.png){kind=icon}
返回
On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems
.png){kind=icon}
OA
AI
DOI：10.1109/TNSE.2021.3095040.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In recent years, coded distributed computing (CDC) has attracted significant attention, because it can efficiently facilitate many delay-sensitive computation tasks against unexpected latencies in distributed computing systems. Despite such a salient feature, many design challenges and opportunities remain. In this paper, we focus on practical computing systems with heterogeneous computing resources, and design a novel CDC approach, called batch-processing based coded computing (BPCC), which exploits the fact that every computing node can obtain some coded results before it completes the whole task. To this end, we first describe the main idea of the BPCC framework, and then formulate an optimization problem for BPCC to minimize the task completion time by configuring the computation load. Through formal theoretical analyses, extensive simulation studies, and comprehensive real experiments on the Amazon EC2 computing clusters, we demonstrate promising performance of the proposed BPCC scheme, in terms of high computational efficiency and robustness to uncertain disturbances.
Keyword:
Task analysis
Distributed computing
Encoding
Optimization
Computational modeling
Heterogeneous networks
Resource management
Coded distributed computing
heterogeneous computing cluster
batch-processing
asymptotic optimality
latency
期刊
I
IF:
7.9
论文数:
2.6K
被引数:
10.0K
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容