Members of the NPC committees will choose the organization mode (in-person, remote, or hybrid) during September 2021 because of the uncertainties related to the pandemic.
High-Performance Computing and Big Data are two main areas where NPC 2021 will provide a dynamic forum to explore, discuss and debate state-of-the-art technology issues and challenges. High-performance computers and big-data systems are tied inextricably to the broader computing ecosystem and its designs and market adoption.
We strongly believe that the stakes are high and are far beyond the boundaries of nations and continents.
We invite all researchers around the world to submit papers to NPC 2021.
We share the view that, during the past decade, the tools and cultures of high-performance computing and big data analytics are diverging to the detriment of both, and the international community should find a unified path that can best serve the needs of a broad spectrum of major application areas. Unlike other tools, which are limited to particular scientific domains, computational modeling and data analytics are applicable to all areas of science and engineering, as they breathe life into the underlying mathematics of scientific models.
Topics of interest include, but are not limited to:
Parallel and distributed applications and algorithms
- Parallel and distributed issues and opportunities on artificial intelligence applications.
- Parallel algorithms for computational and data-enabled scientific, engineering, biological and medical applications.
- Parallel algorithms for accelerators, neuromorphic architectures, and other emerging architectures.
Parallel and distributed architectures and systems
- Domain-Specific Accelerators for AI, deep learning and applications in industry sectors (such as health: genomics, finance: block chain, and others)
- Non-traditional Computing Technology (Quantum/Optical/Superconducting computers)
- Emerging architectures and systems at all scales, from embedded to cloud.
- Systems for enabling parallelism at an extreme scale.
- Power-efficient and green computing systems.
- Neuromorphic architectures and cognitive computing accelerators.
- Heterogeneous multicore architectures and accelerators.
- In-Memory and near-data computing.
- Network and interconnect architectures.
- Storage systems in novel big data architectures.
- IoT and Edge Computing related topics.
Parallel and distributed software environments and tools
- Programming models and compilation for existing and emerging platforms.
- Dataflow programming models, frameworks, languages and environments for data-enabled platforms.
- Virtualization of machines, networks, and storage.
- I/O, file systems, and data management.
- Resource management, scheduling, and load balancing.