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ParaMo 2021 : The 3rd International Workshop on Parallel Programming Models in High-Performance Cloud | |||||||||||||||
Link: https://sites.google.com/view/paramo-workshop/home | |||||||||||||||
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Call For Papers | |||||||||||||||
ParaMo 2021 - 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 https://sites.google.com/view/paramo-workshop/home ==================================================================================== IMPORTANT DATES ==================================================================================== 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 ==================================================================================== OVERVIEW ==================================================================================== 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 ==================================================================================== SUBMISSION INSTRUCTIONS ==================================================================================== 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. ==================================================================================== WORKSHOP CO-CHAIRS ==================================================================================== Sangyoon Oh(Ajou University, Korea) Hyun-Wook Jin(Konkuk University, Korea) ==================================================================================== CONTACT ==================================================================================== Publicity Chair: Sangho Yeo Email: soboru963@ajou.ac.kr |
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