing is being widely adopted in the industry due to providing more computation power and improve resource utilization. In cloud computing systems, many users execute various types of applications that produce a large amount of data. To handle a large amount of data, cloud computing systems provide various, high-performance, and large-scale clustered storage devices. With the large capacity, improving the performance of storage maintenance is an important issue since the large capacity can increase the suspend time during the maintenance significantly. As a storage maintenance technique, checking a bad block in which the data cannot be accessed anymore prevents I/O failure of the application. However, an existing bad block checker (e.g., badblocks in Linux) takes a long time, even when storage devices provide parallelism (e.g., multiple disks, multi-channel SSD, etc). It is because the existing bad block checker performs I/O and check operations in a serialized manner. To reduce the checking time, we propose an efficient and parallel bad block checker for exploiting the parallelism of storage devices. In our scheme, we enable parallel I/O and check operations for the bad block instead of the serialized operations. To do this, we first divide a series of check operations into parallel tasks (i.e., independent tasks). Second, we create a thread pool in which multiple workers fetch their tasks concurrently. Finally, we enable each checker to perform its own check and I/O operations in parallel. We implement and evaluate our checker on a 32-core machine with a disk array and an NVMe SSD. The experimental results show that our proposed bad block checker improves the performance by up to 3.7\(\times\) and 7.8\(\times\) in the disk array and NVMe SSD, respectively, compared with the existing bad block checker.