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Thursday, September 24 • 11:35am - 12:25pm
Storage Performance Analysis for Big Data Processing

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End to end big data benchmarking has become an extreme attention of ICT industry, the related techniques are being investigated by numerous hardware and software vendors. Storages, as one of the core components of a data center system, need specially designed approaches to measure, evaluate and analyze their performance. This talk introduces our methods to create the storage performance model based on workload characterization, algorithm level behavior tracing and capture, and software platform management. The functionality and capability of our methodology for quantitative analysis of big data storage have been validated through benchmarks and measurements performed on real data center system.

Learning Objectives

Storage Performance Measurement and Evaluation
Scalable and Distributed Storage Systems
Best practices architecture for Big Data
Performance analysis

avatar for Da Qi Ren

Da Qi Ren

Staff Research Engineer, Huawei
Dr. Ren, a staff research engineer of Futurewei Technologies in Santa Clara, CA, USA, has more than 12 years of experience in high performance computing and architectures. His research focus has been in the areas of formal methods, parallel and distributed processing, big data analytics... Read More →
avatar for Zane Wei

Zane Wei

Director, Huawei
Mr. Zane Wei has been the head of the Shannon Lab, the head of the IT Research Lab of Central Research Institute, and the head of strategy and planning of corporate hardware technology in Huawei Technologies. He received his master degree from HKUST (Hongkong University of Science... Read More →

Thursday September 24, 2015 11:35am - 12:25pm PDT
Lawrence Room

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