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Minjie Xiang

dblp:276/2079 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 75% Parallel and multicore computing · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing › task scheduling
DAG scheduling
0.412020
On Computing Exact WCRT for DAG Tasks† · DAC 2020
Embedded and real-time systems
real-time scheduling
0.412020
On Computing Exact WCRT for DAG Tasks† · DAC 2020
Embedded and real-time systems › real-time scheduling › schedulability analysis
response time analysis
0.412020
On Computing Exact WCRT for DAG Tasks† · DAC 2020
Embedded and real-time systems › real-time scheduling › schedulability analysis › response time analysis
worst-case response time
0.412020
On Computing Exact WCRT for DAG Tasks† · DAC 2020

Methods — techniques the papers use, named apart from their topics

list scheduling · 0.4SMT · 0.4
YearPublicationVenuePosition
2020 On Computing Exact WCRT for DAG Tasks†
abstract
Most current real-time parallel applications can be modeled as a directed acyclic graph (DAG) task. Existing worst-case response time (WCRT) bounds (e.g., Graham's bound) derived for DAGs may be very pessimistic. No one precisely knows the gap between the WCRT bound and the actual WCRT. In this paper, we aim to derive the exact WCRT of a DAG task under the list scheduling upon multi-core platforms. We encode the WCRT analysis problem into a satisfaction modular theoretical (SMT) formulation based on insights into the list scheduling algorithm, and prove that our SMT program can solve the WCRT precisely, providing an accurate baseline to measure the tightness of the existing WCRT bounds. Experiments show that our method significantly improves the tightness of the WCRT bound, and is practically quite efficient, e.g., it can analyze DAGs with more than 40 vertices in a few seconds.
Jinghao Sun, Feng Li 0032, Nan Guan, Minjie Xiang, Zhishan Guo, Wang Yi 0001
DAC5