2 citations · 3 across the 5 of their papers we have counts for
6 papers
Top-Down Microarchitecture Analysis Without Causal Modelling Is Dangerous!
Chenxi Wang, Lei Wang, Wanling Gao +3
Top-Down Microarchitecture Analysis (TMA) is the standard for identifying CPU bottlenecks. However, TMA implicitly models performance via a single causal path: Workload(dataset, al…
Inference of Component Effect on System Performance
Chenxi Wang, Lei Wang, Wanling Gao +5
In a computer system, multiple components--such as the CPU, memory, and others--work together as a system whose performance can be directly measured. However, the effect of a compo…
On Meta-Evaluation
Hongxiao Li, Chenxi Wang, Fanda Fan +4
Evaluation is the foundation of empirical science, yet the evaluation of evaluation itself -- so-called meta-evaluation -- remains strikingly underdeveloped. While methods such as…
Achieving Consistent and Comparable CPU Evaluation
Chenxi Wang, Lei Wang, Wanling Gao +5
The challenge of CPU evaluation lies in the fact that user-perceived performance metrics can only be measured on an independently running system consisting of the CPU and other ind…
Evaluatology: The Science and Engineering of Evaluation
Jianfeng Zhan, Lei Wang, Wanling Gao +10
Evaluation is a crucial aspect of human existence and plays a vital role in various fields. However, it is often approached in an empirical and ad-hoc manner, lacking consensus on…
WPC: Whole-picture Workload Characterization
Lei Wang, Kaiyong Yang, Chenxi Wang +7
This article raises an important and challenging workload characterization issue: can we uncover each critical component across the stacks contributing what percentages to any spec…