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Browsing by Author "Kim, Wook-Hee"

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    Fireworks: A Fast, Efficient, and Safe Serverless Framework using VM-level post-JIT Snapshot
    Shin, Wonseok; Kim, Wook-Hee; Min, Changwoo (ACM, 2022-03-28)
    Serverless computing is a new paradigm that is rapidly gaining popularity in Cloud computing. One unique property in serverless computing is that the unit of deployment and execution is a serverless function, which is much smaller than a typical server program. Serverless computing introduces a new pay-as-you-go billing model and provides a high economic benefit from highly elastic resource provisioning. However, serverless computing also brings new challenges such as (1) long start-up times compared to relatively short function execution times, (2) security risks from a highly consolidated environment, and (3) memory efficiency problems from unpredictable function invocations. These problems not only degrade performance but also lower the economic benefits of Cloud providers. To address these challenges without any compromises, we propose a novel VM-level post-JIT snapshot approach and develop a new serverless framework, Fireworks. Our key idea is to synergistically leverage a virtual machine (VM)- level snapshot with a language runtime-level just-in-time (JIT) compilation in tandem. Fireworks leverages JITted serverless function code to reduce both start-up time and execution time of functions and improves memory efficiency by sharing the JITted code. Also, Fireworks can provide a high level of isolation by using a VM as a sandbox to execute a serverless function. Our evaluation results show that Fireworks outperforms state-of-art serverless platforms by 20.6× and provides higher memory efficiency of up to 7.3×.
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    PRISM: Optimizing Key-Value Store for Modern Heterogeneous Storage Devices
    Song, Yongju; Kim, Wook-Hee; Monga, Sumit Kumar; Min, Changwoo; Eom, Young Ik (ACM, 2023-01-27)
    As data generation has been on an upward trend, storing vast volumes of data cost-effectively as well as efficiently accessing them is paramount. At the same time, today’s storage landscape continues to diversify, from high-bandwidth storage devices such as NVMe SSDs to low-latency non-volatile memory (e.g., Intel Optane DCPMM). These heterogeneous storage devices have the potential to deliver high performance in terms of bandwidth and latency with cost efficiency, while achieving the performance and cost targets together still remains a challenging problem. We provide our solution, PRISM, a novel key-value store that utilizes modern heterogeneous storage devices. PRISM uses heterogeneous storage devices synergistically to harness the advantages of each storage device while suppressing their downsides. We devise new techniques to balance the latency-bandwidth tradeoff when reading from SSD. For ensuring multicore scalability and crash consistency of data across heterogeneous storage media, PRISM proposes cross-storage concurrency control and cross-storage crash consistency protocols. Our evaluation shows that PRISM outperforms state-of-the-art key-value stores by up to 13.1× with significantly lower tail latency.