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ParaMo 2021 : The 3rd International Workshop on Parallel Programming Models in High-Performance Cloud


When Aug 30, 2021 - Aug 31, 2021
Where virtual
Submission Deadline Jun 14, 2021
Notification Due Jun 30, 2021
Final Version Due Jul 14, 2021
Categories    high performance computing   programming models   parallel/distributed   cloud

Call For Papers

The 3rd International Workshop on Parallel Programming Models in High-Performance Cloud
August 30/31, 2021

In conjunction with Euro-Par 2021

Submission deadline: June 14, 2021 (extended), 23:59 Anywhere on Earth(AoE)
Acceptance notification: June 30, 2021
Camera-ready due: July 14, 2021
Workshop date: August 30/31, 2021
The notion of cloud computing has changed the way how we utilize computing resources. Since High-Performance Computing (HPC) has long been suffered from under- or over-utilization of resources, many researchers are trying to adapt HPC applications, such as AI, big data, and computational science, to the cloud environment. With proper adaptation, HPC applications are able to enhance their resource utilization ratio and scalability by using virtualized and on-demand resources on clouds. While we discuss HPC on clouds, we should discuss the parallel programming models as well. Various parallel programming models and their frameworks (e.g., TensorFlow, PyTorch, MapReduce, MPI, OpenMP, OpenCL, CUDA) have been proposed for parallel computing. These parallel programming models and frameworks should be carefully designed for HPC applications to achieve high-performance and efficient resource usage in clouds as new architectures and workloads are emerging. For example, we have to address data locality, resource management, programming environments and algorithms. The ParaMo workshop will provide a venue for researchers to discuss such challenges to parallel programming models in high-performance cloud.

The topics include, but are not limited to:
Parallel and distributed programming models and frameworks for machine learning (e.g., TensorFlow and PyTorch) in the cloud
Parallel programming models and frameworks for large scale data processing (e.g., MapReduce and Spark) in the cloud
Parallel programming models and frameworks for massively parallel computing (e.g., MPI, OpenMP, and OpenCL) in the cloud
High-performance network management in the cloud
High-performance storage and memory management in the cloud
Heterogeneous resource management (e.g., multi-core CPUs and accelerators) in the cloud
Load balancing schemes for HPC applications in the cloud
OS and runtime support for parallel programming models in the cloud
Energy efficient resource management and parallel programming models in the cloud
Resource management for virtualized environments
Performance evaluation of HPC applications in the cloud
Configurational optimization for HPC applications in the cloud

The submissions should follow the LNCS format. They should be between 10 to 12 pages. Each submission will be reviewed by at least three members of program committee, on the basis of relevance, originality, and clarity. Paper should be submitted electronically via EasyChair. The submission link will be announced shortly in this page.

Sangyoon Oh(Ajou University, Korea)
Hyun-Wook Jin(Konkuk University, Korea)

Publicity Chair: Sangho Yeo

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