{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T20:06:22Z","timestamp":1760731582904,"version":"3.41.0"},"reference-count":46,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T00:00:00Z","timestamp":1726012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Institute for Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government","award":["2021-0-00136"],"award-info":[{"award-number":["2021-0-00136"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Embed. Comput. Syst."],"published-print":{"date-parts":[[2024,11,30]]},"abstract":"<jats:p>\n            The data movement in large-scale computing facilities (from compute nodes to data nodes) is categorized as one of the major contributors to high cost and energy utilization. To tackle it, in-storage processing (ISP) within storage devices, such as Solid-State Drives (SSDs), has been explored actively. The introduction of computational storage drives (CSDs) enabled ISP within the same form factor as regular SSDs and made it easy to replace SSDs within traditional compute nodes. With CSDs, host systems can offload various operations such as search, filter, and count. However, commercialized CSDs have different hardware resources and performance characteristics. Thus, it requires careful consideration of hardware, performance, and workload characteristics for building a CSD-based storage system within a compute node. Therefore, storage architects are hesitant to build a storage system based on CSDs as there are no tools to determine the benefits of CSD-based compute nodes to meet the performance requirements compared to traditional nodes based on SSDs. In this work, we proposed an analytical model-based storage capacity planner called\n            <jats:sc>CsdPlan<\/jats:sc>\n            for system architects to build performance-effective CSD-based compute nodes. Our model takes into account the performance characteristics of the host system, targeted workloads, and hardware and performance characteristics of CSDs to be deployed and provides optimal configuration based on the number of CSDs for a compute node. Furthermore,\n            <jats:sc>CsdPlan<\/jats:sc>\n            estimates and reduces the total cost of ownership (TCO) for building a CSD-based compute node. To evaluate the efficacy of\n            <jats:sc>CsdPlan<\/jats:sc>\n            , we selected two commercially available CSDs and four representative big data analysis workloads.\n          <\/jats:p>","DOI":"10.1145\/3623677","type":"journal-article","created":{"date-parts":[[2023,9,14]],"date-time":"2023-09-14T14:56:02Z","timestamp":1694703362000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["An Analytical Model-based Capacity Planning Approach for Building CSD-based Storage Systems"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2143-4292","authenticated-orcid":false,"given":"Hongsu","family":"Byun","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Sogang University, Mapo-gu, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9011-6431","authenticated-orcid":false,"given":"Safdar","family":"Jamil","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sogang University, Mapo-gu, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8819-1421","authenticated-orcid":false,"given":"Jungwook","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sogang University, Mapo-gu, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0309-1820","authenticated-orcid":false,"given":"Sungyong","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sogang University, Mapo-gu, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1251-1727","authenticated-orcid":false,"given":"Myungcheol","family":"Lee","sequence":"additional","affiliation":[{"name":"Electronics and Telecommunications Research Institute, Daejeon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4655-3505","authenticated-orcid":false,"given":"Changsoo","family":"Kim","sequence":"additional","affiliation":[{"name":"Electronics and Telecommunications Research Institute, Daejeon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7597-3398","authenticated-orcid":false,"given":"Beongjun","family":"Choi","sequence":"additional","affiliation":[{"name":"Electronics and Telecommunications Research Institute, Daejeon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8786-3850","authenticated-orcid":false,"given":"Youngjae","family":"Kim","sequence":"additional","affiliation":[{"name":"Deptartment of Computer Science and Engineering, Sogang University, Mapo-gu, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,9,11]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"2022. 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