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Cost-effective, Energy-efficient, and Scalable Storage Computing for Large-scale AI Applications

Cited 22 time in Web of Science Cited 26 time in Scopus

Do, Jae Young; Ferreira, Victor C.; Bobarshad, Hossein; Torabzadehkashi, Mahdi; Rezaei, Siavash; Heydarigorji, Ali; Souza, Diego; Goldstein, Brunno F.; Santiago, Leandro; Kim, Min Soo; Lima, Priscila M., V; Franca, Felipe M. G.; Alves, Vladimir

Issue Date
Association for Computing Machinary, Inc.
ACM Transactions on Storage, Vol.16 No.4, p. 21
The growing volume of data produced continuously in the Cloud and at the Edge poses significant challenges for large-scale AI applications to extract and learn useful information from the data in a timely and efficient way. The goal of this article is to explore the use of computational storage to address such challenges by distributed near-data processing. We describe Newport, a high-performance and energy-efficient computational storage developed for realizing the full potential of in-storage processing. To the best of our knowledge, Newport is the first commodity SSD that can be configured to run a server-like operating system, greatly minimizing the effort for creating and maintaining applications running inside the storage. We analyze the benefits of using Newport by running complex AI applications such as image similarity search and object tracking on a large visual dataset. The results demonstrate that data-intensive AI workloads can be efficiently parallelized and offloaded, even to a small set of Newport drives with significant performance gains and energy savings. In addition, we introduce a comprehensive taxonomy of existing computational storage solutions together with a realistic cost analysis for high-volume production, giving a good big picture of the economic feasibility of the computational storage technology.
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  • College of Engineering
  • Department of Electrical and Computer Engineering
Research Area AI 애플리케이션을 위한 알고리즘-시스템 공동 설계, AI-powered Big Data Management, Generative AI, Large Language Model, ML, 고성능 대규모 AI 데이터 분석 및 처리, 모달 AI


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