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Benchmarking, Measuring, and Optimizing

Second BenchCouncil International Symposium, Bench 2019, Denver, CO, USA, November 14–16, 2019, Revised Selected Papers

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Wanling Gao

    1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

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  2. Jianfeng Zhan

    1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

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  3. Geoffrey Fox

    1. School of Informatics, Computing, and Engineering, Indiana University, Bloomington, USA

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  4. Xiaoyi Lu

    1. Department of Computer Science and Engineering, The Ohio State University, Columbus, USA

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  5. Dan Stanzione

    1. Texas Advanced Computing Center, The University of Texas at Austin, Austin, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12093)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: Bench 2019.

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Table of contents (31 papers)

  1. Front Matter

    Pages i-xxvi
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  2. Best Paper Session

    1. Front Matter

      Pages 1-1
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    2. Performance Analysis of GPU Programming Models Using the Roofline Scaling Trajectories

      • Khaled Z. Ibrahim, Samuel Williams, Leonid Oliker
      Pages 3-19

    3. GraphBench: A Benchmark Suite for Graph Computing Systems

      • Lei Wang, Minghe Yu
      Pages 20-31

    4. Early Experience in Benchmarking Edge AI Processors with Object Detection Workloads

      • Yujie Hui, Jeffrey Lien, Xiaoyi Lu
      Pages 32-48

  3. AI Challenges on Cambricon Using AIBench

    1. Front Matter

      Pages 49-49
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    2. XDN: Towards Efficient Inference of Residual Neural Networks on Cambricon Chips

      • Guangli Li, Xueying Wang, Xiu Ma, Lei Liu, Xiaobing Feng
      Pages 51-56

    3. Performance Analysis of Cambricon MLU100

      • Jiansong Li, Zihan Jiang
      Pages 57-66

    4. Exploring the Performance Bound of Cambricon Accelerator in End-to-End Inference Scenario

      • Yifan Wang, Chundian Li, Chen Zeng
      Pages 67-74

    5. Improve Image Classification by Convolutional Network on Cambricon

      • Peng He, Ge Chen, Kai Deng, Ping Yao, Li Fu
      Pages 75-82

  4. AI Challenges on RISC-V Using AIBench

    1. Front Matter

      Pages 83-83
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    2. RVTensor: A Light-Weight Neural Network Inference Framework Based on the RISC-V Architecture

      • Pengpeng Hou, Jiageng Yu, Yuxia Miao, Yang Tai, Yanjun Wu, Chen Zhao
      Pages 85-90

    3. AIRV: Enabling Deep Learning Inference on RISC-V

      • Yangyang Kong
      Pages 91-98

  5. AI Challenges on X86 Using AIBench

    1. Front Matter

      Pages 99-99
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    2. PSL: Exploiting Parallelism, Sparsity and Locality to Accelerate Matrix Factorization on x86 Platforms

      • Weixin Deng, Pengyu Wang, Jing Wang, Chao Li, Minyi Guo
      Pages 101-109

    3. The Implementation and Optimization of Matrix Decomposition Based Collaborative Filtering Task on X86 Platform

      • Tianshu Hao, Ziping Zheng
      Pages 110-115

    4. An Efficient Implementation of the ALS-WR Algorithm on x86 CPUs

      • Maosen Chen, Tun Chen, Qianyun Chen
      Pages 116-122

    5. Accelerating Parallel ALS for Collaborative Filtering on Hadoop

      • Yi Liang, Shaokang Zeng, Yande Liang, Kaizhong Chen
      Pages 123-137

  6. AI Challenges on 3D Face Recognition Using AIBench

    1. Front Matter

      Pages 139-139
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    2. Improving RGB-D Face Recognition via Transfer Learning from a Pretrained 2D Network

      • Xingwang Xiong, Xu Wen, Cheng Huang
      Pages 141-148
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  1. Benchmarking, Measuring, and Optimizing

Keywords

About this book

This book constitutes the refereed proceedings of the Second International Symposium on Benchmarking, Measuring, and Optimization, Bench 2019, held in Denver, CO, USA, in November 2019.

The 20 full papers and 11 short papers presented were carefully reviewed and selected from 79 submissions.

The papers are organized in topical sections named: Best Paper Session; AI Challenges on Cambircon using AIBenc; AI Challenges on RISC-V using AIBench; AI Challenges on X86 using AIBench; AI Challenges on 3D Face Recognition using AIBench; Benchmark; AI and Edge; Big Data; Datacenter; Performance Analysis; Scientific Computing.

Editors and Affiliations

  • Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Wanling Gao, Jianfeng Zhan

  • School of Informatics, Computing, and Engineering, Indiana University, Bloomington, USA

    Geoffrey Fox

  • Department of Computer Science and Engineering, The Ohio State University, Columbus, USA

    Xiaoyi Lu

  • Texas Advanced Computing Center, The University of Texas at Austin, Austin, USA

    Dan Stanzione

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