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Beyond Traditional Search: SIMD-Optimized Correction for Learned Index
Yeojin Oh, Nakyeong Kim, Jongmoo Choi, Seehwan Yoo
http://doi.org/10.5626/JOK.2025.52.5.363
To address the limitations of traditional indexing techniques, this study examines the search performance of machine learning-based Learned Indexes, focusing on the read-only RMI and the modifiable ALEX We propose a SIMD-based optimization technique to minimize the overhead incurred during the correction phase, which accounts for over 80% of the total search time. Learned Indexes operate in two phases: prediction and correction. In our experiments with RMI, we found that when the error range is large, the SIMD Branchless Binary Search capable of quickly narrowing down the search range outperforms other methods. In contrast. when the error range is small, the model prediction-based SIMD Linear Search demonstrates superior performance. For ALEX, which maintains a relatively constant error range, the straightforward SIMD Linear Search proved to be the most efficient compared to more complex search techniques. These results underscore the importance of choosing the right search algorithm based on the dataset’s error range, index size, and density to achieve optimal performance.
Overcoming a Zone Reclaiming Overhead with Partial-Zone Reclaiming
Inho Song, Wonjin Lee, Jaedong Lee, Seehwan Yoo, Jongmoo Choi
http://doi.org/10.5626/JOK.2024.51.2.115
Solid State Drive (SSD) suffers unpredictable IO latency and space amplification due to the traditional block interface. Zoned Namespace, which is a more flash friendly interface, replaced the block interface bringing reliable IO latency and increasing both the capacity and lifespan of SSDs. The benefit of the zone interface is not free. A Zoned Namespace (ZNS) SSD delegates the garbage collection and data placement responsibility to the host, which requires host-level garbage collection called "zone reclaiming". At the same time, ZNS SSD exposes a larger zone to the host to exploit the device parallelism. The increased number of blocks to a zone gives high parallelism; however, the overhead of the zone reclaiming process becomes high with the increased size of the zone. Eventually, the host neither expects predictable latency nor optimal performance due to the background process. This paper tackles the overhead of the zone reclaiming process by introducing "Partial Zone Reclaiming" method. Partial zone reclaiming delays the ongoing reclaiming process and handles the host request that is on the fly. In our experiment, partial zone reclaiming not only improved the host request latency by up to 8% on average, but also reduced zone reclaiming time by up to 41%.
Vulnerability Analysis on Kernel Code and Memory Protection in Nested Kernel
http://doi.org/10.5626/JOK.2018.45.9.873
Nested Kernel is a secure kernel architecture, presented at the 2015 ACM ASPLOS conference, which aims at assuring the lifetime integrity of the kernel. With the conventional off-the-shelf HW-based protection facility, the Nested Kernel significantly improves the security of the system by introducing a new OS kernel architecture. However, our analysis reveals that the current Nested Kernel has some flaws in its implementation for handling direct mapping and the kernel code mapping region. In addition, its integrity can be broken because of the reported security vulnerability. Consequently, the Nested Kernel needs further study for it to be used safely as a security kernel.
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