Name
Abstract | ||
|---|---|---|
The previous major efforts on big data benchmark either propose a large amount of workloads (e.g. a recent comprehensive big data benchmark suite—BigDataBench [4]), which impose cognitive difficulty on workload characterization and serious benchmarking cost; or only select a few workloads according to so-called popularity[1], which lead to partial or biased observations. |
Year | Venue | DocType |
|---|---|---|
2015 | ISPASS | Journal |
Volume | Citations | PageRank |
abs/1506.07943 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Wang | 1 | 577 | 46.85 |
| Jianfeng Zhan | 2 | 767 | 62.86 |
| Zhen Jia | 3 | 338 | 17.82 |
| rui han | 4 | 0 | 0.34 |