Performance Evaluation and Benchmarking [electronic resource] : 14th TPC Technology Conference, TPCTC 2022, Sydney, NSW, Australia, September 5, 2022, Revised Selected Papers / edited by Raghunath Nambiar, Meikel Poess.
Contributor(s): Nambiar, Raghunath [editor.] | Poess, Meikel [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Computer Science: 13860Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: IX, 149 p. 57 illus., 40 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031295768.Subject(s): Computers | Computer networks | Computers, Special purpose | Application software | Artificial intelligence | Software engineering | Computing Milieux | Computer Communication Networks | Special Purpose and Application-Based Systems | Computer and Information Systems Applications | Artificial Intelligence | Software EngineeringAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 004 Online resources: Click here to access onlinePick and Mix Isolation Levels: Mixed Serialization Graph Testing -- BODS: A Benchmark on Data Sortedness -- Disaggregated Database Management Systems (Panel) -- TPCx-AI on NVIDIA Jetson -- More the Merrier: Comparative evaluation of TPCx-AI and MLPerf Benchmarks for AI -- Preliminary Scaling Characterization with TPCx-AI -- 4mbench: Performance Benchmark of Manufacturing Business Database -- Benchmarking considerations for Trustworthy and Responsible AI (Panel) -- TPCx-AI: First Adopter's Experience Report -- New Initiatives in the TPC.
This book constitutes the refereed post-conference proceedings the 14th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2022, which was held in Sydney, NSW, Australia, on September 5, 2022. The 5 revised full papers presented were carefully selected from 12 submissions. The conference focuses on Pick and Mix Isolation Levels; Benchmarking considerations for Trustworthy and Responsible AI (Panel); Preliminary Scaling Characterization with TPCx-AI and New Initiatives. .
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