IHPC develops advanced computing techniques on various hardware architectures (e.g. multicore CPU, GPU, FPGA, ASIC) for various applications, especially compute-intensive AI/ML-oriented ones.
The main research areas include:
- Code optimisation for parallel & heterogeneous computing with modern hardware architectures.
- Edge AI computing: to enable ubiquitous AI deployment catering to demanding scenarios and constraints.
- Quantum computing: to understand quantum computing and quantum-inspired computing paradigms, and apply quantum computing to real-world applications.
Decentralised Computing focuses on data, computation, and intelligence across platforms and organisations, tackling the challenges of performance, scalability, cost-efficiency, privacy-preserving and trustworthy collaborations.
Research areas include:
- Distributed computation & system for efficient parallel data processing and adaptive resource provisioning on distributed system and framework.
- Distributed learning and interoperability on complex data flow, efficient analytics workflow, flexible model deployment on edge, on-premises and cloud platforms.
- Trusted computing & collaboration to technology convergence of Blockchain, secure multiparty computation and federated learning for trustworthy ecosystem.