In Hybrid Mode


Scopus H-Index of the previous PDGC Conferences {Click on the image to enlarge}

Keynote Speakers

Prominent international keynote speakers will be presenting the state of art in research in Parallel, Distributed and Grid Computing. (Click here to see more..)



2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC) will be organized at Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India. PDGC-2024 will serve as an international forum for researchers and practitioners interested in recent advances in the areas of parallel, distributed and grid computing. It will provide an opportunity to present and exchange advanced scientific and technological information in hardware, software and theoretical foundation in these areas. 


Jaypee University of Information Technology is located at Waknaghat, Solan, Himachal Pradesh 173234, India. It is situated near Shimla (24 Km) just 3 Km off the NH22 (Delhi-Ambala-Kalka-Waknaghat-Shimla road). Convenient airports are Shimla (30 Km), Chandigarh (100 Km), New Delhi (350 Km) and Amritsar (350 Km).



Track-1: Parallel and Distributed Algorithms: Design and analysis of distributed algorithms, data-intensive and compute intensive parallel algorithms, advances in parallel algorithms, performance studies, scalability of algorithms and data structures for parallel and distributed systems, communication and synchronization protocols, network algorithms, Algorithms and systems for Internet of Things, multiprocessor and multi-core architectures and algorithms, Parallel Algorithms, Algorithms Exploiting Clusters and General-Purpose Distributed and Parallel Systems

Track-2: Dependable, Cluster and Grid Computing: Computer-supported cooperative work, Fault-tolerance, Self-stabilization, Performance Prediction and Analysis, Simulation, Knowledge-based Program Development, Collaboration Technologies, Communication and Networking Systems, Data Analysis and Management on Grids, Data Grids, Grid Computing Infrastructures, Middleware and Tools, Grid Computing Services, Grid Infrastructures for Data Analysis, Grid Standards as related to Applications, Hybrid & Embedded Parallel Systems, Memory Organization, Support for Parallel I/O, Multi/Many Core Systems, GPU and FPGA based Parallel Systems, Heterogeneous Distributed Systems, Distributed Shared Memory Systems, Distributed Object-oriented Systems

Track-3: Applications of parallel and distributed computing: Big data applications, parallel crowd sourcing, large-scale social network analysis, management of big data, cloud and grid computing, high performance supercomputing, the use of supercomputers to solve complex modelling problems in a spectrum of disciplines, scientific and biomedical applications, mobile computing, Pervasive computing, P2P computing, ubiquitous computing, Green computing, Affective computing, Cloud, edge and fog computing and, Machine learning and Deep learning applications in healthcare etc., AI in Distributed Systems, Real Time Distributed Systems

Track-4: Resource management and Fault Tolerance in parallel and distributed systems: Resource scheduling, load balancing, discovery and allocation, and optimization, fault-tolerance, reliability and availability of distributed systems, performance analysis of parallel applications, performance modelling and evaluation

Track-5: Parallel and distributed architectures: Architectures for instruction-level and thread-level parallelism, architectural characteristics, design, analysis, implementation, multi-core processors, heterogeneous many-core systems, novel big data architectures, graphics processors architecture, impact of technology on architecture, architecture for emerging technologies e.g., novel memory technologies, quantum computing, network and interconnect architectures, parallel I/O and storage systems, architecture of the memory hierarchy, power-efficient and green computing architectures,  P2P architectures; dependable architectures

Track-6: Parallel and distributed software: Parallel and multi-core programming languages and compilers, runtime systems, distributed operating systems and middleware, system software for parallel computer systems including programming languages and compilation techniques, Internet computing and web services, resource management including green computing, middleware for grids, clouds, and data centres, libraries, parallel programming paradigms, and programming environments and tools, Configuration, Policy, Management Issues

Track-7: Security in distributed computing: Security in computational and data grids, security in distributed environments, cryptographic protocols, protocols for communication networks and peer-to-peer systems, biometric systems, cyber security, trust, security and privacy

Track-8: Distributed and parallel databases: Big data storage and processing, query processing and optimization, social networks, storage, indexing, and physical database design, graph data management, data mining and knowledge discovery

Track-9: Networks, Interconnection Networks and Network based Computing, Multimedia & Service Networking: Scalable Networks, Reconfigurable Networks, Routing Issues, General-Purpose Network Performance for Distributed Applications, Network Protocols, Internet Technology, Optical Interconnections and Computing, Novel Network Topologies, Web Computing, Cluster Computing, Cloud Computing, Computational Grids, Data Grids, Semantic Grid, Mobile Agents, Distributed Web Services, Multimedia Communications and Services, Real-time Networking, Performance Modelling, Networked Real-time Embedded Systems, Services on Demand, Network Management, Multimedia Architectures and Protocols, Multimedia Applications, Quality of Service Support, Operating System and Networking Support, Internet Tools and Applications, Audio/Video Delivery over the Internet.

Track-10: Cloud and Big Data Computing: Actor Model, Cluster Manager, Redundant Array of Inexpensive Servers, Utility computing, Virtual Private Cloud, Cloud Computing Techniques for Big Data, Algorithms and Programming Techniques for Big Data Processing, Model and Languages for Big Data, Persistence and Preservation Algorithms and Systems for Big Data search, Distributed and Peer to Peer search, Large Scale Social Media and Recommendation Systems, Big Data Tool Kits, Anomaly Detection in Very Large Scale Systems, Parallel and Distributed Data Mining Algorithms, Web-based Computing and Service-Oriented Architecture, Wireless and Mobile Computing, Algorithms Design and Analysis, Artificial Intelligence, Computer Vision, Neural Networks and Fuzzy Logic, Biologically Inspired Computing, Systems Biology, Cyber-Physical Systems, Wireless Sensor Networks, Remote Sensing, Social Networks (Social Media), Human Computer Interaction, Graph Embedding, Computer Graphics and Virtual Reality, Nanotechnology in High Performance Computing.

Track-11: Machine Learning, Deep Learning and AI Ethics in Distributed Systems, Parallel and Grid Computing: Profiling and Social Networking, Recommendation Systems, Reinforcement Learning, Sentiment Analysis, Cyber Physical Systems, Society of Apps, Speech Technologies, Topic Detection, Trustworthy Computing, Authenticity, Honesty & Deception, Constraint Satisfaction Problems, Ethics and AI, Explainability in AI, Federated Learning, Metalearning, Neuro-symbolic Computing, Affective Computing, Business Analytics, Computational Intelligence, Customer relation analysis, Health Care Systems, Intelligent Manufacturing, Knowledge Management, Smart Cities.

Track-12: Blockchain Integration and Applications in Parallel, Distributed, and Grid Computing environment: Parallel blockchain architectures and scalability solutions, blockchain consensus mechanisms in distributed systems, Smart contracts in parallel and distributed systems, Data privacy and security using blockchain in grid computing environments, blockchain's role in distributed ledger technologies and decentralized applications, blockchain's for healthcare, supply chain management, and financial services within the context of parallel, distributed, and grid computing.

Track-13: Biomedical and Health Informatics in Parallel, Distributed, and Grid Computing environment: Cloud, fog, and edge computing systems for biomedical data processing and analysis, exploiting parallel computation techniques, and GPU programming, for biomedical processing models, large-scale processing systems for multi-modal biomedical data, Deep learning-based processing and diagnostic analysis of biomedical data, such as nodule detection in CT images, enhancement of low-quality images, etc, Hardware or database architectures for large-scale multi-modal biomedical data.

The following IEEE societies will be requested for technical sponsorship:

  • IEEE Computer Society
  • IEEE Communications Society
  • IEEE Computational Intelligence Society
  • IEEE Engineering in Medicine and Biology Society
  • IEEE Information Theory Society
  • IEEE Robotics and Automation Society
  • IEEE Reliability Society
  • IEEE Society on Social Implications of Technology
  • IEEE Systems, Man, and Cybernetics Society
  • IEEE Signal Processing Society




  • IEEE Delhi Section





  • For information to all, that official email of PDGC-2024 is and
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