Paper Info
Title
BigDataBench: A Dwarf-based Big Data and AI Benchmark Suite.
Abstract
As architecture, system, data management, and machine learning communities pay greater attention to innovative big data and data-driven artificial intelligence (in short, AI) algorithms, architecture, and systems, the pressure of benchmarking rises. However, complexity, diversity, frequently changed workloads, and rapid evolution of big data, especially AI systems raise great challenges in benchmarking. First, for the sake of conciseness, benchmarking scalability, portability cost, reproducibility, and better interpretation of performance data, we need understand what are the abstractions of frequently-appearing units of computation, which we call dwarfs, among big data and AI workloads. Second, for the sake of fairness, the benchmarks must include diversity of data and workloads. Third, for co-design of software and hardware, the benchmarks should be consistent across different communities. Other than creating a new benchmark or proxy for every possible workload, we propose using dwarf-based benchmarks--the combination of eight dwarfs--to represent diversity of big data and AI workloads. The current version--BigDataBench 4.0 provides 13 representative real-world data sets and 47 big data and AI benchmarks, including seven workload types: online service, offline analytics, graph analytics, AI, data warehouse, NoSQL, and streaming. BigDataBench 4.0 is publicly available from this http URL Also, for the first time, we comprehensively characterize the benchmarks of seven workload types in BigDataBench 4.0 in addition to traditional benchmarks like SPECCPU, PARSEC and HPCC in a hierarchical manner and drill down on five levels, using the Top-Down analysis from an architecture perspective.
Year
Venue
Field
2018
arXiv: Distributed, Parallel, and Cluster Computing
Data warehouse,Computer science,Drill down,NoSQL,Analytics,Data management,Big data,Benchmarking,Database,Scalability
DocType
Volume
Citations 
Journal
abs/1802.08254
0
PageRank 
References 
Authors
0.34
0
12
Name
Order
Citations
PageRank
Wanling Gao129919.12
Jianfeng Zhan201.69
Lei Wang357746.85
Chunjie Luo443421.86
Daoyi Zheng552.81
Rui Ren601.69
Chen Zheng72137.64
Gang Lu831112.40
Jingwei Li926514.38
Zheng Cao1003.04
Shujie Zhang112367.32
Haoning Tang1200.68