On Task Mapping in Multi-chiplet Based Many-Core Systems to Optimize Inter- and Intra-chiplet Communications

Multi-chiplet system design, by integrating multiple chiplets/dielets within a single package, has emerged as a promising paradigm in the post-Moore era. This paper introduces a novel task mapping algorithm for multi-chiplet based many-core systems, addressing the unique challenges posed by intra- and inter-chiplet communications under power and thermal constraints. Traditional task mapping algorithms fail to account for the latency and bandwidth differences between these communications, leading to sub-optimal performance in multi-chiplet systems. Our proposed algorithm employs a two-step process: (1) task assignment to chiplets using binary linear programming, leveraging a totally unimodular constraint matrix, and (2) intra-chiplet mapping that minimizes communication latency while considering both thermal and power constraints. This method strategically positions tasks with extensive inter-chiplet communication near interface nodes and centralizes those with predominant intra-chiplet communication. Experimental results demonstrate that the proposed algorithm outperforms existing methods (DAR and IOA) with a 37.5% and 24.7% reduction in execution time, respectively. Communication latency is also reduced by up to 43.2% and 32.9%, compared to DAR and IOA. These findings affirm that the proposed task mapping algorithm aligns well with the characteristics of multi-chiplet based many-core systems, and thus improves optimal performance.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Computers
Published
2024-11-18
DOI
https://doi.org/10.1109/tc.2024.3500354
Citations
4
Primary Topic
Interconnection Networks and Systems
Type
article
Field-Weighted Citation Impact
1.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On Task Mapping in Multi-chiplet Based Many-Core Systems to Optimize Inter- and Intra-chiplet Communications

Amit Kumar Singh, Yingtao Jiang, Yang Yang, Yifan Wang et al.
4 citations
IEEE Transactions on Computers
Interconnection Networks and Systems
1.40
article

On Task Mapping in Multi-chiplet Based Many-Core Systems to Optimize Inter- and Intra-chiplet Communications

Amit Kumar Singh, Yingtao Jiang, Yang Yang, Yifan Wang, Xiaohang Wang
article en
4 citations

Abstract

Multi-chiplet system design, by integrating multiple chiplets/dielets within a single package, has emerged as a promising paradigm in the post-Moore era. This paper introduces a novel task mapping algorithm for multi-chiplet based many-core systems, addressing the unique challenges posed by intra- and inter-chiplet communications under power and thermal constraints. Traditional task mapping algorithms fail to account for the latency and bandwidth differences between these communications, leading to sub-optimal performance in multi-chiplet systems. Our proposed algorithm employs a two-step process: (1) task assignment to chiplets using binary linear programming, leveraging a totally unimodular constraint matrix, and (2) intra-chiplet mapping that minimizes communication latency while considering both thermal and power constraints. This method strategically positions tasks with extensive inter-chiplet communication near interface nodes and centralizes those with predominant intra-chiplet communication. Experimental results demonstrate that the proposed algorithm outperforms existing methods (DAR and IOA) with a 37.5% and 24.7% reduction in execution time, respectively. Communication latency is also reduced by up to 43.2% and 32.9%, compared to DAR and IOA. These findings affirm that the proposed task mapping algorithm aligns well with the characteristics of multi-chiplet based many-core systems, and thus improves optimal performance.

IEEE Transactions on ComputersVol. 74(2)
University of Essex (GB), University of Nevada, Las Vegas (US), Zhejiang University (CN)
Openalex Percentile: Top 16%
Interconnection Networks and Systems
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

On Task Mapping in Multi-chiplet Based Many-Core Systems to Optimize Inter- and Intra-chiplet Communications — Amit Kumar Singh, Yingtao Jiang, et al. · IEEE Transactions on Computers (2024) | TGRS Research Map | TGRS