Conference Information
ICPP 2020: International Conference on Parallel Processing
https://jnamaral.github.io/icpp20/
Submission Date:
2020-03-02
Notification Date:
2020-05-19
Conference Date:
2020-08-17
Location:
Edmonton, Alberta, Canada
Years:
49
CCF: b   CORE: a   QUALIS: a2   Viewed: 37159   Tracked: 124   Attend: 21

Conference Location
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Call For Papers
ICPP, the International Conference on Parallel Processing, provides a forum for engineers and scientists in academia, industry and government to present their latest research findings in all aspects of parallel and distributed computing. ICPP 2020 will be held in the campus of the University of Alberta in Edmonton, Alberta, Canada. ICPP is one of the oldest computer science conferences and is a premier venue for presenting the latest research on all aspects of parallel processing. 

Topics of interest in ICPP 2020 Papers include, but not limited to:

Algorithms: Parallel and Distributed Algorithms, Parallel and Distributed Combinatorial & Numerical Methods, Scheduling Algorithms for Parallel and Distributed Applications and Platforms, Algorithmic Innovations for Parallel and Distributed Machine Learning

Applications: Parallel and Distributed Applications, Scalable Data Analytics & Applied Machine Learning, Computational and Data-driven Science & Engineering

Architecture: Micro Architecture for Parallel Computing, Parallel Computer Architecture and Accelerators Designs, Datacenter/Warehouse Computing Architecture, Machine Learning Architectures, Architecture Support for Networking, New Memory Technologies, Near-Memory Computing, Architectures for Edge Computing, Architectural Support for Reliability and Security.

Performance Modeling and Evaluation: Performance Modeling of Parallel or Distributed Computing, Performance Evaluations of Parallel or Distributed Systems; Simulation Models; Analytical Models; Measurement based Evaluation

Systems Software: Parallel and Distributed Programming Languages & Models, Programming Systems, Compilers, Libraries, Programming Infrastructures and Tools, Operating and Real-Time Systems, Middleware, Systems Software for Machine Learning
Last updated by Dou Sun in 2019-10-14
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
20113638122.3%
20092207132.3%
20082638130.8%
20062006432%
20052416928.6%
20041906534.2%
20031926935.9%
20021886735.6%
20011396546.8%
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