Central Library

Normal view MARC view ISBD view

Performance Evaluation and Benchmarking for the Era of Cloud(s) [electronic resource] : 11th TPC Technology Conference, TPCTC 2019, Los Angeles, CA, USA, August 26, 2019, Revised Selected Papers / edited by Raghunath Nambiar, Meikel Poess.

Contributor(s): Nambiar, Raghunath [editor.] | Poess, Meikel [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Programming and Software Engineering: 12257Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: XIV, 165 p. 77 illus., 37 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030550240.Subject(s): Electronic digital computers -- Evaluation | Computer networks  | Database management | Application software | Artificial intelligence | Computer systems | System Performance and Evaluation | Computer Communication Networks | Database Management | Computer and Information Systems Applications | Artificial Intelligence | Computer System ImplementationAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 004.24 Online resources: Click here to access online
Contents:
Benchmarking Elastic Cloud Big Data Services under SLA Constraints -- Efficient Multiway Hash Join on Reconfigurable Hardware -- Challenges in Distributed MLPerf -- ADABench - Towards an Industry Standard Benchmark for Advanced Analytics -- TPCx-BB (Big Bench) in a Single-Node Environment -- CBench-Dynamo: A Consistency Benchmark for NoSQL Database Systems -- Benchmarking Databases On-The-Go -- End-to-End Benchmarking of Deep Learning Platforms -- Role of the TPC in the Cloud Age -- Benchmarking Database Cloud Services -- Use Machine Learning Methods to Predict Performance of Storage Devices. .
In: Springer Nature eBookSummary: This book constitutes the refereed post-conference proceedings of the 11th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2019, held in conjunction with the 45th International Conference on Very Large Databases (VLDB 2019) in August 2019. The 11 papers presented were carefully reviewed and focus on topics such as blockchain; big data and analytics; complex event processing; database Optimizations; data Integration; disaster tolerance and recovery; artificial Intelligence; emerging storage technologies (NVMe, 3D XPoint Memory etc.); hybrid workloads; energy and space efficiency; in-memory databases; internet of things; virtualization; enhancements to TPC workloads; lessons learned in practice using TPC workloads; collection and interpretation of performance data in public cloud environments. .
    average rating: 0.0 (0 votes)
No physical items for this record

Benchmarking Elastic Cloud Big Data Services under SLA Constraints -- Efficient Multiway Hash Join on Reconfigurable Hardware -- Challenges in Distributed MLPerf -- ADABench - Towards an Industry Standard Benchmark for Advanced Analytics -- TPCx-BB (Big Bench) in a Single-Node Environment -- CBench-Dynamo: A Consistency Benchmark for NoSQL Database Systems -- Benchmarking Databases On-The-Go -- End-to-End Benchmarking of Deep Learning Platforms -- Role of the TPC in the Cloud Age -- Benchmarking Database Cloud Services -- Use Machine Learning Methods to Predict Performance of Storage Devices. .

This book constitutes the refereed post-conference proceedings of the 11th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2019, held in conjunction with the 45th International Conference on Very Large Databases (VLDB 2019) in August 2019. The 11 papers presented were carefully reviewed and focus on topics such as blockchain; big data and analytics; complex event processing; database Optimizations; data Integration; disaster tolerance and recovery; artificial Intelligence; emerging storage technologies (NVMe, 3D XPoint Memory etc.); hybrid workloads; energy and space efficiency; in-memory databases; internet of things; virtualization; enhancements to TPC workloads; lessons learned in practice using TPC workloads; collection and interpretation of performance data in public cloud environments. .

There are no comments for this item.

Log in to your account to post a comment.