Name
Abstract | ||
|---|---|---|
MPI communication optimization is a crucial stage to optimize high-performance applications. As a formal analysis of MPI communication, the communication performance models have made some achievements in improving the efficiency of collective algorithms and optimizing communication scheduling. However, previous models are difficult to model asynchronous concurrent communication and do not take into account numerous contention factors. In this paper, we present C-Lop, an incremental MPI performance model based on τ-Lop. Firstly, C-Lop proposes a method for asynchronous modeling of concurrent communication. As the only model that considers concurrent transmission, τ-Lop describes the cost of the all processes as a whole without distinguishing the cost of each process. Here, C-Lop uses the idea of asynchronous modeling that describe the cost of the system by averaging the communication cost per process. It can describe the communication cost for some systems with out-of-sync communication more accurately. Moreover, C-Lop introduces the parameter C to represent the contention, and considers the contention of concurrent transmissions on network-on-chip, data reuse, and contention of noncommunication processes to make a more accuracy estimation. Furthermore, parameter C can be customized to fit more application scenarios. In addition, we evaluate several common collective algorithms, a matrix multiplication algorithm (SUMMA), and two kinds of communication in a three-dimensional multi-grid application on the Tianhe-3 prototype, and results show that C-Lop outperforms the competition. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.parco.2022.102925 | Parallel Computing |
Keywords | DocType | Volume |
Parallel performance models,Message passing interface,Performance analysis,Multicore clusters | Journal | 111 |
ISSN | Citations | PageRank |
0167-8191 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ziheng Wang | 1 | 0 | 1.01 |
| Heng Chen | 2 | 0 | 3.72 |
| Weiling Cai | 3 | 0 | 0.34 |
| Xiaoshe Dong | 4 | 172 | 51.44 |
| Xingjun Zhang | 5 | 81 | 34.06 |