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Performance Evaluation and Benchmarking for the Era of Artificial Intelligence

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Cover of 'Performance Evaluation and Benchmarking for the Era of Artificial Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Industry Panel on Defining Industry Standards for Benchmarking Artificial Intelligence
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    Chapter 2 UniBench: A Benchmark for Multi-model Database Management Systems
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    Chapter 3 PolyBench: The First Benchmark for Polystores
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    Chapter 4 Benchmarking Distributed Data Processing Systems for Machine Learning Workloads
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    Chapter 5 Characterizing the Performance and Resilience of HCI Clusters with the TPCx-HCI Benchmark
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    Chapter 6 Requirements for an Enterprise AI Benchmark
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    Chapter 7 Towards Evaluation of Tensorflow Performance in a Distributed Compute Environment
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    Chapter 8 A Comparison of Two Cache Augmented SQL Architectures
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    Chapter 9 Benchmarking and Performance Analysis of Event Sequence Queries on Relational Database
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    Chapter 10 Data Consistency Properties of Document Store as a Service (DSaaS): Using MongoDB Atlas as an Example
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    Chapter 11 Lessons Learned from the Industry’s First TPC Benchmark DS (TPC-DS)
Attention for Chapter 10: Data Consistency Properties of Document Store as a Service (DSaaS): Using MongoDB Atlas as an Example
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