The 22nd IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC-2021) 
  
  May 21, 2021, Portland Hilton Downtown, Portland, Oregon, USA to be held in conjunction with IPDPS 2021. 
  
http://www.ieee-tcsc.org/2021/pdsec/
    
Important Dates:
	Paper submission due . . . . . . . . . . . . . . January 22, 2021
	Notification of Acceptance . . . . . . . . . . . February 28, 2021 
	Final camera-ready paper . . . . . . . . . . . . March 13, 2021
	Workshop Date  . . . . . . . . . . . . . . . . . May 21, 2021
  
Scope and Interests: 
	The technological trends in HPC system evolution indicates an increasing burden placed on application developers due to the management of the unprecedented complexity levels of hardware and its associated performance characteristics. Many existing scientific applications codes are unlikely to perform well on future systems without major modifications or even complete rewrites. In the future, it will be necessary to utilize, in concert, many characteristics such as multiple levels of parallelism, many lightweight cores, complex memory hierarchies, novel I/O technology, power capping, system-wide temporal/spatial performance heterogeneity and reliability concerns. The parallel and distributed computing (PDC) community has developed new programming models, algorithms, libraries and tools to meet these challenges in order to accommodate productive code development and effective system use. However, the scientific application community still needs to identify the benefit through practical evaluations.

	Thus, the focus of this workshop is on methodologies and experiences used in scientific and engineering applications and algorithms to achieve sustainable code development for better productivity, application performance and reliability. In particular, we will focus on the following topics in parallel and distributed scientific and engineering applications, and not limited to:

	* Scalable parallel and distributed algorithms supporting science and engineering applications.

	* Performance portability across heterogeneous architectures.

	* Performance modeling and simulation for the execution of scalable scientific applications on new heterogeneous architectures.

	* Big scientific data.

	* Graph analytics with their (scientific) applications.

	* Code modernization methodologies and experiences for adapting the changes in future computing systems .

	* Languages for scientific computing on hybrid systems (e.g. Python, MPI+X where X is OpenMP, OpenCL, CUDA etc.).
	
	* Use cases of enterprise distributed computing technology (such as MapReduce, Data Analytics and Machine-learning tools) in scientific and engineering applications.
	
Paper Submission: TBA

Organizing Committee  
General Chairs
	Raphaël Couturier, University of Bourgogne Franche-Comt´e, France
	Peter Strazdins, The Australian National University, Australia

Program Chairs
	Srishti Srivastava, University of Southern Indiana, USA
	Sabine Roller, University of Siegen, Germany
  
Steering Chairs
	Laurence T. Yang, St. Francis Xavier University, Canada
	Thomas Rauber, University of Bayreuth, Germany
	Gudula Runger, Chemnitz University of Technology, Germany

Organizing Chair
	Neda Ebrahimi Pour, University of Siegen, Germany
	
Publicity Chair
	Suzanne Michelle Shontz, University of Kansas, USA  

Web Chair
	Sazzad Hussain, St. Francis Xavier University, Canada