Focus
- Design, analysis, and engineering of distributed and parallel algorithms
- Theoretical foundations, models, and complexity issues
- Data structures for parallel and distributed algorithms
- Emerging paradigms for parallel and distributed computation
- Theory and algorithms for emerging parallel/distributed architectures
- Lower bounds for parallel/distributed computing
- Approximation and randomized algorithms
- Algorithms for combinatorial and graph problems
- Algorithms for sparse and dense numerical linear algebra
- Algorithms and models for Big Data/Data-intensive computing
- Algorithms for routing and information dissemination in networks
- Algorithms for social networks
- Algorithms for dynamic networks
- Algorithms for cloud and edge computing
- Fault-tolerant and self-stabilizing algorithms
- Power/energy-efficient algorithms
- Tensor operations, low-rank approximation
- Theoretical aspects of dependable, secure, and privacy-preserving distributed systems
- Parallel/distributed aspects of learning and mining algorithms
- Theoretical aspects of emerging architectures
