# Amphishea: A Novel Persistent Buffer Management Strategy to Improve SMR Disk Performance
## 6 Experiment
### Performance Evaluation
Unlike Skylight, both Fluid and Fluid_loop follow the FIFO principle during the cleanup, so they cannot select victims based on data layout characteristics, which is the main reason for their higher write amplification. Figure 12: Normalized average response latency. Figure 13: Write hit rates. **RMW and RMW-free counts. ** Figure 15 shows the effect of Amphisheaena in reducing RMW operations. As confirmed in the literature [21; 22], the number of RMW operations is a key factor affecting the overall performance of SMR disks. Therefore, reducing the number of RMWs is an effective way to improve disk performance. As shown in Figure 15, the bottom of each bar indicates the number of RMW operations involved in write-backs, and the top bar indicates the number of write-backs that are not involved in RMW operations (also known as RMW-free), so the sum of the two indicates the total number of write-backs. From the results, it is clear that Amphisheaen not only has the lowest number of RMW operations but also the total number of write-backs is lower than the other competitors. Unlike other competitors that lack data layout awareness, our victim selection policy takes into account the impact of victims on the native zone's spatial locality, which is the key to eliminating unnecessary RMW operations. As a result, Amphisheaen can reduce RMW operations by an average of 37%. **Padding data volume. ** Since the sequential write constraint of SMR disks causes blocks to be appended sequentially only at the location of the write pointer, synthetic data are used to fill the gap between valid blocks. In fact, the amount of synthetic data introduced during data migration affects the spatial locality of the native zone. Avoiding too much synthetic data as much as possible can effectively reduce RMW operations during cleanup. In addition, the excessive synthetic data written back inevitably occupy the internal bandwidth of the disk, thus increasing the response latency of user requests. From Figure 16, we can clearly see that Amphisheaen introduces the least amount of synthetic data among all the traces. For example, Amphisheaena can reduce synthetic data by up to 552 GB and 191 GB under src2_2 and prxy_0, two workloads with strong spatial locality and strong temporal locality, respectively. Figure 14: Normalized write amplification. Figure 15: RMW and RMW-Free counts. **Average victim zone size. ** A larger victim zone size means that it has a stronger spatial locality that can reduce the write amplification. The average victim zone size is the total number of buffer blocks evicted each time divided by the number of zones involved in the cleanup. The garbage collector selects a larger victim zone to make better use of the sequential write capability of the disk and to reduce the seek time during garbage collection. In addition, if the number of blocks to be evicted is certain, the larger the zone size, the fewer RMW operations are introduced and the cleanup time is shorter. Figure 17 shows the average victim zone size. Except for the ts_0 and src2_0 workloads, the size of the evicted victim zone in Amphishebaena is the largest. There are two reasons for this: some of the hot blocks are reserved in the HFB, which makes it difficult to form a larger victim zone in the LFB; on the other hand, the latency-sensitive garbage collection policy aborts the collection process at the next checkpoint if it detects the write request against the current victim zone, resulting in only some of the blocks in the victim zone being write-back.