28 citations · 76 across the 14 of their papers we have counts for
14 papers
AIBench Training: Balanced Industry-Standard AI Training Benchmarking
Fei Tang, Wanling Gao, Jianfeng Zhan +30
Earlier-stage evaluations of a new AI architecture/system need affordable benchmarks. Only using a few AI component benchmarks like MLPerfalone in the other stages may lead to misl…
AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite
Wanling Gao, Fei Tang, Jianfeng Zhan +31
Domain-specific software and hardware co-design is encouraging as it is much easier to achieve efficiency for fewer tasks. Agile domain-specific benchmarking speeds up the process…
BenchCouncil's View on Benchmarking AI and Other Emerging Workloads
Jianfeng Zhan, Lei Wang, Wanling Gao +1
This paper outlines BenchCouncil's view on the challenges, rules, and vision of benchmarking modern workloads like Big Data, AI or machine learning, and Internet Services. We concl…
Landscape of Big Medical Data: A Pragmatic Survey on Prioritized Tasks
Zhifei Zhang, Wanling Gao, Fan Zhang +13
Big medical data poses great challenges to life scientists, clinicians, computer scientists, and engineers. In this paper, a group of life scientists, clinicians, computer scientis…
Clustering Residential Electricity Load Curves via Community Detection in Network
Yunyou Huang, Jianfeng Zhan, Nana Wang +3
Performing analytic of household load curves (LCs) has significant value in predicting individual electricity consumption patterns, and hence facilitate developing demand-response…
Anomaly Analysis for Co-located Datacenter Workloads in the Alibaba Cluster
Rui Ren, Jinheng Li, Lei Wang +2
In warehouse-scale cloud datacenters, co-locating online services and offline batch jobs is an efficient approach to improving datacenter utilization. To better facilitate the unde…
Data Motif-based Proxy Benchmarks for Big Data and AI Workloads
Wanling Gao, Jianfeng Zhan, Lei Wang +8
For the architecture community, reasonable simulation time is a strong requirement in addition to performance data accuracy. However, emerging big data and AI workloads are too hug…
A veracity preserving model for synthesizing scalable electricity load profiles
Yunyou Huang, Jianfeng Zhan, Chunjie Luo +5
Electricity users are the major players of the electric systems, and electricity consumption is growing at an extraordinary rate. The research on electricity consumption behaviors…
BigDataBench: A Scalable and Unified Big Data and AI Benchmark Suite
Wanling Gao, Jianfeng Zhan, Lei Wang +11
Several fundamental changes in technology indicate domain-specific hardware and software co-design is the only path left. In this context, architecture, system, data management, an…
BOPS, Not FLOPS! A New Metric and Roofline Performance Model For Datacenter Computing
Lei Wang, Jianfeng Zhan, Wanling Gao +5
For emerging datacenter (in short, DC) workloads, such as online Internet services or offline data analytics, how to evaluate the upper bound performance and provide apple-to-apple…
HybridTune: Spatio-temporal Data and Model Driven Performance Diagnosis for Big Data Systems
Rui Ren, Jiechao Cheng, Xiwen He +3
With tremendous growing interests in Big Data systems, analyzing and facilitating their performance improvement become increasingly important. Although there have much research eff…
Deep Convolutional Neural Networks for Anomaly Event Classification on Distributed Systems
Jiechao Cheng, Rui Ren, Lei Wang +1
The increasing popularity of server usage has brought a plenty of anomaly log events, which have threatened a vast collection of machines. Recognizing and categorizing the anomalou…
Cosine Normalization: Using Cosine Similarity Instead of Dot Product in Neural Networks
Chunjie Luo, Jianfeng Zhan, Lei Wang +1
Traditionally, multi-layer neural networks use dot product between the output vector of previous layer and the incoming weight vector as the input to activation function. The resul…
Characterization and Architectural Implications of Big Data Workloads
Lei Wang, Jianfeng Zhan, Zhen Jia +1
Big data areas are expanding in a fast way in terms of increasing workloads and runtime systems, and this situation imposes a serious challenge to workload characterization, which…